interaction method applied: Topics by Science.gov

Sample records for interaction method applied

Microscopic Lagrangian description of warm plasmas. III - Nonlinear wave-particle interaction

NASA Technical Reports Server (NTRS)

Galloway, J. J.; Crawford, F. W.

1977-01-01

The averaged-Lagrangian method is applied to nonlinear wave-particle interactions in an infinite, homogeneous, magnetic-field-free plasma. The specific example of Langmuir waves is considered, and the combined effects of four-wave interactions and wave-particle interactions are treated. It is demonstrated how the latter lead to diffusion in velocity space, and the quasilinear diffusion equation is derived. The analysis is generalized to the random phase approximation. The paper concludes with a summary of the method as applied in Parts 1-3 of the paper.
Applying An Aptitude-Treatment Interaction Approach to Competency Based Teacher Education.

ERIC Educational Resources Information Center

McNergney, Robert

Aptitude treatment interaction (ATI), as applied to education, measures the interaction of personality factors and experimentally manipulated teaching strategies. ATI research has had dissappointingly inconclusive results so far, but proponents argue that this has been due to imprecise methods, which can be rectified. They believe that…
Generalized theoretical method for the interaction between arbitrary nonuniform electric field and molecular vibrations: Toward near-field infrared spectroscopy and microscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Iwasa, Takeshi, E-mail: tiwasa@mail.sci.hokudai.ac.jp; Takenaka, Masato; Taketsugu, Tetsuya

A theoretical method to compute infrared absorption spectra when a molecule is interacting with an arbitrary nonuniform electric field such as near-fields is developed and numerically applied to simple model systems. The method is based on the multipolar Hamiltonian where the light-matter interaction is described by a spatial integral of the inner product of the molecular polarization and applied electric field. The computation scheme is developed under the harmonic approximation for the molecular vibrations and the framework of modern electronic structure calculations such as the density functional theory. Infrared reflection absorption and near-field infrared absorption are considered as model systems.more » The obtained IR spectra successfully reflect the spatial structure of the applied electric field and corresponding vibrational modes, demonstrating applicability of the present method to analyze modern nanovibrational spectroscopy using near-fields. The present method can use arbitral electric fields and thus can integrate two fields such as computational chemistry and electromagnetics.« less
Generalized theoretical method for the interaction between arbitrary nonuniform electric field and molecular vibrations: Toward near-field infrared spectroscopy and microscopy.

PubMed

Iwasa, Takeshi; Takenaka, Masato; Taketsugu, Tetsuya

2016-03-28

A theoretical method to compute infrared absorption spectra when a molecule is interacting with an arbitrary nonuniform electric field such as near-fields is developed and numerically applied to simple model systems. The method is based on the multipolar Hamiltonian where the light-matter interaction is described by a spatial integral of the inner product of the molecular polarization and applied electric field. The computation scheme is developed under the harmonic approximation for the molecular vibrations and the framework of modern electronic structure calculations such as the density functional theory. Infrared reflection absorption and near-field infrared absorption are considered as model systems. The obtained IR spectra successfully reflect the spatial structure of the applied electric field and corresponding vibrational modes, demonstrating applicability of the present method to analyze modern nanovibrational spectroscopy using near-fields. The present method can use arbitral electric fields and thus can integrate two fields such as computational chemistry and electromagnetics.
Split luciferase complementation assay to detect regulated protein-protein interactions in rice protoplasts in a large-scale format

PubMed Central

2014-01-01

Background The rice interactome, in which a network of protein-protein interactions has been elucidated in rice, is a useful resource to identify functional modules of rice signal transduction pathways. Protein-protein interactions occur in cells in two ways, constitutive and regulative. While a yeast-based high-throughput method has been widely used to identify the constitutive interactions, a method to detect the regulated interactions is rarely developed for a large-scale analysis. Results A split luciferase complementation assay was applied to detect the regulated interactions in rice. A transformation method of rice protoplasts in a 96-well plate was first established for a large-scale analysis. In addition, an antibody that specifically recognizes a carboxyl-terminal fragment of Renilla luciferase was newly developed. A pair of antibodies that recognize amino- and carboxyl- terminal fragments of Renilla luciferase, respectively, was then used to monitor quality and quantity of interacting recombinant-proteins accumulated in the cells. For a proof-of-concept, the method was applied to detect the gibberellin-dependent interaction between GIBBERELLIN INSENSITIVE DWARF1 and SLENDER RICE 1. Conclusions A method to detect regulated protein-protein interactions was developed towards establishment of the rice interactome. PMID:24987490
CTE method and interaction solutions for the Kadomtsev-Petviashvili equation

NASA Astrophysics Data System (ADS)

Ren, Bo

2017-02-01

The consistent tanh expansion method is applied to the Kadomtsev-Petviashvili equation. The interaction solutions among one soliton and other types of solitary waves, such as multiple resonant soliton solutions and cnoidal waves, are explicitly given. Some special concrete interaction solutions are discussed both in analytical and graphical ways.
Interactive Anatomical and Surgical Live Stream Lectures Improve Students' Academic Performance in Applied Clinical Anatomy

ERIC Educational Resources Information Center

Shiozawa, Thomas; Butz, Benjamin; Herlan, Stephan; Kramer, Andreas; Hirt, Bernhard

2017-01-01

Tuebingen's "Sectio Chirurgica" (TSC) is an innovative, interactive, multimedia, and transdisciplinary teaching method designed to complement dissection courses. The Tuebingen's "Sectio Chirurgica" (TSC) allows clinical anatomy to be taught via interactive live stream surgeries moderated by an anatomist. This method aims to…
A Spatial-frequency Method for Analyzing Antenna-to-Probe Interactions in Near-field Antenna Measurements.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brock, Billy C.

The measurement of the radiation characteristics of an antenna on a near-field range requires that the antenna under test be located very close to the near-field probe. Although the direct coupling is utilized for characterizing the near field, this close proximity also presents the opportunity for significant undesired interactions (for example, reflections) to occur between the antenna and the near-field probe. When uncompensated, these additional interactions will introduce error into the measurement, increasing the uncertainty in the final gain pattern obtained through the near-field-to-far-field transformation. Quantifying this gain-uncertainty contribution requires quantifying the various additional interactions. A method incorporating spatial-frequency analysismore » is described which allows the dominant interaction contributions to be easily identified and quantified. In addition to identifying the additional antenna-to-probe interactions, the method also allows identification and quantification of interactions with other nearby objects within the measurement room. Because the method is a spatial-frequency method, wide-bandwidth data is not required, and it can be applied even when data is available at only a single temporal frequency. This feature ensures that the method can be applied to narrow-band antennas, where a similar time-domain analysis would not be possible. - 3 - - 4 -« less
Improving Method-in-Use through Classroom Observation

ERIC Educational Resources Information Center

Nunn, Roger

2011-01-01

Method-in-use (Nunn, Describing classroom interaction in intercultural curricular research and development, University of Reading, 1996, International Review of Applied Linguistics in Language Teaching 37: 23-42, 1999) is a description of the method actually being enacted through classroom interaction in a particular context. The description is…
Macromolecular Competition Titration Method: Accessing Thermodynamics of the Unmodified Macromolecule–Ligand Interactions Through Spectroscopic Titrations of Fluorescent Analogs

PubMed Central

Bujalowski, Wlodzimierz; Jezewska, Maria J.

2011-01-01

Analysis of thermodynamically rigorous binding isotherms provides fundamental information about the energetics of the ligand–macromolecule interactions and often an invaluable insight about the structure of the formed complexes. The Macromolecular Competition Titration (MCT) method enables one to quantitatively obtain interaction parameters of protein–nucleic acid interactions, which may not be available by other methods, particularly for the unmodified long polymer lattices and specific nucleic acid substrates, if the binding is not accompanied by adequate spectroscopic signal changes. The method can be applied using different fluorescent nucleic acids or fluorophores, although the etheno-derivatives of nucleic acid are especially suitable as they are relatively easy to prepare, have significant blue fluorescence, their excitation band lies far from the protein absorption spectrum, and the modification eliminates the possibility of base pairing with other nucleic acids. The MCT method is not limited to the specific size of the reference nucleic acid. Particularly, a simple analysis of the competition titration experiments is described in which the fluorescent, short fragment of nucleic acid, spanning the exact site-size of the protein–nucleic acid complex, and binding with only a 1:1 stoichiometry to the protein, is used as a reference macromolecule. Although the MCT method is predominantly discussed as applied to studying protein–nucleic acid interactions, it can generally be applied to any ligand–macromolecule system by monitoring the association reaction using the spectroscopic signal originating from the reference macromolecule in the presence of the competing macromolecule, whose interaction parameters with the ligand are to be determined. PMID:21195223
Estimating and Interpreting Latent Variable Interactions: A Tutorial for Applying the Latent Moderated Structural Equations Method

ERIC Educational Resources Information Center

Maslowsky, Julie; Jager, Justin; Hemken, Douglas

2015-01-01

Latent variables are common in psychological research. Research questions involving the interaction of two variables are likewise quite common. Methods for estimating and interpreting interactions between latent variables within a structural equation modeling framework have recently become available. The latent moderated structural equations (LMS)…
Epistasis analysis for quantitative traits by functional regression model.

PubMed

Zhang, Futao; Boerwinkle, Eric; Xiong, Momiao

2014-06-01

The critical barrier in interaction analysis for rare variants is that most traditional statistical methods for testing interactions were originally designed for testing the interaction between common variants and are difficult to apply to rare variants because of their prohibitive computational time and poor ability. The great challenges for successful detection of interactions with next-generation sequencing (NGS) data are (1) lack of methods for interaction analysis with rare variants, (2) severe multiple testing, and (3) time-consuming computations. To meet these challenges, we shift the paradigm of interaction analysis between two loci to interaction analysis between two sets of loci or genomic regions and collectively test interactions between all possible pairs of SNPs within two genomic regions. In other words, we take a genome region as a basic unit of interaction analysis and use high-dimensional data reduction and functional data analysis techniques to develop a novel functional regression model to collectively test interactions between all possible pairs of single nucleotide polymorphisms (SNPs) within two genome regions. By intensive simulations, we demonstrate that the functional regression models for interaction analysis of the quantitative trait have the correct type 1 error rates and a much better ability to detect interactions than the current pairwise interaction analysis. The proposed method was applied to exome sequence data from the NHLBI's Exome Sequencing Project (ESP) and CHARGE-S study. We discovered 27 pairs of genes showing significant interactions after applying the Bonferroni correction (P-values < 4.58 × 10(-10)) in the ESP, and 11 were replicated in the CHARGE-S study. © 2014 Zhang et al.; Published by Cold Spring Harbor Laboratory Press.
A strategy to apply quantitative epistasis analysis on developmental traits.

PubMed

Labocha, Marta K; Yuan, Wang; Aleman-Meza, Boanerges; Zhong, Weiwei

2017-05-15

Genetic interactions are keys to understand complex traits and evolution. Epistasis analysis is an effective method to map genetic interactions. Large-scale quantitative epistasis analysis has been well established for single cells. However, there is a substantial lack of such studies in multicellular organisms and their complex phenotypes such as development. Here we present a method to extend quantitative epistasis analysis to developmental traits. In the nematode Caenorhabditis elegans, we applied RNA interference on mutants to inactivate two genes, used an imaging system to quantitatively measure phenotypes, and developed a set of statistical methods to extract genetic interactions from phenotypic measurement. Using two different C. elegans developmental phenotypes, body length and sex ratio, as examples, we showed that this method could accommodate various metazoan phenotypes with performances comparable to those methods in single cell growth studies. Comparing with qualitative observations, this method of quantitative epistasis enabled detection of new interactions involving subtle phenotypes. For example, several sex-ratio genes were found to interact with brc-1 and brd-1, the orthologs of the human breast cancer genes BRCA1 and BARD1, respectively. We confirmed the brc-1 interactions with the following genes in DNA damage response: C34F6.1, him-3 (ortholog of HORMAD1, HORMAD2), sdc-1, and set-2 (ortholog of SETD1A, SETD1B, KMT2C, KMT2D), validating the effectiveness of our method in detecting genetic interactions. We developed a reliable, high-throughput method for quantitative epistasis analysis of developmental phenotypes.
A proximity-based graph clustering method for the identification and application of transcription factor clusters.

PubMed

Spadafore, Maxwell; Najarian, Kayvan; Boyle, Alan P

2017-11-29

Transcription factors (TFs) form a complex regulatory network within the cell that is crucial to cell functioning and human health. While methods to establish where a TF binds to DNA are well established, these methods provide no information describing how TFs interact with one another when they do bind. TFs tend to bind the genome in clusters, and current methods to identify these clusters are either limited in scope, unable to detect relationships beyond motif similarity, or not applied to TF-TF interactions. Here, we present a proximity-based graph clustering approach to identify TF clusters using either ChIP-seq or motif search data. We use TF co-occurrence to construct a filtered, normalized adjacency matrix and use the Markov Clustering Algorithm to partition the graph while maintaining TF-cluster and cluster-cluster interactions. We then apply our graph structure beyond clustering, using it to increase the accuracy of motif-based TFBS searching for an example TF. We show that our method produces small, manageable clusters that encapsulate many known, experimentally validated transcription factor interactions and that our method is capable of capturing interactions that motif similarity methods might miss. Our graph structure is able to significantly increase the accuracy of motif TFBS searching, demonstrating that the TF-TF connections within the graph correlate with biological TF-TF interactions. The interactions identified by our method correspond to biological reality and allow for fast exploration of TF clustering and regulatory dynamics.
Active subnetwork recovery with a mechanism-dependent scoring function; with application to angiogenesis and organogenesis studies

PubMed Central

2013-01-01

Background The learning active subnetworks problem involves finding subnetworks of a bio-molecular network that are active in a particular condition. Many approaches integrate observation data (e.g., gene expression) with the network topology to find candidate subnetworks. Increasingly, pathway databases contain additional annotation information that can be mined to improve prediction accuracy, e.g., interaction mechanism (e.g., transcription, microRNA, cleavage) annotations. We introduce a mechanism-based approach to active subnetwork recovery which exploits such annotations. We suggest that neighboring interactions in a network tend to be co-activated in a way that depends on the “correlation” of their mechanism annotations. e.g., neighboring phosphorylation and de-phosphorylation interactions may be more likely to be co-activated than neighboring phosphorylation and covalent bonding interactions. Results Our method iteratively learns the mechanism correlations and finds the most likely active subnetwork. We use a probabilistic graphical model with a Markov Random Field component which creates dependencies between the states (active or non-active) of neighboring interactions, that incorporates a mechanism-based component to the function. We apply a heuristic-based EM-based algorithm suitable for the problem. We validated our method’s performance using simulated data in networks downloaded from GeneGO against the same approach without the mechanism-based component, and two other existing methods. We validated our methods performance in correctly recovering (1) the true interaction states, and (2) global network properties of the original network against these other methods. We applied our method to networks generated from time-course gene expression studies in angiogenesis and lung organogenesis and validated the findings from a biological perspective against current literature. Conclusions The advantage of our mechanism-based approach is best seen in networks composed of connected regions with a large number of interactions annotated with a subset of mechanisms, e.g., a regulatory region of transcription interactions, or a cleavage cascade region. When applied to real datasets, our method recovered novel and biologically meaningful putative interactions, e.g., interactions from an integrin signaling pathway using the angiogenesis dataset, and a group of regulatory microRNA interactions in an organogenesis network. PMID:23432934
A sampling framework for incorporating quantitative mass spectrometry data in protein interaction analysis.

PubMed

Tucker, George; Loh, Po-Ru; Berger, Bonnie

2013-10-04

Comprehensive protein-protein interaction (PPI) maps are a powerful resource for uncovering the molecular basis of genetic interactions and providing mechanistic insights. Over the past decade, high-throughput experimental techniques have been developed to generate PPI maps at proteome scale, first using yeast two-hybrid approaches and more recently via affinity purification combined with mass spectrometry (AP-MS). Unfortunately, data from both protocols are prone to both high false positive and false negative rates. To address these issues, many methods have been developed to post-process raw PPI data. However, with few exceptions, these methods only analyze binary experimental data (in which each potential interaction tested is deemed either observed or unobserved), neglecting quantitative information available from AP-MS such as spectral counts. We propose a novel method for incorporating quantitative information from AP-MS data into existing PPI inference methods that analyze binary interaction data. Our approach introduces a probabilistic framework that models the statistical noise inherent in observations of co-purifications. Using a sampling-based approach, we model the uncertainty of interactions with low spectral counts by generating an ensemble of possible alternative experimental outcomes. We then apply the existing method of choice to each alternative outcome and aggregate results over the ensemble. We validate our approach on three recent AP-MS data sets and demonstrate performance comparable to or better than state-of-the-art methods. Additionally, we provide an in-depth discussion comparing the theoretical bases of existing approaches and identify common aspects that may be key to their performance. Our sampling framework extends the existing body of work on PPI analysis using binary interaction data to apply to the richer quantitative data now commonly available through AP-MS assays. This framework is quite general, and many enhancements are likely possible. Fruitful future directions may include investigating more sophisticated schemes for converting spectral counts to probabilities and applying the framework to direct protein complex prediction methods.
A Generalized Weizsacker-Williams Method Applied to Pion Production in Proton-Proton Collisions

NASA Technical Reports Server (NTRS)

Ahern, Sean C.; Poyser, William J.; Norbury, John W.; Tripathi, R. K.

2002-01-01

A new "Generalized" Weizsacker-Williams method (GWWM) is used to calculate approximate cross sections for relativistic peripheral proton-proton collisions. Instead of a mass less photon mediator, the method allows for the mediator to have mass for short range interactions. This method generalizes the Weizsacker-Williams method (WWM) from Coulomb interactions to GWWM for strong interactions. An elastic proton-proton cross section is calculated using GWWM with experimental data for the elastic p+p interaction, where the mass p+ is now the mediator. The resulting calculated cross sections is compared to existing data for the elastic proton-proton interaction. A good approximate fit is found between the data and the calculation.
Transition-density-fragment interaction combined with transfer integral approach for excitation-energy transfer via charge-transfer states

NASA Astrophysics Data System (ADS)

Fujimoto, Kazuhiro J.

2012-07-01

A transition-density-fragment interaction (TDFI) combined with a transfer integral (TI) method is proposed. The TDFI method was previously developed for describing electronic Coulomb interaction, which was applied to excitation-energy transfer (EET) [K. J. Fujimoto and S. Hayashi, J. Am. Chem. Soc. 131, 14152 (2009)] and exciton-coupled circular dichroism spectra [K. J. Fujimoto, J. Chem. Phys. 133, 124101 (2010)]. In the present study, the TDFI method is extended to the exchange interaction, and hence it is combined with the TI method for applying to the EET via charge-transfer (CT) states. In this scheme, the overlap correction is also taken into account. To check the TDFI-TI accuracy, several test calculations are performed to an ethylene dimer. As a result, the TDFI-TI method gives a much improved description of the electronic coupling, compared with the previous TDFI method. Based on the successful description of the electronic coupling, the decomposition analysis is also performed with the TDFI-TI method. The present analysis clearly shows a large contribution from the Coulomb interaction in most of the cases, and a significant influence of the CT states at the small separation. In addition, the exchange interaction is found to be small in this system. The present approach is useful for analyzing and understanding the mechanism of EET.
Human-computer interface including haptically controlled interactions

DOEpatents

Anderson, Thomas G.

2005-10-11

The present invention provides a method of human-computer interfacing that provides haptic feedback to control interface interactions such as scrolling or zooming within an application. Haptic feedback in the present method allows the user more intuitive control of the interface interactions, and allows the user's visual focus to remain on the application. The method comprises providing a control domain within which the user can control interactions. For example, a haptic boundary can be provided corresponding to scrollable or scalable portions of the application domain. The user can position a cursor near such a boundary, feeling its presence haptically (reducing the requirement for visual attention for control of scrolling of the display). The user can then apply force relative to the boundary, causing the interface to scroll the domain. The rate of scrolling can be related to the magnitude of applied force, providing the user with additional intuitive, non-visual control of scrolling.
Genome-wide gene–gene interaction analysis for next-generation sequencing

PubMed Central

Zhao, Jinying; Zhu, Yun; Xiong, Momiao

2016-01-01

The critical barrier in interaction analysis for next-generation sequencing (NGS) data is that the traditional pairwise interaction analysis that is suitable for common variants is difficult to apply to rare variants because of their prohibitive computational time, large number of tests and low power. The great challenges for successful detection of interactions with NGS data are (1) the demands in the paradigm of changes in interaction analysis; (2) severe multiple testing; and (3) heavy computations. To meet these challenges, we shift the paradigm of interaction analysis between two SNPs to interaction analysis between two genomic regions. In other words, we take a gene as a unit of analysis and use functional data analysis techniques as dimensional reduction tools to develop a novel statistic to collectively test interaction between all possible pairs of SNPs within two genome regions. By intensive simulations, we demonstrate that the functional logistic regression for interaction analysis has the correct type 1 error rates and higher power to detect interaction than the currently used methods. The proposed method was applied to a coronary artery disease dataset from the Wellcome Trust Case Control Consortium (WTCCC) study and the Framingham Heart Study (FHS) dataset, and the early-onset myocardial infarction (EOMI) exome sequence datasets with European origin from the NHLBI's Exome Sequencing Project. We discovered that 6 of 27 pairs of significantly interacted genes in the FHS were replicated in the independent WTCCC study and 24 pairs of significantly interacted genes after applying Bonferroni correction in the EOMI study. PMID:26173972

A fast and accurate method to predict 2D and 3D aerodynamic boundary layer flows

NASA Astrophysics Data System (ADS)

Bijleveld, H. A.; Veldman, A. E. P.

2014-12-01

A quasi-simultaneous interaction method is applied to predict 2D and 3D aerodynamic flows. This method is suitable for offshore wind turbine design software as it is a very accurate and computationally reasonably cheap method. This study shows the results for a NACA 0012 airfoil. The two applied solvers converge to the experimental values when the grid is refined. We also show that in separation the eigenvalues remain positive thus avoiding the Goldstein singularity at separation. In 3D we show a flow over a dent in which separation occurs. A rotating flat plat is used to show the applicability of the method for rotating flows. The shown capabilities of the method indicate that the quasi-simultaneous interaction method is suitable for design methods for offshore wind turbine blades.
Path-integral Monte Carlo method for Rényi entanglement entropies.

PubMed

Herdman, C M; Inglis, Stephen; Roy, P-N; Melko, R G; Del Maestro, A

2014-07-01

We introduce a quantum Monte Carlo algorithm to measure the Rényi entanglement entropies in systems of interacting bosons in the continuum. This approach is based on a path-integral ground state method that can be applied to interacting itinerant bosons in any spatial dimension with direct relevance to experimental systems of quantum fluids. We demonstrate how it may be used to compute spatial mode entanglement, particle partitioned entanglement, and the entanglement of particles, providing insights into quantum correlations generated by fluctuations, indistinguishability, and interactions. We present proof-of-principle calculations and benchmark against an exactly soluble model of interacting bosons in one spatial dimension. As this algorithm retains the fundamental polynomial scaling of quantum Monte Carlo when applied to sign-problem-free models, future applications should allow for the study of entanglement entropy in large-scale many-body systems of interacting bosons.
Lattice quantum chromodynamical approach to nuclear physics

NASA Astrophysics Data System (ADS)

Aoki, Sinya; Doi, Takumi; Hatsuda, Tetsuo; Ikeda, Yoichi; Inoue, Takashi; Ishii, Noriyoshi; Murano, Keiko; Nemura, Hidekatsu; Sasaki, Kenji; HAL QCD Collaboration

2012-09-01

We review recent progress in the HAL QCD method, which was recently proposed to investigate hadron interactions in lattice quantum chromodynamics (QCD). The strategy to extract the energy-independent non-local potential in lattice QCD is explained in detail. The method is applied to study nucleon-nucleon, nucleon-hyperon, hyperon-hyperon, and meson-baryon interactions. Several extensions of the method are also discussed.
A UNIFYING CONCEPT FOR ASSESSING TOXICOLOGICAL INTERACTIONS: CHANGES IN SLOPE

EPA Science Inventory

Robust statistical methods are important to the evaluation of interactions among chemicals in a mixture. However, different concepts of interaction as applied to the statistical analysis of chemical mixture toxicology data or as used in environmental risk assessment often can ap...
A Comparison of Interactional Aerodynamics Methods for a Helicopter in Low Speed Flight

NASA Technical Reports Server (NTRS)

Berry, John D.; Letnikov, Victor; Bavykina, Irena; Chaffin, Mark S.

1998-01-01

Recent advances in computing subsonic flow have been applied to helicopter configurations with various degrees of success. This paper is a comparison of two specific methods applied to a particularly challenging regime of helicopter flight, very low speeds, where the interaction of the rotor wake and the fuselage are most significant. Comparisons are made between different methods of predicting the interactional aerodynamics associated with a simple generic helicopter configuration. These comparisons are made using fuselage pressure data from a Mach-scaled powered model helicopter with a rotor diameter of approximately 3 meters. The data shown are for an advance ratio of 0.05 with a thrust coefficient of 0.0066. The results of this comparison show that in this type of complex flow both analytical techniques have regions where they are more accurate in matching the experimental data.
Demonstrating Functional Interactive Language Teaching in the Nigerian Universities

ERIC Educational Resources Information Center

Bello, Rachael O.; Oni-Buraimoh, Olawunmi O.

2014-01-01

Applied linguistics affords Linguists the opportunity of solving language related problems using various methods. In this paper, we x-ray the Nigerian University classroom situation in the teaching of the English language viz-a-viz the use of functional interactive method. Following Littlewood (1981) and Krashen (1982), we posit that the teaching…
A theoretical approach for estimation of ultimate size of bimetallic nanocomposites synthesized in microemulsion systems

NASA Astrophysics Data System (ADS)

Salabat, Alireza; Saydi, Hassan

2012-12-01

In this research a new idea for prediction of ultimate sizes of bimetallic nanocomposites synthesized in water-in-oil microemulsion system is proposed. In this method, by modifying Tabor Winterton approximation equation, an effective Hamaker constant was introduced. This effective Hamaker constant was applied in the van der Waals attractive interaction energy. The obtained effective van der Waals interaction energy was used as attractive contribution in the total interaction energy. The modified interaction energy was applied successfully to predict some bimetallic nanoparticles, at different mass fraction, synthesized in microemulsion system of dioctyl sodium sulfosuccinate (AOT)/isooctane.
Analysis Of Dynamic Interactions Between Solar Array Simulators And Spacecraft Power Conditioning And Distribution Units

NASA Astrophysics Data System (ADS)

Valdivia, V.; Barrado, A.; Lazaro, A.; Rueda, P.; Tonicello, F.; Fernandez, A.; Mourra, O.

2011-10-01

Solar array simulators (SASs) are hardware devices, commonly applied instead of actual solar arrays (SAs) during the design process of spacecrafts power conditioning and distribution units (PCDUs), and during spacecrafts assembly integration and tests. However, the dynamic responses between SASs and actual SAs are usually different. This fact plays an important role, since the dynamic response of the SAS may influence significantly the dynamic behaviour of the PCDU under certain conditions, even leading to instability. This paper deals with the dynamic interactions between SASs and PCDUs. Several methods for dynamic characterization of the SASs are discussed, and the response of commercial SASs widely applied in the space industry is compared to that of actual SAs. After that, the interactions are experimentally analyzed by using a boost converter connected to the aforementioned SASs, thus demonstrating their critical importance. The interactions are first tackled analytically by means of small-signal models, and finally a black-box modelling method of SASs is proposed as a useful tool to analyze the interactions by means of simulation. The capabilities of both the analytical method and the black- box model to predict the interactions are demonstrated.
Numerical Study of Rarefied Hypersonic Flow Interacting with a Continuum Jet. Degree awarded by Pennsylvania State Univ., Aug. 1999

NASA Technical Reports Server (NTRS)

Glass, Christopher E.

2000-01-01

An uncoupled Computational Fluid Dynamics-Direct Simulation Monte Carlo (CFD-DSMC) technique is developed and applied to provide solutions for continuum jets interacting with rarefied external flows. The technique is based on a correlation of the appropriate Bird breakdown parameter for a transitional-rarefied condition that defines a surface within which the continuum solution is unaffected by the external flow-jet interaction. The method is applied to two problems to assess and demonstrate its validity; one of a jet interaction in the transitional-rarefied flow regime and the other in the moderately rarefied regime. Results show that the appropriate Bird breakdown surface for uncoupling the continuum and non-continuum solutions is a function of a non-dimensional parameter relating the momentum flux and collisionality between the two interacting flows. The correlation is exploited for the simulation of a jet interaction modeled for an experimental condition in the transitional-rarefied flow regime and the validity of the correlation is demonstrated. The uncoupled technique is also applied to an aerobraking flight condition for the Mars Global Surveyor spacecraft with attitude control system jet interaction. Aerodynamic yawing moment coefficients for cases without and with jet interaction at various angles-of-attack were predicted, and results from the present method compare well with values published previously. The flow field and surface properties are analyzed in some detail to describe the mechanism by which the jet interaction affects the aerodynamics.
SELF-BLM: Prediction of drug-target interactions via self-training SVM.

PubMed

Keum, Jongsoo; Nam, Hojung

2017-01-01

Predicting drug-target interactions is important for the development of novel drugs and the repositioning of drugs. To predict such interactions, there are a number of methods based on drug and target protein similarity. Although these methods, such as the bipartite local model (BLM), show promise, they often categorize unknown interactions as negative interaction. Therefore, these methods are not ideal for finding potential drug-target interactions that have not yet been validated as positive interactions. Thus, here we propose a method that integrates machine learning techniques, such as self-training support vector machine (SVM) and BLM, to develop a self-training bipartite local model (SELF-BLM) that facilitates the identification of potential interactions. The method first categorizes unlabeled interactions and negative interactions among unknown interactions using a clustering method. Then, using the BLM method and self-training SVM, the unlabeled interactions are self-trained and final local classification models are constructed. When applied to four classes of proteins that include enzymes, G-protein coupled receptors (GPCRs), ion channels, and nuclear receptors, SELF-BLM showed the best performance for predicting not only known interactions but also potential interactions in three protein classes compare to other related studies. The implemented software and supporting data are available at https://github.com/GIST-CSBL/SELF-BLM.
Researching Online Foreign Language Interaction and Exchange: Theories, Methods and Challenges. Telecollaboration in Education. Volume 3

ERIC Educational Resources Information Center

Dooly, Melinda; O'Dowd, Robert

2012-01-01

This book provides an accessible introduction to some of the methods and theoretical approaches for investigating foreign language (FL) interaction and exchange in online environments. Research approaches which can be applied to Computer-Mediated Communication (CMC) are outlined, followed by discussion of the way in which tools and techniques for…
Combining multiple positive training sets to generate confidence scores for protein-protein interactions.

PubMed

Yu, Jingkai; Finley, Russell L

2009-01-01

High-throughput experimental and computational methods are generating a wealth of protein-protein interaction data for a variety of organisms. However, data produced by current state-of-the-art methods include many false positives, which can hinder the analyses needed to derive biological insights. One way to address this problem is to assign confidence scores that reflect the reliability and biological significance of each interaction. Most previously described scoring methods use a set of likely true positives to train a model to score all interactions in a dataset. A single positive training set, however, may be biased and not representative of true interaction space. We demonstrate a method to score protein interactions by utilizing multiple independent sets of training positives to reduce the potential bias inherent in using a single training set. We used a set of benchmark yeast protein interactions to show that our approach outperforms other scoring methods. Our approach can also score interactions across data types, which makes it more widely applicable than many previously proposed methods. We applied the method to protein interaction data from both Drosophila melanogaster and Homo sapiens. Independent evaluations show that the resulting confidence scores accurately reflect the biological significance of the interactions.
Projection-reduction method applied to deriving non-linear optical conductivity for an electron-impurity system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kang, Nam Lyong; Lee, Sang-Seok; Graduate School of Engineering, Tottori University, 4-101 Koyama-Minami, Tottori

2013-07-15

The projection-reduction method introduced by the present authors is known to give a validated theory for optical transitions in the systems of electrons interacting with phonons. In this work, using this method, we derive the linear and first order nonlinear optical conductivites for an electron-impurity system and examine whether the expressions faithfully satisfy the quantum mechanical philosophy, in the same way as for the electron-phonon systems. The result shows that the Fermi distribution function for electrons, energy denominators, and electron-impurity coupling factors are contained properly in organized manners along with absorption of photons for each electron transition process in themore » final expressions. Furthermore, the result is shown to be represented properly by schematic diagrams, as in the formulation of electron-phonon interaction. Therefore, in conclusion, we claim that this method can be applied in modeling optical transitions of electrons interacting with both impurities and phonons.« less
Membrane fouling in a submerged membrane bioreactor: New method and its applications in interfacial interaction quantification.

PubMed

Hong, Huachang; Cai, Xiang; Shen, Liguo; Li, Renjie; Lin, Hongjun

2017-10-01

Quantification of interfacial interactions between two rough surfaces represents one of the most pressing requirements for membrane fouling prediction and control in membrane bioreactors (MBRs). This study firstly constructed regularly rough membrane and particle surfaces by using rigorous mathematical equations. Thereafter, a new method involving surface element integration (SEI) method, differential geometry and composite Simpson's rule was proposed to quantify the interfacial interactions between the two constructed rough surfaces. This new method were then applied to investigate interfacial interactions in a MBR with the data of surface properties of membrane and foulants experimentally measured. The feasibility of the new method was verified. It was found that asperity amplitude and period of the membrane surface exerted profound effects on the total interaction. The new method had broad potential application fields especially including guiding membrane surface design for membrane fouling mitigation. Copyright © 2017 Elsevier Ltd. All rights reserved.
Numerical simulation of stress amplification induced by crack interaction in human femur bone

NASA Astrophysics Data System (ADS)

Alia, Noor; Daud, Ruslizam; Ramli, Mohammad Fadzli; Azman, Wan Zuki; Faizal, Ahmad; Aisyah, Siti

2015-05-01

This research is about numerical simulation using a computational method which study on stress amplification induced by crack interaction in human femur bone. Cracks in human femur bone usually occur because of large load or stress applied on it. Usually, the fracture takes longer time to heal itself. At present, the crack interaction is still not well understood due to bone complexity. Thus, brittle fracture behavior of bone may be underestimated and inaccurate. This study aims to investigate the geometrical effect of double co-planar edge cracks on stress intensity factor (K) in femur bone. This research focuses to analyze the amplification effect on the fracture behavior of double co-planar edge cracks, where numerical model is developed using computational method. The concept of fracture mechanics and finite element method (FEM) are used to solve the interacting cracks problems using linear elastic fracture mechanics (LEFM) theory. As a result, this study has shown the identification of the crack interaction limit (CIL) and crack unification limit (CUL) exist in the human femur bone model developed. In future research, several improvements will be made such as varying the load, applying thickness on the model and also use different theory or method in calculating the stress intensity factor (K).
Applying electric field to charged and polar particles between metallic plates: extension of the Ewald method.

PubMed

Takae, Kyohei; Onuki, Akira

2013-09-28

We develop an efficient Ewald method of molecular dynamics simulation for calculating the electrostatic interactions among charged and polar particles between parallel metallic plates, where we may apply an electric field with an arbitrary size. We use the fact that the potential from the surface charges is equivalent to the sum of those from image charges and dipoles located outside the cell. We present simulation results on boundary effects of charged and polar fluids, formation of ionic crystals, and formation of dipole chains, where the applied field and the image interaction are crucial. For polar fluids, we find a large deviation of the classical Lorentz-field relation between the local field and the applied field due to pair correlations along the applied field. As general aspects, we clarify the difference between the potential-fixed and the charge-fixed boundary conditions and examine the relationship between the discrete particle description and the continuum electrostatics.
The Role of Group Interaction in Collective Efficacy and CSCL Performance

ERIC Educational Resources Information Center

Wang, Shu-Ling; Hsu, Hsien-Yuan; Lin, Sunny S. J.; Hwang, Gwo-Jen

2014-01-01

Although research has identified the importance of interaction behaviors in computer-supported collaborative learning (CSCL), very few attempts have been made to carry out in-depth analysis of interaction behaviors. This study thus applies both qualitative (e.g., content analyses, interviews) and quantitative methods in an attempt to investigate…
Handling qualities of large flexible control-configured aircraft

NASA Technical Reports Server (NTRS)

Swaim, R. L.

1979-01-01

The approach to an analytical study of flexible airplane longitudinal handling qualities was to parametrically vary the natural frequencies of two symmetric elastic modes to induce mode interactions with the rigid body dynamics. Since the structure of the pilot model was unknown for such dynamic interactions, the optimal control pilot modeling method is being applied and used in conjunction with pilot rating method.
Interactively Applying the Variational Method to the Dihydrogen Molecule: Exploring Bonding and Antibonding

ERIC Educational Resources Information Center

Cruzeiro, Vinícius Wilian D.; Roitberg, Adrian; Polfer, Nicolas C.

2016-01-01

In this work we are going to present how an interactive platform can be used as a powerful tool to allow students to better explore a foundational problem in quantum chemistry: the application of the variational method to the dihydrogen molecule using simple Gaussian trial functions. The theoretical approach for the hydrogen atom is quite…
Optimization of o-phtaldialdehyde/2-mercaptoethanol postcolumn reaction for the hydrophilic interaction liquid chromatography determination of memantine utilizing a silica hydride stationary phase.

PubMed

Douša, Michal; Pivoňková, Veronika; Sýkora, David

2016-08-01

A rapid procedure for the determination of memantine based on hydrophilic interaction chromatography with fluorescence detection was developed. Fluorescence detection after postcolumn derivatization with o-phtaldialdehyde/2-mercaptoethanol was performed at excitation and emission wavelengths of 345 and 450 nm, respectively. The postcolumn reaction conditions such as reaction temperature, derivatization reagent flow rate, and reagents concentration were studied due to steric hindrance of amino group of memantine. The derivatization reaction was applied for the hydrophilic interaction liquid chromatography method which was based on Cogent Silica-C stationary phase with a mobile phase consisting of a mixture of 10 mmol/L citric acid and 10 mmol/L o-phosphoric acid (pH 6.0) with acetonitrile using an isocratic composition of 2:8 v/v. The benefit of the reported approach consists in a simple sample pretreatment and a quick and sensitive hydrophilic interaction chromatography method. The developed method was validated in terms of linearity, accuracy, precision, and selectivity according to the International Conference on Harmonisation guidelines. The developed method was successfully applied for the analysis of commercial memantine tablets. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Constructing networks from a dynamical system perspective for multivariate nonlinear time series.

PubMed

Nakamura, Tomomichi; Tanizawa, Toshihiro; Small, Michael

2016-03-01

We describe a method for constructing networks for multivariate nonlinear time series. We approach the interaction between the various scalar time series from a deterministic dynamical system perspective and provide a generic and algorithmic test for whether the interaction between two measured time series is statistically significant. The method can be applied even when the data exhibit no obvious qualitative similarity: a situation in which the naive method utilizing the cross correlation function directly cannot correctly identify connectivity. To establish the connectivity between nodes we apply the previously proposed small-shuffle surrogate (SSS) method, which can investigate whether there are correlation structures in short-term variabilities (irregular fluctuations) between two data sets from the viewpoint of deterministic dynamical systems. The procedure to construct networks based on this idea is composed of three steps: (i) each time series is considered as a basic node of a network, (ii) the SSS method is applied to verify the connectivity between each pair of time series taken from the whole multivariate time series, and (iii) the pair of nodes is connected with an undirected edge when the null hypothesis cannot be rejected. The network constructed by the proposed method indicates the intrinsic (essential) connectivity of the elements included in the system or the underlying (assumed) system. The method is demonstrated for numerical data sets generated by known systems and applied to several experimental time series.
An inviscid-viscous interaction approach to the calculation of dynamic stall initiation on airfoils

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cebeci, T.; Platzer, M.F.; Jang, H.M.

An interactive boundary-layer method is described for computing unsteady incompressible flow over airfoils, including the initiation of dynamic stall. The inviscid unsteady panel method developed by Platzer and Teng is extended to include viscous effects. The solutions of the boundary-layer equations are obtained with an inverse finite-difference method employing an interaction law based on the Hilbert integral, and the algebraic eddy-viscosity formulation of Cebeci and Smith. The method is applied to airfoils subject to periodic and ramp-type motions and its abilities are examined for a range of angles of attack, reduced frequency, and pitch rate.
Microscopic Lagrangian description of warm plasmas. IV - Macroscopic approximation

NASA Technical Reports Server (NTRS)

Kim, H.; Crawford, F. W.

1983-01-01

The averaged-Lagrangian method is applied to linear wave propagation and nonlinear three-wave interaction in a warm magnetoplasma, in the macroscopic approximation. The microscopic Lagrangian treated by Kim and Crawford (1977) and by Galloway and Crawford (1977) is first expanded to third order in perturbation. Velocity integration is then carried out, before applying Hamilton's principle to obtain a general description of wave propagation and coupling. The results are specialized to the case of interaction between two electron plasma waves and an Alfven wave. The method is shown to be more powerful than the alternative possibility of working from the beginning with a macroscopic Lagrangian density.
Applying an analytical method to study neutron behavior for dosimetry

NASA Astrophysics Data System (ADS)

Shirazi, S. A. Mousavi

2016-12-01

In this investigation, a new dosimetry process is studied by applying an analytical method. This novel process is associated with a human liver tissue. The human liver tissue has compositions including water, glycogen and etc. In this study, organic compound materials of liver are decomposed into their constituent elements based upon mass percentage and density of every element. The absorbed doses are computed by analytical method in all constituent elements of liver tissue. This analytical method is introduced applying mathematical equations based on neutron behavior and neutron collision rules. The results show that the absorbed doses are converged for neutron energy below 15MeV. This method can be applied to study the interaction of neutrons in other tissues and estimating the absorbed dose for a wide range of neutron energy.
Co-evolutionary Analysis of Domains in Interacting Proteins Reveals Insights into Domain–Domain Interactions Mediating Protein–Protein Interactions

PubMed Central

Jothi, Raja; Cherukuri, Praveen F.; Tasneem, Asba; Przytycka, Teresa M.

2006-01-01

Recent advances in functional genomics have helped generate large-scale high-throughput protein interaction data. Such networks, though extremely valuable towards molecular level understanding of cells, do not provide any direct information about the regions (domains) in the proteins that mediate the interaction. Here, we performed co-evolutionary analysis of domains in interacting proteins in order to understand the degree of co-evolution of interacting and non-interacting domains. Using a combination of sequence and structural analysis, we analyzed protein–protein interactions in F1-ATPase, Sec23p/Sec24p, DNA-directed RNA polymerase and nuclear pore complexes, and found that interacting domain pair(s) for a given interaction exhibits higher level of co-evolution than the noninteracting domain pairs. Motivated by this finding, we developed a computational method to test the generality of the observed trend, and to predict large-scale domain–domain interactions. Given a protein–protein interaction, the proposed method predicts the domain pair(s) that is most likely to mediate the protein interaction. We applied this method on the yeast interactome to predict domain–domain interactions, and used known domain–domain interactions found in PDB crystal structures to validate our predictions. Our results show that the prediction accuracy of the proposed method is statistically significant. Comparison of our prediction results with those from two other methods reveals that only a fraction of predictions are shared by all the three methods, indicating that the proposed method can detect known interactions missed by other methods. We believe that the proposed method can be used with other methods to help identify previously unrecognized domain–domain interactions on a genome scale, and could potentially help reduce the search space for identifying interaction sites. PMID:16949097
Self-interaction corrections applied to Mg-porphyrin, C60, and pentacene molecules

NASA Astrophysics Data System (ADS)

Pederson, Mark R.; Baruah, Tunna; Kao, Der-you; Basurto, Luis

2016-04-01

We have applied a recently developed method to incorporate the self-interaction correction through Fermi orbitals to Mg-porphyrin, C60, and pentacene molecules. The Fermi-Löwdin orbitals are localized and unitarily invariant to the Kohn-Sham orbitals from which they are constructed. The self-interaction-corrected energy is obtained variationally leading to an optimum set of Fermi-Löwdin orbitals (orthonormalized Fermi orbitals) that gives the minimum energy. A Fermi orbital, by definition, is dependent on a certain point which is referred to as the descriptor position. The degree to which the initial choice of descriptor positions influences the variational approach to the minimum and the complexity of the energy landscape as a function of Fermi-orbital descriptors is examined in detail for Mg-porphyrin. The applications presented here also demonstrate that the method can be applied to larger molecular systems containing a few hundred electrons. The atomization energy of the C60 molecule within the Fermi-Löwdin-orbital self-interaction-correction approach is significantly improved compared to local density approximation in the Perdew-Wang 92 functional and generalized gradient approximation of Perdew-Burke-Ernzerhof functionals. The eigenvalues of the highest occupied molecular orbitals show qualitative improvement.
Parallelized Stochastic Cutoff Method for Long-Range Interacting Systems

NASA Astrophysics Data System (ADS)

Endo, Eishin; Toga, Yuta; Sasaki, Munetaka

2015-07-01

We present a method of parallelizing the stochastic cutoff (SCO) method, which is a Monte-Carlo method for long-range interacting systems. After interactions are eliminated by the SCO method, we subdivide a lattice into noninteracting interpenetrating sublattices. This subdivision enables us to parallelize the Monte-Carlo calculation in the SCO method. Such subdivision is found by numerically solving the vertex coloring of a graph created by the SCO method. We use an algorithm proposed by Kuhn and Wattenhofer to solve the vertex coloring by parallel computation. This method was applied to a two-dimensional magnetic dipolar system on an L × L square lattice to examine its parallelization efficiency. The result showed that, in the case of L = 2304, the speed of computation increased about 102 times by parallel computation with 288 processors.
Non-causal Propagation for Higher-Order Interactions of Torsion with Spinor Fields

NASA Astrophysics Data System (ADS)

Fabbri, Luca

2018-06-01

We consider field equations of spinors with torsional interactions having higher-order dimension: by applying the Velo-Zwanziger method, we obtain that it is always possible to find situations where the propagation is affected by non-causal behavior.
Users' Interaction with World Wide Web Resources: An Exploratory Study Using a Holistic Approach.

ERIC Educational Resources Information Center

Wang, Peiling; Hawk, William B.; Tenopir, Carol

2000-01-01

Presents results of a study that explores factors of user-Web interaction in finding factual information, develops a conceptual framework for studying user-Web interaction, and applies a process-tracing method for conducting holistic user-Web studies. Describes measurement techniques and proposes a model consisting of the user, interface, and the…
Interactive grid adaption

NASA Technical Reports Server (NTRS)

Abolhassani, Jamshid S.; Everton, Eric L.

1990-01-01

An interactive grid adaption method is developed, discussed and applied to the unsteady flow about an oscillating airfoil. The user is allowed to have direct interaction with the adaption of the grid as well as the solution procedure. Grid points are allowed to adapt simultaneously to several variables. In addition to the theory and results, the hardware and software requirements are discussed.
Conversation analysis as a method for investigating interaction in care home environments.

PubMed

Chatwin, John

2014-11-01

This article gives an outline of how the socio-linguistic approach of conversation analysis can be applied to the analysis of carer-patient interaction in care homes. A single case study from a routine encounter in a residential care home is presented. This is used to show how the conversation analysis method works, the kinds of interactional and communication features it can expose, and what specific contribution this kind of micro-interactional approach may make to improving quality of care in these environments. © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.
A discontinuous Galerkin method for nonlinear parabolic equations and gradient flow problems with interaction potentials

NASA Astrophysics Data System (ADS)

Sun, Zheng; Carrillo, José A.; Shu, Chi-Wang

2018-01-01

We consider a class of time-dependent second order partial differential equations governed by a decaying entropy. The solution usually corresponds to a density distribution, hence positivity (non-negativity) is expected. This class of problems covers important cases such as Fokker-Planck type equations and aggregation models, which have been studied intensively in the past decades. In this paper, we design a high order discontinuous Galerkin method for such problems. If the interaction potential is not involved, or the interaction is defined by a smooth kernel, our semi-discrete scheme admits an entropy inequality on the discrete level. Furthermore, by applying the positivity-preserving limiter, our fully discretized scheme produces non-negative solutions for all cases under a time step constraint. Our method also applies to two dimensional problems on Cartesian meshes. Numerical examples are given to confirm the high order accuracy for smooth test cases and to demonstrate the effectiveness for preserving long time asymptotics.
A quasi-static continuum model describing interactions between plasmons and non-absorbing biomolecules

NASA Astrophysics Data System (ADS)

Salary, Mohammad Mahdi; Mosallaei, Hossein

2015-06-01

Interactions between the plasmons of noble metal nanoparticles and non-absorbing biomolecules forms the basis of the plasmonic sensors, which have received much attention. Studying these interactions can help to exploit the full potentials of plasmonic sensors in quantification and analysis of biomolecules. Here, a quasi-static continuum model is adopted for this purpose. We present a boundary-element method for computing the optical response of plasmonic particles to the molecular binding events by solving the Poisson equation. The model represents biomolecules with their molecular surfaces, thus accurately accounting for the influence of exact binding conformations as well as structural differences between different proteins on the response of plasmonic nanoparticles. The linear systems arising in the method are solved iteratively with Krylov generalized minimum residual algorithm, and the acceleration is achieved by applying precorrected-Fast Fourier Transformation technique. We apply the developed method to investigate interactions of biotinylated gold nanoparticles (nanosphere and nanorod) with four different types of biotin-binding proteins. The interactions are studied at both ensemble and single-molecule level. Computational results demonstrate the ability of presented model for analyzing realistic nanoparticle-biomolecule configurations. The method can provide comprehensive study for wide variety of applications, including protein structures, monitoring structural and conformational transitions, and quantification of protein concentrations. In addition, it is suitable for design and optimization of the nano-plasmonic sensors.
PPI-IRO: a two-stage method for protein-protein interaction extraction based on interaction relation ontology.

PubMed

Li, Chuan-Xi; Chen, Peng; Wang, Ru-Jing; Wang, Xiu-Jie; Su, Ya-Ru; Li, Jinyan

2014-01-01

Mining Protein-Protein Interactions (PPIs) from the fast-growing biomedical literature resources has been proven as an effective approach for the identification of biological regulatory networks. This paper presents a novel method based on the idea of Interaction Relation Ontology (IRO), which specifies and organises words of various proteins interaction relationships. Our method is a two-stage PPI extraction method. At first, IRO is applied in a binary classifier to determine whether sentences contain a relation or not. Then, IRO is taken to guide PPI extraction by building sentence dependency parse tree. Comprehensive and quantitative evaluations and detailed analyses are used to demonstrate the significant performance of IRO on relation sentences classification and PPI extraction. Our PPI extraction method yielded a recall of around 80% and 90% and an F1 of around 54% and 66% on corpora of AIMed and BioInfer, respectively, which are superior to most existing extraction methods.
Harmonic force spectroscopy measures load-dependent kinetics of individual human β-cardiac myosin molecules.

PubMed

Sung, Jongmin; Nag, Suman; Mortensen, Kim I; Vestergaard, Christian L; Sutton, Shirley; Ruppel, Kathleen; Flyvbjerg, Henrik; Spudich, James A

2015-08-04

Molecular motors are responsible for numerous cellular processes from cargo transport to heart contraction. Their interactions with other cellular components are often transient and exhibit kinetics that depend on load. Here, we measure such interactions using 'harmonic force spectroscopy'. In this method, harmonic oscillation of the sample stage of a laser trap immediately, automatically and randomly applies sinusoidally varying loads to a single motor molecule interacting with a single track along which it moves. The experimental protocol and the data analysis are simple, fast and efficient. The protocol accumulates statistics fast enough to deliver single-molecule results from single-molecule experiments. We demonstrate the method's performance by measuring the force-dependent kinetics of individual human β-cardiac myosin molecules interacting with an actin filament at physiological ATP concentration. We show that a molecule's ADP release rate depends exponentially on the applied load, in qualitative agreement with cardiac muscle, which contracts with a velocity inversely proportional to external load.
Harmonic force spectroscopy measures load-dependent kinetics of individual human β-cardiac myosin molecules

PubMed Central

Sung, Jongmin; Nag, Suman; Mortensen, Kim I.; Vestergaard, Christian L.; Sutton, Shirley; Ruppel, Kathleen; Flyvbjerg, Henrik; Spudich, James A.

2015-01-01

Molecular motors are responsible for numerous cellular processes from cargo transport to heart contraction. Their interactions with other cellular components are often transient and exhibit kinetics that depend on load. Here, we measure such interactions using ‘harmonic force spectroscopy'. In this method, harmonic oscillation of the sample stage of a laser trap immediately, automatically and randomly applies sinusoidally varying loads to a single motor molecule interacting with a single track along which it moves. The experimental protocol and the data analysis are simple, fast and efficient. The protocol accumulates statistics fast enough to deliver single-molecule results from single-molecule experiments. We demonstrate the method's performance by measuring the force-dependent kinetics of individual human β-cardiac myosin molecules interacting with an actin filament at physiological ATP concentration. We show that a molecule's ADP release rate depends exponentially on the applied load, in qualitative agreement with cardiac muscle, which contracts with a velocity inversely proportional to external load. PMID:26239258
Markov Logic Networks in the Analysis of Genetic Data

PubMed Central

Sakhanenko, Nikita A.

2010-01-01

Abstract Complex, non-additive genetic interactions are common and can be critical in determining phenotypes. Genome-wide association studies (GWAS) and similar statistical studies of linkage data, however, assume additive models of gene interactions in looking for genotype-phenotype associations. These statistical methods view the compound effects of multiple genes on a phenotype as a sum of influences of each gene and often miss a substantial part of the heritable effect. Such methods do not use any biological knowledge about underlying mechanisms. Modeling approaches from the artificial intelligence (AI) field that incorporate deterministic knowledge into models to perform statistical analysis can be applied to include prior knowledge in genetic analysis. We chose to use the most general such approach, Markov Logic Networks (MLNs), for combining deterministic knowledge with statistical analysis. Using simple, logistic regression-type MLNs we can replicate the results of traditional statistical methods, but we also show that we are able to go beyond finding independent markers linked to a phenotype by using joint inference without an independence assumption. The method is applied to genetic data on yeast sporulation, a complex phenotype with gene interactions. In addition to detecting all of the previously identified loci associated with sporulation, our method identifies four loci with smaller effects. Since their effect on sporulation is small, these four loci were not detected with methods that do not account for dependence between markers due to gene interactions. We show how gene interactions can be detected using more complex models, which can be used as a general framework for incorporating systems biology with genetics. PMID:20958249
Detection and characterization of nonspecific, sparsely-populated binding modes in the early stages of complexation

PubMed Central

Cardone, A.; Bornstein, A.; Pant, H. C.; Brady, M.; Sriram, R.; Hassan, S. A.

2015-01-01

A method is proposed to study protein-ligand binding in a system governed by specific and non-specific interactions. Strong associations lead to narrow distributions in the proteins configuration space; weak and ultra-weak associations lead instead to broader distributions, a manifestation of non-specific, sparsely-populated binding modes with multiple interfaces. The method is based on the notion that a discrete set of preferential first-encounter modes are metastable states from which stable (pre-relaxation) complexes at equilibrium evolve. The method can be used to explore alternative pathways of complexation with statistical significance and can be integrated into a general algorithm to study protein interaction networks. The method is applied to a peptide-protein complex. The peptide adopts several low-population conformers and binds in a variety of modes with a broad range of affinities. The system is thus well suited to analyze general features of binding, including conformational selection, multiplicity of binding modes, and nonspecific interactions, and to illustrate how the method can be applied to study these problems systematically. The equilibrium distributions can be used to generate biasing functions for simulations of multiprotein systems from which bulk thermodynamic quantities can be calculated. PMID:25782918
Tiny moments of great importance: the Marte Meo method applied in the context of early mother-infant interaction and postnatal depression. Utilizing Daniel Stern's theory of 'schemas of being with' in understanding empirical findings and developing a stringent Marte Meo methodology.

PubMed

Vik, Kari; Rohde, Rolf

2014-01-01

This paper provides an overview of basic Marte Meo video interaction guidance concepts and describes the therapeutic performance of the method applied in the context of early mother-infant interaction and postnatal depression. Weight is put upon the importance of the therapeutic relationship. Further Marte Meo therapy is understood in the light of Daniel Stern's theory of 'schemas of being with' and accompanied by clinical vignettes from therapy sessions. The empirical basis for the paper is a study of postnatal depression, mother-infant interaction and video guidance, carried out in Southern Norway. The study examined Marte Meo from a phenomenological perspective. Marte Meo was offered to mothers with either postnatal depression or depressive symptoms. In in-depth interviews the participants reported that the Marte Meo method, 'from the outside looking in', increased their reflections about their infants and their own mental states as well as their sensitive interaction with their newborn. Their mothering was improved and they reported feeling less depressed. We argue that Marte Meo methodology can guide new mothers with depressive symptoms, and contribute to the creation of new schemas of being together.
A New Method for Interpreting Nonstationary Running Correlations and Its Application to the ENSO-EAWM Relationship

NASA Astrophysics Data System (ADS)

Geng, Xin; Zhang, Wenjun; Jin, Fei-Fei; Stuecker, Malte F.

2018-01-01

We here propose a new statistical method to interpret nonstationary running correlations by decomposing them into a stationary part and a first-order Taylor expansion approximation for the nonstationary part. Then, this method is applied to investigate the nonstationary behavior of the El Niño-Southern Oscillation (ENSO)-East Asian winter monsoon (EAWM) relationship, which exhibits prominent multidecadal variations. It is demonstrated that the first-order approximation of the nonstationary part can be expressed to a large extent by the impact of the nonlinear interaction between the Atlantic Multidecadal Oscillation (AMO) and ENSO (AMO*Niño3.4) on the EAWM. Therefore, the nonstationarity in the ENSO-EAWM relationship comes predominantly from the impact of an AMO modulation on the ENSO-EAWM teleconnection via this key nonlinear interaction. This general method can be applied to investigate nonstationary relationships that are often observed between various different climate phenomena.

Interactive Social Neuroscience to Study Autism Spectrum Disorder

PubMed Central

Rolison, Max J.; Naples, Adam J.; McPartland, James C.

2015-01-01

Individuals with autism spectrum disorder (ASD) demonstrate difficulty with social interactions and relationships, but the neural mechanisms underlying these difficulties remain largely unknown. While social difficulties in ASD are most apparent in the context of interactions with other people, most neuroscience research investigating ASD have provided limited insight into the complex dynamics of these interactions. The development of novel, innovative “interactive social neuroscience” methods to study the brain in contexts with two interacting humans is a necessary advance for ASD research. Studies applying an interactive neuroscience approach to study two brains engaging with one another have revealed significant differences in neural processes during interaction compared to observation in brain regions that are implicated in the neuropathology of ASD. Interactive social neuroscience methods are crucial in clarifying the mechanisms underlying the social and communication deficits that characterize ASD. PMID:25745371
Interactive social neuroscience to study autism spectrum disorder.

PubMed

Rolison, Max J; Naples, Adam J; McPartland, James C

2015-03-01

Individuals with autism spectrum disorder (ASD) demonstrate difficulty with social interactions and relationships, but the neural mechanisms underlying these difficulties remain largely unknown. While social difficulties in ASD are most apparent in the context of interactions with other people, most neuroscience research investigating ASD have provided limited insight into the complex dynamics of these interactions. The development of novel, innovative "interactive social neuroscience" methods to study the brain in contexts with two interacting humans is a necessary advance for ASD research. Studies applying an interactive neuroscience approach to study two brains engaging with one another have revealed significant differences in neural processes during interaction compared to observation in brain regions that are implicated in the neuropathology of ASD. Interactive social neuroscience methods are crucial in clarifying the mechanisms underlying the social and communication deficits that characterize ASD.
The Value of Learning Talk: Applying a Novel Dialogue Scoring Method to Inform Interaction Design in an Open-Ended, Embodied Museum Exhibit

ERIC Educational Resources Information Center

Roberts, Jessica; Lyons, Leilah

2017-01-01

Museum researchers have long acknowledged the importance of dialogue in informal learning, particularly for open-ended exploratory exhibits. Novel interaction techniques like full-body interaction are appealing for these exploratory exhibits, but designers have not had a metric for determining how their designs are supporting productive learning…
Enhanced identification of synergistic and antagonistic emergent interactions among three or more drugs

PubMed Central

White, Cynthia; Mao, Zhiyuan; Savage, Van M.

2016-01-01

Interactions among drugs play a critical role in the killing efficacy of multi-drug treatments. Recent advances in theory and experiment for three-drug interactions enable the search for emergent interactions—ones not predictable from pairwise interactions. Previous work has shown it is easier to detect synergies and antagonisms among pairwise interactions when a rescaling method is applied to the interaction metric. However, no study has carefully examined whether new types of normalization might be needed for emergence. Here, we propose several rescaling methods for enhancing the classification of the higher order drug interactions based on our conceptual framework. To choose the rescaling that best separates synergism, antagonism and additivity, we conducted bacterial growth experiments in the presence of single, pairwise and triple-drug combinations among 14 antibiotics. We found one of our rescaling methods is far better at distinguishing synergistic and antagonistic emergent interactions than any of the other methods. Using our new method, we find around 50% of emergent interactions are additive, much less than previous reports of greater than 90% additivity. We conclude that higher order emergent interactions are much more common than previously believed, and we argue these findings for drugs suggest that appropriate rescaling is crucial to infer higher order interactions. PMID:27278366
Analysis of random structure-acoustic interaction problems using coupled boundary element and finite element methods

NASA Technical Reports Server (NTRS)

Mei, Chuh; Pates, Carl S., III

1994-01-01

A coupled boundary element (BEM)-finite element (FEM) approach is presented to accurately model structure-acoustic interaction systems. The boundary element method is first applied to interior, two and three-dimensional acoustic domains with complex geometry configurations. Boundary element results are very accurate when compared with limited exact solutions. Structure-interaction problems are then analyzed with the coupled FEM-BEM method, where the finite element method models the structure and the boundary element method models the interior acoustic domain. The coupled analysis is compared with exact and experimental results for a simplistic model. Composite panels are analyzed and compared with isotropic results. The coupled method is then extended for random excitation. Random excitation results are compared with uncoupled results for isotropic and composite panels.
Polymer separations by liquid interaction chromatography: principles - prospects - limitations.

PubMed

Radke, Wolfgang

2014-03-28

Most heterogeneities of polymers with respect to different structural features cannot be resolved by only size exclusion chromatography (SEC), the most frequently applied mode of polymer chromatography. Instead, methods of interaction chromatography became increasingly important. However, despite the increasing applications the principles and potential of polymer interaction chromatography are still often unknown to a large number of polymer scientists. The present review will explain the principles of the different modes of polymer chromatography. Based on selected examples it will be shown which separation techniques can be successfully applied for separations with respect to the different structural features of polymers. Copyright © 2013 Elsevier B.V. All rights reserved.
Dual Logic and Cerebral Coordinates for Reciprocal Interaction in Eye Contact

PubMed Central

Lee, Ray F.

2015-01-01

In order to scientifically study the human brain’s response to face-to-face social interaction, the scientific method itself needs to be reconsidered so that both quantitative observation and symbolic reasoning can be adapted to the situation where the observer is also observed. In light of the recent development of dyadic fMRI which can directly observe dyadic brain interacting in one MRI scanner, this paper aims to establish a new form of logic, dual logic, which provides a theoretical platform for deductive reasoning in a complementary dual system with emergence mechanism. Applying the dual logic in the dfMRI experimental design and data analysis, the exogenous and endogenous dual systems in the BOLD responses can be identified; the non-reciprocal responses in the dual system can be suppressed; a cerebral coordinate for reciprocal interaction can be generated. Elucidated by dual logic deductions, the cerebral coordinate for reciprocal interaction suggests: the exogenous and endogenous systems consist of the empathy network and the mentalization network respectively; the default-mode network emerges from the resting state to activation in the endogenous system during reciprocal interaction; the cingulate plays an essential role in the emergence from the exogenous system to the endogenous system. Overall, the dual logic deductions are supported by the dfMRI experimental results and are consistent with current literature. Both the theoretical framework and experimental method set the stage to formally apply the scientific method in studying complex social interaction. PMID:25885446
A novel non-contact radar sensor for affective and interactive analysis.

PubMed

Lin, Hong-Dun; Lee, Yen-Shien; Shih, Hsiang-Lan; Chuang, Bor-Nian

2013-01-01

Currently, many physiological signal sensing techniques have been applied for affective analysis in Human-Computer Interaction applications. Most known maturely developed sensing methods (EEG/ECG/EMG/Temperature/BP etc. al.) replied on contact way to obtain desired physiological information for further data analysis. However, those methods might cause some inconvenient and uncomfortable problems, and not easy to be used for affective analysis in interactive performing. To improve this issue, a novel technology based on low power radar technology (Nanosecond Pulse Near-field Sensing, NPNS) with 300 MHz radio-frequency was proposed to detect humans' pulse signal by the non-contact way for heartbeat signal extraction. In this paper, a modified nonlinear HRV calculated algorithm was also developed and applied on analyzing affective status using extracted Peak-to-Peak Interval (PPI) information from detected pulse signal. The proposed new affective analysis method is designed to continuously collect the humans' physiological signal, and validated in a preliminary experiment with sound, light and motion interactive performance. As a result, the mean bias between PPI (from NPNS) and RRI (from ECG) shows less than 1ms, and the correlation is over than 0.88, respectively.
Applied Graph-Mining Algorithms to Study Biomolecular Interaction Networks

PubMed Central

2014-01-01

Protein-protein interaction (PPI) networks carry vital information on the organization of molecular interactions in cellular systems. The identification of functionally relevant modules in PPI networks is one of the most important applications of biological network analysis. Computational analysis is becoming an indispensable tool to understand large-scale biomolecular interaction networks. Several types of computational methods have been developed and employed for the analysis of PPI networks. Of these computational methods, graph comparison and module detection are the two most commonly used strategies. This review summarizes current literature on graph kernel and graph alignment methods for graph comparison strategies, as well as module detection approaches including seed-and-extend, hierarchical clustering, optimization-based, probabilistic, and frequent subgraph methods. Herein, we provide a comprehensive review of the major algorithms employed under each theme, including our recently published frequent subgraph method, for detecting functional modules commonly shared across multiple cancer PPI networks. PMID:24800226
Quantitative analysis of protein-ligand interactions by NMR.

PubMed

Furukawa, Ayako; Konuma, Tsuyoshi; Yanaka, Saeko; Sugase, Kenji

2016-08-01

Protein-ligand interactions have been commonly studied through static structures of the protein-ligand complex. Recently, however, there has been increasing interest in investigating the dynamics of protein-ligand interactions both for fundamental understanding of the underlying mechanisms and for drug development. NMR is a versatile and powerful tool, especially because it provides site-specific quantitative information. NMR has widely been used to determine the dissociation constant (KD), in particular, for relatively weak interactions. The simplest NMR method is a chemical-shift titration experiment, in which the chemical-shift changes of a protein in response to ligand titration are measured. There are other quantitative NMR methods, but they mostly apply only to interactions in the fast-exchange regime. These methods derive the dissociation constant from population-averaged NMR quantities of the free and bound states of a protein or ligand. In contrast, the recent advent of new relaxation-based experiments, including R2 relaxation dispersion and ZZ-exchange, has enabled us to obtain kinetic information on protein-ligand interactions in the intermediate- and slow-exchange regimes. Based on R2 dispersion or ZZ-exchange, methods that can determine the association rate, kon, dissociation rate, koff, and KD have been developed. In these approaches, R2 dispersion or ZZ-exchange curves are measured for multiple samples with different protein and/or ligand concentration ratios, and the relaxation data are fitted to theoretical kinetic models. It is critical to choose an appropriate kinetic model, such as the two- or three-state exchange model, to derive the correct kinetic information. The R2 dispersion and ZZ-exchange methods are suitable for the analysis of protein-ligand interactions with a micromolar or sub-micromolar dissociation constant but not for very weak interactions, which are typical in very fast exchange. This contrasts with the NMR methods that are used to analyze population-averaged NMR quantities. Essentially, to apply NMR successfully, both the type of experiment and equation to fit the data must be carefully and specifically chosen for the protein-ligand interaction under analysis. In this review, we first explain the exchange regimes and kinetic models of protein-ligand interactions, and then describe the NMR methods that quantitatively analyze these specific interactions. Copyright © 2016 Elsevier B.V. All rights reserved.
Detection of time delays and directional interactions based on time series from complex dynamical systems

NASA Astrophysics Data System (ADS)

Ma, Huanfei; Leng, Siyang; Tao, Chenyang; Ying, Xiong; Kurths, Jürgen; Lai, Ying-Cheng; Lin, Wei

2017-07-01

Data-based and model-free accurate identification of intrinsic time delays and directional interactions is an extremely challenging problem in complex dynamical systems and their networks reconstruction. A model-free method with new scores is proposed to be generally capable of detecting single, multiple, and distributed time delays. The method is applicable not only to mutually interacting dynamical variables but also to self-interacting variables in a time-delayed feedback loop. Validation of the method is carried out using physical, biological, and ecological models and real data sets. Especially, applying the method to air pollution data and hospital admission records of cardiovascular diseases in Hong Kong reveals the major air pollutants as a cause of the diseases and, more importantly, it uncovers a hidden time delay (about 30-40 days) in the causal influence that previous studies failed to detect. The proposed method is expected to be universally applicable to ascertaining and quantifying subtle interactions (e.g., causation) in complex systems arising from a broad range of disciplines.
Probing fibronectin–antibody interactions using AFM force spectroscopy and lateral force microscopy

PubMed Central

Kulik, Andrzej J; Lee, Kyumin; Pyka-Fościak, Grazyna; Nowak, Wieslaw

2015-01-01

Summary The first experiment showing the effects of specific interaction forces using lateral force microscopy (LFM) was demonstrated for lectin–carbohydrate interactions some years ago. Such measurements are possible under the assumption that specific forces strongly dominate over the non-specific ones. However, obtaining quantitative results requires the complex and tedious calibration of a torsional force. Here, a new and relatively simple method for the calibration of the torsional force is presented. The proposed calibration method is validated through the measurement of the interaction forces between human fibronectin and its monoclonal antibody. The results obtained using LFM and AFM-based classical force spectroscopies showed similar unbinding forces recorded at similar loading rates. Our studies verify that the proposed lateral force calibration method can be applied to study single molecule interactions. PMID:26114080
Accurate prediction of protein–protein interactions from sequence alignments using a Bayesian method

PubMed Central

Burger, Lukas; van Nimwegen, Erik

2008-01-01

Accurate and large-scale prediction of protein–protein interactions directly from amino-acid sequences is one of the great challenges in computational biology. Here we present a new Bayesian network method that predicts interaction partners using only multiple alignments of amino-acid sequences of interacting protein domains, without tunable parameters, and without the need for any training examples. We first apply the method to bacterial two-component systems and comprehensively reconstruct two-component signaling networks across all sequenced bacteria. Comparisons of our predictions with known interactions show that our method infers interaction partners genome-wide with high accuracy. To demonstrate the general applicability of our method we show that it also accurately predicts interaction partners in a recent dataset of polyketide synthases. Analysis of the predicted genome-wide two-component signaling networks shows that cognates (interacting kinase/regulator pairs, which lie adjacent on the genome) and orphans (which lie isolated) form two relatively independent components of the signaling network in each genome. In addition, while most genes are predicted to have only a small number of interaction partners, we find that 10% of orphans form a separate class of ‘hub' nodes that distribute and integrate signals to and from up to tens of different interaction partners. PMID:18277381
Long range Debye-Hückel correction for computation of grid-based electrostatic forces between biomacromolecules

PubMed Central

2014-01-01

Background Brownian dynamics (BD) simulations can be used to study very large molecular systems, such as models of the intracellular environment, using atomic-detail structures. Such simulations require strategies to contain the computational costs, especially for the computation of interaction forces and energies. A common approach is to compute interaction forces between macromolecules by precomputing their interaction potentials on three-dimensional discretized grids. For long-range interactions, such as electrostatics, grid-based methods are subject to finite size errors. We describe here the implementation of a Debye-Hückel correction to the grid-based electrostatic potential used in the SDA BD simulation software that was applied to simulate solutions of bovine serum albumin and of hen egg white lysozyme. Results We found that the inclusion of the long-range electrostatic correction increased the accuracy of both the protein-protein interaction profiles and the protein diffusion coefficients at low ionic strength. Conclusions An advantage of this method is the low additional computational cost required to treat long-range electrostatic interactions in large biomacromolecular systems. Moreover, the implementation described here for BD simulations of protein solutions can also be applied in implicit solvent molecular dynamics simulations that make use of gridded interaction potentials. PMID:25045516
Mitigation of adverse interactions in pairs of clinical practice guidelines using constraint logic programming.

PubMed

Wilk, Szymon; Michalowski, Wojtek; Michalowski, Martin; Farion, Ken; Hing, Marisela Mainegra; Mohapatra, Subhra

2013-04-01

We propose a new method to mitigate (identify and address) adverse interactions (drug-drug or drug-disease) that occur when a patient with comorbid diseases is managed according to two concurrently applied clinical practice guidelines (CPGs). A lack of methods to facilitate the concurrent application of CPGs severely limits their use in clinical practice and the development of such methods is one of the grand challenges for clinical decision support. The proposed method responds to this challenge. We introduce and formally define logical models of CPGs and other related concepts, and develop the mitigation algorithm that operates on these concepts. In the algorithm we combine domain knowledge encoded as interaction and revision operators using the constraint logic programming (CLP) paradigm. The operators characterize adverse interactions and describe revisions to logical models required to address these interactions, while CLP allows us to efficiently solve the logical models - a solution represents a feasible therapy that may be safely applied to a patient. The mitigation algorithm accepts two CPGs and available (likely incomplete) patient information. It reports whether mitigation has been successful or not, and on success it gives a feasible therapy and points at identified interactions (if any) together with the revisions that address them. Thus, we consider the mitigation algorithm as an alerting tool to support a physician in the concurrent application of CPGs that can be implemented as a component of a clinical decision support system. We illustrate our method in the context of two clinical scenarios involving a patient with duodenal ulcer who experiences an episode of transient ischemic attack. Copyright © 2013 Elsevier Inc. All rights reserved.
Magnetic micro/nanoparticle flocculation-based signal amplification for biosensing

PubMed Central

Mzava, Omary; Taş, Zehra; İçöz, Kutay

2016-01-01

We report a time and cost efficient signal amplification method for biosensors employing magnetic particles. In this method, magnetic particles in an applied external magnetic field form magnetic dipoles, interact with each other, and accumulate along the magnetic field lines. This magnetic interaction does not need any biomolecular coating for binding and can be controlled with the strength of the applied magnetic field. The accumulation can be used to amplify the corresponding pixel area that is obtained from an image of a single magnetic particle. An application of the method to the Escherichia coli 0157:H7 bacteria samples is demonstrated in order to show the potential of the approach. A minimum of threefold to a maximum of 60-fold amplification is reached from a single bacteria cell under a magnetic field of 20 mT. PMID:27354793
Mapping protein-RNA interactions by RCAP, RNA-cross-linking and peptide fingerprinting.

PubMed

Vaughan, Robert C; Kao, C Cheng

2015-01-01

RNA nanotechnology often feature protein RNA complexes. The interaction between proteins and large RNAs are difficult to study using traditional structure-based methods like NMR or X-ray crystallography. RCAP, an approach that uses reversible-cross-linking affinity purification method coupled with mass spectrometry, has been developed to map regions within proteins that contact RNA. This chapter details how RCAP is applied to map protein-RNA contacts within virions.
Weld quality inspection using laser-EMAT ultrasonic system and C-scan method

NASA Astrophysics Data System (ADS)

Yang, Lei; Ume, I. Charles

2014-02-01

Laser/EMAT ultrasonic technique has attracted more and more interests in weld quality inspection because of its non-destructive and non-contact characteristics. When ultrasonic techniques are used to detect welds joining relative thin plates, the dominant ultrasonic waves present in the plates are Lamb waves, which propagate all through the thickness. Traditional Time of Flight(ToF) method loses its power. The broadband nature of laser excited ultrasound plus dispersive and multi-modal characteristic of Lamb waves make the EMAT acquired signals very complicated in this situation. Challenge rises in interpreting the received signals and establishing relationship between signal feature and weld quality. In this paper, the laser/EMAT ultrasonic technique was applied in a C-scan manner to record full wave propagation field over an area close to the weld. Then the effect of weld defect on the propagation field of Lamb waves was studied visually by watching an movie resulted from the recorded signals. This method was proved to be effective to detect the presence of hidden defect in the weld. Discrete wavelet transform(DWT) was applied to characterize the acquired ultrasonic signals and ideal band-pass filter was used to isolate wave components most sensitive to the weld defect. Different interactions with the weld defect were observed for different wave components. Thus this C-Scan method, combined with DWT and ideal band-pass filter, proved to be an effective methodology to experimentally study interactions of various laser excited Lamb Wave components with weld defect. In this work, the method was demonstrated by inspecting a hidden local incomplete penetration in weld. In fact, this method can be applied to study Lamb Wave interactions with any type of structural inconsistency. This work also proposed a ideal filtered based method to effectively reduce the total experimental time.
Three-Dimensional Reconstruction of Three-Way FRET Microscopy Improves Imaging of Multiple Protein-Protein Interactions.

PubMed

Scott, Brandon L; Hoppe, Adam D

2016-01-01

Fluorescence resonance energy transfer (FRET) microscopy is a powerful tool for imaging the interactions between fluorescently tagged proteins in two-dimensions. For FRET microscopy to reach its full potential, it must be able to image more than one pair of interacting molecules and image degradation from out-of-focus light must be reduced. Here we extend our previous work on the application of maximum likelihood methods to the 3-dimensional reconstruction of 3-way FRET interactions within cells. We validated the new method (3D-3Way FRET) by simulation and fluorescent protein test constructs expressed in cells. In addition, we improved the computational methods to create a 2-log reduction in computation time over our previous method (3DFSR). We applied 3D-3Way FRET to image the 3D subcellular distributions of HIV Gag assembly. Gag fused to three different FPs (CFP, YFP, and RFP), assembled into viral-like particles and created punctate FRET signals that become visible on the cell surface when 3D-3Way FRET was applied to the data. Control experiments in which YFP-Gag, RFP-Gag and free CFP were expressed, demonstrated localized FRET between YFP and RFP at sites of viral assembly that were not associated with CFP. 3D-3Way FRET provides the first approach for quantifying multiple FRET interactions while improving the 3D resolution of FRET microscopy data without introducing bias into the reconstructed estimates. This method should allow improvement of widefield, confocal and superresolution FRET microscopy data.
Distinguishing time-delayed causal interactions using convergent cross mapping

PubMed Central

Ye, Hao; Deyle, Ethan R.; Gilarranz, Luis J.; Sugihara, George

2015-01-01

An important problem across many scientific fields is the identification of causal effects from observational data alone. Recent methods (convergent cross mapping, CCM) have made substantial progress on this problem by applying the idea of nonlinear attractor reconstruction to time series data. Here, we expand upon the technique of CCM by explicitly considering time lags. Applying this extended method to representative examples (model simulations, a laboratory predator-prey experiment, temperature and greenhouse gas reconstructions from the Vostok ice core, and long-term ecological time series collected in the Southern California Bight), we demonstrate the ability to identify different time-delayed interactions, distinguish between synchrony induced by strong unidirectional-forcing and true bidirectional causality, and resolve transitive causal chains. PMID:26435402

Maximum-Likelihood Methods for Processing Signals From Gamma-Ray Detectors

PubMed Central

Barrett, Harrison H.; Hunter, William C. J.; Miller, Brian William; Moore, Stephen K.; Chen, Yichun; Furenlid, Lars R.

2009-01-01

In any gamma-ray detector, each event produces electrical signals on one or more circuit elements. From these signals, we may wish to determine the presence of an interaction; whether multiple interactions occurred; the spatial coordinates in two or three dimensions of at least the primary interaction; or the total energy deposited in that interaction. We may also want to compute listmode probabilities for tomographic reconstruction. Maximum-likelihood methods provide a rigorous and in some senses optimal approach to extracting this information, and the associated Fisher information matrix provides a way of quantifying and optimizing the information conveyed by the detector. This paper will review the principles of likelihood methods as applied to gamma-ray detectors and illustrate their power with recent results from the Center for Gamma-ray Imaging. PMID:20107527
Simplification of the time-dependent generalized self-interaction correction method using two sets of orbitals: Application of the optimized effective potential formalism

DOE Office of Scientific and Technical Information (OSTI.GOV)

Messud, J.; Dinh, P. M.; Suraud, Eric

2009-10-15

We propose a simplification of the time-dependent self-interaction correction (TD-SIC) method using two sets of orbitals, applying the optimized effective potential (OEP) method. The resulting scheme is called time-dependent 'generalized SIC-OEP'. A straightforward approximation, using the spatial localization of one set of orbitals, leads to the 'generalized SIC-Slater' formalism. We show that it represents a great improvement compared to the traditional SIC-Slater and Krieger-Li-Iafrate formalisms.
Simplification of the time-dependent generalized self-interaction correction method using two sets of orbitals: Application of the optimized effective potential formalism

NASA Astrophysics Data System (ADS)

Messud, J.; Dinh, P. M.; Reinhard, P.-G.; Suraud, Eric

2009-10-01

We propose a simplification of the time-dependent self-interaction correction (TD-SIC) method using two sets of orbitals, applying the optimized effective potential (OEP) method. The resulting scheme is called time-dependent “generalized SIC-OEP.” A straightforward approximation, using the spatial localization of one set of orbitals, leads to the “generalized SIC-Slater” formalism. We show that it represents a great improvement compared to the traditional SIC-Slater and Krieger-Li-Iafrate formalisms.
An immersed-boundary method for flow–structure interaction in biological systems with application to phonation

PubMed Central

Luo, Haoxiang; Mittal, Rajat; Zheng, Xudong; Bielamowicz, Steven A.; Walsh, Raymond J.; Hahn, James K.

2008-01-01

A new numerical approach for modeling a class of flow–structure interaction problems typically encountered in biological systems is presented. In this approach, a previously developed, sharp-interface, immersed-boundary method for incompressible flows is used to model the fluid flow and a new, sharp-interface Cartesian grid, immersed boundary method is devised to solve the equations of linear viscoelasticity that governs the solid. The two solvers are coupled to model flow–structure interaction. This coupled solver has the advantage of simple grid generation and efficient computation on simple, single-block structured grids. The accuracy of the solid-mechanics solver is examined by applying it to a canonical problem. The solution methodology is then applied to the problem of laryngeal aerodynamics and vocal fold vibration during human phonation. This includes a three-dimensional eigen analysis for a multi-layered vocal fold prototype as well as two-dimensional, flow-induced vocal fold vibration in a modeled larynx. Several salient features of the aerodynamics as well as vocal-fold dynamics are presented. PMID:19936017
Flow and Turbulence Modeling and Computation of Shock Buffet Onset for Conventional and Supercritical Airfoils

NASA Technical Reports Server (NTRS)

Bartels, Robert E.

1998-01-01

Flow and turbulence models applied to the problem of shock buffet onset are studied. The accuracy of the interactive boundary layer and the thin-layer Navier-Stokes equations solved with recent upwind techniques using similar transport field equation turbulence models is assessed for standard steady test cases, including conditions having significant shock separation. The two methods are found to compare well in the shock buffet onset region of a supercritical airfoil that involves strong trailing-edge separation. A computational analysis using the interactive-boundary layer has revealed a Reynolds scaling effect in the shock buffet onset of the supercritical airfoil, which compares well with experiment. The methods are next applied to a conventional airfoil. Steady shock-separated computations of the conventional airfoil with the two methods compare well with experiment. Although the interactive boundary layer computations in the shock buffet region compare well with experiment for the conventional airfoil, the thin-layer Navier-Stokes computations do not. These findings are discussed in connection with possible mechanisms important in the onset of shock buffet and the constraints imposed by current numerical modeling techniques.
An Application of Gröbner Basis in Differential Equations of Physics

NASA Astrophysics Data System (ADS)

Chaharbashloo, Mohammad Saleh; Basiri, Abdolali; Rahmany, Sajjad; Zarrinkamar, Saber

2013-11-01

We apply the Gröbner basis to the ansatz method in quantum mechanics to obtain the energy eigenvalues and the wave functions in a very simple manner. There are important physical potentials such as the Cornell interaction which play significant roles in particle physics and can be treated via this technique. As a typical example, the algorithm is applied to the semi-relativistic spinless Salpeter equation under the Cornell interaction. Many other applications of the idea in a wide range of physical fields are listed as well.
Multichannel-Hadamard calibration of high-order adaptive optics systems.

PubMed

Guo, Youming; Rao, Changhui; Bao, Hua; Zhang, Ang; Zhang, Xuejun; Wei, Kai

2014-06-02

we present a novel technique of calibrating the interaction matrix for high-order adaptive optics systems, called the multichannel-Hadamard method. In this method, the deformable mirror actuators are firstly divided into a series of channels according to their coupling relationship, and then the voltage-oriented Hadamard method is applied to these channels. Taking the 595-element adaptive optics system as an example, the procedure is described in detail. The optimal channel dividing is discussed and tested by numerical simulation. The proposed method is also compared with the voltage-oriented Hadamard only method and the multichannel only method by experiments. Results show that the multichannel-Hadamard method can produce significant improvement on interaction matrix measurement.
Estimating Interaction Effects With Incomplete Predictor Variables

PubMed Central

Enders, Craig K.; Baraldi, Amanda N.; Cham, Heining

2014-01-01

The existing missing data literature does not provide a clear prescription for estimating interaction effects with missing data, particularly when the interaction involves a pair of continuous variables. In this article, we describe maximum likelihood and multiple imputation procedures for this common analysis problem. We outline 3 latent variable model specifications for interaction analyses with missing data. These models apply procedures from the latent variable interaction literature to analyses with a single indicator per construct (e.g., a regression analysis with scale scores). We also discuss multiple imputation for interaction effects, emphasizing an approach that applies standard imputation procedures to the product of 2 raw score predictors. We thoroughly describe the process of probing interaction effects with maximum likelihood and multiple imputation. For both missing data handling techniques, we outline centering and transformation strategies that researchers can implement in popular software packages, and we use a series of real data analyses to illustrate these methods. Finally, we use computer simulations to evaluate the performance of the proposed techniques. PMID:24707955
Multimodal Interaction on English Testing Academic Assessment

ERIC Educational Resources Information Center

Magal-Royo, T.; Gimenez-Lopez, J. L.; Garcia Laborda, Jesus

2012-01-01

Multimodal interaction methods applied to learning environments of the English language will be a line for future research from the use of adapted mobile phones or PDAs. Today's mobile devices allow access and data entry in a synchronized manner through different channels. At the academic level we made the first analysis of English language…
Functional modules by relating protein interaction networks and gene expression.

PubMed

Tornow, Sabine; Mewes, H W

2003-11-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.
Functional modules by relating protein interaction networks and gene expression

PubMed Central

Tornow, Sabine; Mewes, H. W.

2003-01-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships. PMID:14576317
Biomarker Identification for Prostate Cancer and Lymph Node Metastasis from Microarray Data and Protein Interaction Network Using Gene Prioritization Method

PubMed Central

Arias, Carlos Roberto; Yeh, Hsiang-Yuan; Soo, Von-Wun

2012-01-01

Finding a genetic disease-related gene is not a trivial task. Therefore, computational methods are needed to present clues to the biomedical community to explore genes that are more likely to be related to a specific disease as biomarker. We present biomarker identification problem using gene prioritization method called gene prioritization from microarray data based on shortest paths, extended with structural and biological properties and edge flux using voting scheme (GP-MIDAS-VXEF). The method is based on finding relevant interactions on protein interaction networks, then scoring the genes using shortest paths and topological analysis, integrating the results using a voting scheme and a biological boosting. We applied two experiments, one is prostate primary and normal samples and the other is prostate primary tumor with and without lymph nodes metastasis. We used 137 truly prostate cancer genes as benchmark. In the first experiment, GP-MIDAS-VXEF outperforms all the other state-of-the-art methods in the benchmark by retrieving the truest related genes from the candidate set in the top 50 scores found. We applied the same technique to infer the significant biomarkers in prostate cancer with lymph nodes metastasis which is not established well. PMID:22654636
Comparison of methods for the analysis of relatively simple mediation models.

PubMed

Rijnhart, Judith J M; Twisk, Jos W R; Chinapaw, Mai J M; de Boer, Michiel R; Heymans, Martijn W

2017-09-01

Statistical mediation analysis is an often used method in trials, to unravel the pathways underlying the effect of an intervention on a particular outcome variable. Throughout the years, several methods have been proposed, such as ordinary least square (OLS) regression, structural equation modeling (SEM), and the potential outcomes framework. Most applied researchers do not know that these methods are mathematically equivalent when applied to mediation models with a continuous mediator and outcome variable. Therefore, the aim of this paper was to demonstrate the similarities between OLS regression, SEM, and the potential outcomes framework in three mediation models: 1) a crude model, 2) a confounder-adjusted model, and 3) a model with an interaction term for exposure-mediator interaction. Secondary data analysis of a randomized controlled trial that included 546 schoolchildren. In our data example, the mediator and outcome variable were both continuous. We compared the estimates of the total, direct and indirect effects, proportion mediated, and 95% confidence intervals (CIs) for the indirect effect across OLS regression, SEM, and the potential outcomes framework. OLS regression, SEM, and the potential outcomes framework yielded the same effect estimates in the crude mediation model, the confounder-adjusted mediation model, and the mediation model with an interaction term for exposure-mediator interaction. Since OLS regression, SEM, and the potential outcomes framework yield the same results in three mediation models with a continuous mediator and outcome variable, researchers can continue using the method that is most convenient to them.
Semantics of User Interface for Image Retrieval: Possibility Theory and Learning Techniques.

ERIC Educational Resources Information Center

Crehange, M.; And Others

1989-01-01

Discusses the need for a rich semantics for the user interface in interactive image retrieval and presents two methods for building such interfaces: possibility theory applied to fuzzy data retrieval, and a machine learning technique applied to learning the user's deep need. Prototypes developed using videodisks and knowledge-based software are…
Directionality of coupling of physiological subsystems: age-related changes of cardiorespiratory interaction during different sleep stages in babies.

PubMed

Mrowka, Ralf; Cimponeriu, Laura; Patzak, Andreas; Rosenblum, Michael G

2003-12-01

Activity of many physiological subsystems has a well-expressed rhythmic character. Often, a dependency between physiological rhythms is established due to interaction between the corresponding subsystems. Traditional methods of data analysis allow one to quantify the strength of interaction but not the causal interrelation that is indispensable for understanding the mechanisms of interaction. Here we present a recently developed method for quantification of coupling direction and apply it to an important problem. Namely, we study the mutual influence of respiratory and cardiovascular rhythms in healthy newborns within the first 6 mo of life in quiet and active sleep. We find an age-related change of the coupling direction: the interaction is nearly symmetric during the first days and becomes practically unidirectional (from respiration to heart rhythm) at the age of 6 mo. Next, we show that the direction of interaction is mainly determined by respiratory frequency. If the latter is less than approximately 0.6 Hz, the interaction occurs dominantly from respiration to heart. With higher respiratory frequencies that only occur at very young ages, the dominating direction is less pronounced or even abolished. The observed dependencies are not related to sleep stage, suggesting that the coupling direction is determined by system-inherent dynamical processes, rather than by functional modulations. The directional analysis may be applied to other interacting narrow band oscillatory systems, e.g., in the central nervous system. Thus it is an important step forward in revealing and understanding causal mechanisms of interactions.
An improved method for pancreas segmentation using SLIC and interactive region merging

NASA Astrophysics Data System (ADS)

Zhang, Liyuan; Yang, Huamin; Shi, Weili; Miao, Yu; Li, Qingliang; He, Fei; He, Wei; Li, Yanfang; Zhang, Huimao; Mori, Kensaku; Jiang, Zhengang

2017-03-01

Considering the weak edges in pancreas segmentation, this paper proposes a new solution which integrates more features of CT images by combining SLIC superpixels and interactive region merging. In the proposed method, Mahalanobis distance is first utilized in SLIC method to generate better superpixel images. By extracting five texture features and one gray feature, the similarity measure between two superpixels becomes more reliable in interactive region merging. Furthermore, object edge blocks are accurately addressed by re-segmentation merging process. Applying the proposed method to four cases of abdominal CT images, we segment pancreatic tissues to verify the feasibility and effectiveness. The experimental results show that the proposed method can make segmentation accuracy increase to 92% on average. This study will boost the application process of pancreas segmentation for computer-aided diagnosis system.
Elliptic Length Scales in Laminar, Two-Dimensional Supersonic Flows

DTIC Science & Technology

2015-06-01

sophisticated computational fluid dynamics ( CFD ) methods. Additionally, for 3D interactions, the length scales would require determination in spanwise as well...Manna, M. “Experimental, Analytical, and Computational Methods Applied to Hypersonic Compression Ramp Flows,” AIAA Journal, Vol. 32, No. 2, Feb. 1994
Filtering Gene Ontology semantic similarity for identifying protein complexes in large protein interaction networks.

PubMed

Wang, Jian; Xie, Dong; Lin, Hongfei; Yang, Zhihao; Zhang, Yijia

2012-06-21

Many biological processes recognize in particular the importance of protein complexes, and various computational approaches have been developed to identify complexes from protein-protein interaction (PPI) networks. However, high false-positive rate of PPIs leads to challenging identification. A protein semantic similarity measure is proposed in this study, based on the ontology structure of Gene Ontology (GO) terms and GO annotations to estimate the reliability of interactions in PPI networks. Interaction pairs with low GO semantic similarity are removed from the network as unreliable interactions. Then, a cluster-expanding algorithm is used to detect complexes with core-attachment structure on filtered network. Our method is applied to three different yeast PPI networks. The effectiveness of our method is examined on two benchmark complex datasets. Experimental results show that our method performed better than other state-of-the-art approaches in most evaluation metrics. The method detects protein complexes from large scale PPI networks by filtering GO semantic similarity. Removing interactions with low GO similarity significantly improves the performance of complex identification. The expanding strategy is also effective to identify attachment proteins of complexes.
GEOPHYSICS, ASTRONOMY AND ASTROPHYSICS: Numerical method of studying nonlinear interactions between long waves and multiple short waves

NASA Astrophysics Data System (ADS)

Xie, Tao; Kuang, Hai-Lan; William, Perrie; Zou, Guang-Hui; Nan, Cheng-Feng; He, Chao; Shen, Tao; Chen, Wei

2009-07-01

Although the nonlinear interactions between a single short gravity wave and a long wave can be solved analytically, the solution is less tractable in more general cases involving multiple short waves. In this work we present a numerical method of studying nonlinear interactions between a long wave and multiple short harmonic waves in infinitely deep water. Specifically, this method is applied to the calculation of the temporal and spatial evolutions of the surface elevations in which a given long wave interacts with several short harmonic waves. Another important application of our method is to quantitatively analyse the nonlinear interactions between an arbitrary short wave train and another short wave train. From simulation results, we obtain that the mechanism for the nonlinear interactions between one short wave train and another short wave train (expressed as wave train 2) leads to the energy focusing of the other short wave train (expressed as wave train 3). This mechanism occurs on wave components with a narrow frequency bandwidth, whose frequencies are near that of wave train 3.
Screening of the binding of small molecules to proteins by desorption electrospray ionization mass spectrometry combined with protein microarray.

PubMed

Yao, Chenxi; Wang, Tao; Zhang, Buqing; He, Dacheng; Na, Na; Ouyang, Jin

2015-11-01

The interaction between bioactive small molecule ligands and proteins is one of the important research areas in proteomics. Herein, a simple and rapid method is established to screen small ligands that bind to proteins. We designed an agarose slide to immobilize different proteins. The protein microarrays were allowed to interact with different small ligands, and after washing, the microarrays were screened by desorption electrospray ionization mass spectrometry (DESI MS). This method can be applied to screen specific protein binding ligands and was shown for seven proteins and 34 known ligands for these proteins. In addition, a high-throughput screening was achieved, with the analysis requiring approximately 4 s for one sample spot. We then applied this method to determine the binding between the important protein matrix metalloproteinase-9 (MMP-9) and 88 small compounds. The molecular docking results confirmed the MS results, demonstrating that this method is suitable for the rapid and accurate screening of ligands binding to proteins. Graphical Abstract ᅟ.

A comparative study of multivariable robustness analysis methods as applied to integrated flight and propulsion control

NASA Technical Reports Server (NTRS)

Schierman, John D.; Lovell, T. A.; Schmidt, David K.

1993-01-01

Three multivariable robustness analysis methods are compared and contrasted. The focus of the analysis is on system stability and performance robustness to uncertainty in the coupling dynamics between two interacting subsystems. Of particular interest is interacting airframe and engine subsystems, and an example airframe/engine vehicle configuration is utilized in the demonstration of these approaches. The singular value (SV) and structured singular value (SSV) analysis methods are compared to a method especially well suited for analysis of robustness to uncertainties in subsystem interactions. This approach is referred to here as the interacting subsystem (IS) analysis method. This method has been used previously to analyze airframe/engine systems, emphasizing the study of stability robustness. However, performance robustness is also investigated here, and a new measure of allowable uncertainty for acceptable performance robustness is introduced. The IS methodology does not require plant uncertainty models to measure the robustness of the system, and is shown to yield valuable information regarding the effects of subsystem interactions. In contrast, the SV and SSV methods allow for the evaluation of the robustness of the system to particular models of uncertainty, and do not directly indicate how the airframe (engine) subsystem interacts with the engine (airframe) subsystem.
Detection of Protein Complexes Based on Penalized Matrix Decomposition in a Sparse Protein⁻Protein Interaction Network.

PubMed

Cao, Buwen; Deng, Shuguang; Qin, Hua; Ding, Pingjian; Chen, Shaopeng; Li, Guanghui

2018-06-15

High-throughput technology has generated large-scale protein interaction data, which is crucial in our understanding of biological organisms. Many complex identification algorithms have been developed to determine protein complexes. However, these methods are only suitable for dense protein interaction networks, because their capabilities decrease rapidly when applied to sparse protein⁻protein interaction (PPI) networks. In this study, based on penalized matrix decomposition ( PMD ), a novel method of penalized matrix decomposition for the identification of protein complexes (i.e., PMD pc ) was developed to detect protein complexes in the human protein interaction network. This method mainly consists of three steps. First, the adjacent matrix of the protein interaction network is normalized. Second, the normalized matrix is decomposed into three factor matrices. The PMD pc method can detect protein complexes in sparse PPI networks by imposing appropriate constraints on factor matrices. Finally, the results of our method are compared with those of other methods in human PPI network. Experimental results show that our method can not only outperform classical algorithms, such as CFinder, ClusterONE, RRW, HC-PIN, and PCE-FR, but can also achieve an ideal overall performance in terms of a composite score consisting of F-measure, accuracy (ACC), and the maximum matching ratio (MMR).
Exact kinetic energy enables accurate evaluation of weak interactions by the FDE-vdW method.

PubMed

Sinha, Debalina; Pavanello, Michele

2015-08-28

The correlation energy of interaction is an elusive and sought-after interaction between molecular systems. By partitioning the response function of the system into subsystem contributions, the Frozen Density Embedding (FDE)-vdW method provides a computationally amenable nonlocal correlation functional based on the adiabatic connection fluctuation dissipation theorem applied to subsystem density functional theory. In reproducing potential energy surfaces of weakly interacting dimers, we show that FDE-vdW, either employing semilocal or exact nonadditive kinetic energy functionals, is in quantitative agreement with high-accuracy coupled cluster calculations (overall mean unsigned error of 0.5 kcal/mol). When employing the exact kinetic energy (which we term the Kohn-Sham (KS)-vdW method), the binding energies are generally closer to the benchmark, and the energy surfaces are also smoother.
Exact kinetic energy enables accurate evaluation of weak interactions by the FDE-vdW method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sinha, Debalina; Pavanello, Michele, E-mail: m.pavanello@rutgers.edu

2015-08-28

The correlation energy of interaction is an elusive and sought-after interaction between molecular systems. By partitioning the response function of the system into subsystem contributions, the Frozen Density Embedding (FDE)-vdW method provides a computationally amenable nonlocal correlation functional based on the adiabatic connection fluctuation dissipation theorem applied to subsystem density functional theory. In reproducing potential energy surfaces of weakly interacting dimers, we show that FDE-vdW, either employing semilocal or exact nonadditive kinetic energy functionals, is in quantitative agreement with high-accuracy coupled cluster calculations (overall mean unsigned error of 0.5 kcal/mol). When employing the exact kinetic energy (which we term themore » Kohn-Sham (KS)-vdW method), the binding energies are generally closer to the benchmark, and the energy surfaces are also smoother.« less
Receptor-based 3D QSAR analysis of estrogen receptor ligands - merging the accuracy of receptor-based alignments with the computational efficiency of ligand-based methods

NASA Astrophysics Data System (ADS)

Sippl, Wolfgang

2000-08-01

One of the major challenges in computational approaches to drug design is the accurate prediction of binding affinity of biomolecules. In the present study several prediction methods for a published set of estrogen receptor ligands are investigated and compared. The binding modes of 30 ligands were determined using the docking program AutoDock and were compared with available X-ray structures of estrogen receptor-ligand complexes. On the basis of the docking results an interaction energy-based model, which uses the information of the whole ligand-receptor complex, was generated. Several parameters were modified in order to analyze their influence onto the correlation between binding affinities and calculated ligand-receptor interaction energies. The highest correlation coefficient ( r 2 = 0.617, q 2 LOO = 0.570) was obtained considering protein flexibility during the interaction energy evaluation. The second prediction method uses a combination of receptor-based and 3D quantitative structure-activity relationships (3D QSAR) methods. The ligand alignment obtained from the docking simulations was taken as basis for a comparative field analysis applying the GRID/GOLPE program. Using the interaction field derived with a water probe and applying the smart region definition (SRD) variable selection, a significant and robust model was obtained ( r 2 = 0.991, q 2 LOO = 0.921). The predictive ability of the established model was further evaluated by using a test set of six additional compounds. The comparison with the generated interaction energy-based model and with a traditional CoMFA model obtained using a ligand-based alignment ( r 2 = 0.951, q 2 LOO = 0.796) indicates that the combination of receptor-based and 3D QSAR methods is able to improve the quality of the underlying model.
Modeling Latent Interactions at Level 2 in Multilevel Structural Equation Models: An Evaluation of Mean-Centered and Residual-Centered Unconstrained Approaches

ERIC Educational Resources Information Center

Leite, Walter L.; Zuo, Youzhen

2011-01-01

Among the many methods currently available for estimating latent variable interactions, the unconstrained approach is attractive to applied researchers because of its relatively easy implementation with any structural equation modeling (SEM) software. Using a Monte Carlo simulation study, we extended and evaluated the unconstrained approach to…
Quantification of arrestin-rhodopsin binding stoichiometry.

PubMed

Lally, Ciara C M; Sommer, Martha E

2015-01-01

We have developed several methods to quantify arrestin-1 binding to rhodopsin in the native rod disk membrane. These methods can be applied to study arrestin interactions with all functional forms of rhodopsin, including dark-state rhodopsin, light-activated metarhodopsin II (Meta II), and the products of Meta II decay, opsin and all-trans-retinal. When used in parallel, these methods report both the actual amount of arrestin bound to the membrane surface and the functional aspects of arrestin binding, such as which arrestin loops are engaged and whether Meta II is stabilized. Most of these methods can also be applied to recombinant receptor reconstituted into liposomes, bicelles, and nanodisks.
Determination of structure and properties of molecular crystals from first principles.

PubMed

Szalewicz, Krzysztof

2014-11-18

CONSPECTUS: Until recently, it had been impossible to predict structures of molecular crystals just from the knowledge of the chemical formula for the constituent molecule(s). A solution of this problem has been achieved using intermolecular force fields computed from first principles. These fields were developed by calculating interaction energies of molecular dimers and trimers using an ab initio method called symmetry-adapted perturbation theory (SAPT) based on density-functional theory (DFT) description of monomers [SAPT(DFT)]. For clusters containing up to a dozen or so atoms, interaction energies computed using SAPT(DFT) are comparable in accuracy to the results of the best wave function-based methods, whereas the former approach can be applied to systems an order of magnitude larger than the latter. In fact, for monomers with a couple dozen atoms, SAPT(DFT) is about equally time-consuming as the supermolecular DFT approach. To develop a force field, SAPT(DFT) calculations are performed for a large number of dimer and possibly also trimer configurations (grid points in intermolecular coordinates), and the interaction energies are then fitted by analytic functions. The resulting force fields can be used to determine crystal structures and properties by applying them in molecular packing, lattice energy minimization, and molecular dynamics calculations. In this way, some of the first successful determinations of crystal structures were achieved from first principles, with crystal densities and lattice parameters agreeing with experimental values to within about 1%. Crystal properties obtained using similar procedures but empirical force fields fitted to crystal data have typical errors of several percent due to low sensitivity of empirical fits to interactions beyond those of the nearest neighbors. The first-principles approach has additional advantages over the empirical approach for notional crystals and cocrystals since empirical force fields can only be extrapolated to such cases. As an alternative to applying SAPT(DFT) in crystal structure calculations, one can use supermolecular DFT interaction energies combined with scaled dispersion energies computed from simple atom-atom functions, that is, use the so-called DFT+D approach. Whereas the standard DFT methods fail for intermolecular interactions, DFT+D performs reasonably well since the dispersion correction is used not only to provide the missing dispersion contribution but also to fix other deficiencies of DFT. The latter cancellation of errors is unphysical and can be avoided by applying the so-called dispersionless density functional, dlDF. In this case, the dispersion energies are added without any scaling. The dlDF+D method is also one of the best performing DFT+D methods. The SAPT(DFT)-based approach has been applied so far only to crystals with rigid monomers. It can be extended to partly flexible monomers, that is, to monomers with only a few internal coordinates allowed to vary. However, the costs will increase relative to rigid monomer cases since the number of grid points increases exponentially with the number of dimensions. One way around this problem is to construct force fields with approximate couplings between inter- and intramonomer degrees of freedom. Another way is to calculate interaction energies (and possibly forces) "on the fly", i.e., in each step of lattice energy minimization procedure. Such an approach would be prohibitively expensive if it replaced analytic force fields at all stages of the crystal predictions procedure, but it can be used to optimize a few dozen candidate structures determined by other methods.
Predicting Physical Interactions between Protein Complexes*

PubMed Central

Clancy, Trevor; Rødland, Einar Andreas; Nygard, Ståle; Hovig, Eivind

2013-01-01

Protein complexes enact most biochemical functions in the cell. Dynamic interactions between protein complexes are frequent in many cellular processes. As they are often of a transient nature, they may be difficult to detect using current genome-wide screens. Here, we describe a method to computationally predict physical interactions between protein complexes, applied to both humans and yeast. We integrated manually curated protein complexes and physical protein interaction networks, and we designed a statistical method to identify pairs of protein complexes where the number of protein interactions between a complex pair is due to an actual physical interaction between the complexes. An evaluation against manually curated physical complex-complex interactions in yeast revealed that 50% of these interactions could be predicted in this manner. A community network analysis of the highest scoring pairs revealed a biologically sensible organization of physical complex-complex interactions in the cell. Such analyses of proteomes may serve as a guide to the discovery of novel functional cellular relationships. PMID:23438732
Interactive forms of conducting business and role games in dialogical training

NASA Astrophysics Data System (ADS)

Medvedeva, L.; Yushkov, E.; Yakovlev, D.; Bogatyreova, M.

2017-01-01

Mastering interactive technologies by teachers of higher educational institutions is the basis of enhancing the quality of education. The competent use of interactive forms of business and role-play games at seminars strengthens a pedagogical effect on the development of the culture of thinking, professional and personal qualities of students, as well as provides an in-depth study of the subject and acquisition of scientific cognition methods. Dialogical thinking creates a truly open mind for sharing opinions and freely discussing suggestions made by the participants, especially in situations of seeking effective task-solving methods. In order to train competitive graduates, ready to act efficiently in their future career, it is necessary to apply innovational interactive technologies in the educational process.
Thermal transport through a spin-phonon interacting junction: A nonequilibrium Green's function method study

NASA Astrophysics Data System (ADS)

Zhang, Zu-Quan; Lü, Jing-Tao

2017-09-01

Using the nonequilibrium Green's function method, we consider heat transport in an insulating ferromagnetic spin chain model with spin-phonon interaction under an external magnetic field. Employing the Holstein-Primakoff transformation to the spin system, we treat the resulted magnon-phonon interaction within the self-consistent Born approximation. We find the magnon-phonon coupling can change qualitatively the magnon thermal conductance in the high-temperature regime. At a spectral mismatched ferromagnetic-normal insulator interface, we also find thermal rectification and negative differential thermal conductance due to the magnon-phonon interaction. We show that these effects can be effectively tuned by the external applied magnetic field, a convenient advantage absent in anharmonic phonon and electron-phonon systems studied before.
Construction of ontology augmented networks for protein complex prediction.

PubMed

Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian

2013-01-01

Protein complexes are of great importance in understanding the principles of cellular organization and function. The increase in available protein-protein interaction data, gene ontology and other resources make it possible to develop computational methods for protein complex prediction. Most existing methods focus mainly on the topological structure of protein-protein interaction networks, and largely ignore the gene ontology annotation information. In this article, we constructed ontology augmented networks with protein-protein interaction data and gene ontology, which effectively unified the topological structure of protein-protein interaction networks and the similarity of gene ontology annotations into unified distance measures. After constructing ontology augmented networks, a novel method (clustering based on ontology augmented networks) was proposed to predict protein complexes, which was capable of taking into account the topological structure of the protein-protein interaction network, as well as the similarity of gene ontology annotations. Our method was applied to two different yeast protein-protein interaction datasets and predicted many well-known complexes. The experimental results showed that (i) ontology augmented networks and the unified distance measure can effectively combine the structure closeness and gene ontology annotation similarity; (ii) our method is valuable in predicting protein complexes and has higher F1 and accuracy compared to other competing methods.
Analysis of the STAT3 interactome using in-situ biotinylation and SILAC.

PubMed

Blumert, Conny; Kalkhof, Stefan; Brocke-Heidrich, Katja; Kohajda, Tibor; von Bergen, Martin; Horn, Friedemann

2013-12-06

Signal transducer and activator of transcription 3 (STAT3) is activated by a variety of cytokines and growth factors. To generate a comprehensive data set of proteins interacting specifically with STAT3, we applied stable isotope labeling with amino acids in cell culture (SILAC). For high-affinity pull-down using streptavidin, we fused STAT3 with a short peptide tag allowing biotinylation in situ (bio-tag), which did not affect STAT3 functions. By this approach, 3642 coprecipitated proteins were detected in human embryonic kidney-293 cells. Filtering using statistical and functional criteria finally extracted 136 proteins as putative interaction partners of STAT3. Both, a physical interaction network analysis and the enrichment of known and predicted interaction partners suggested that our filtering criteria successfully enriched true STAT3 interactors. Our approach identified numerous novel interactors, including ones previously predicted to associate with STAT3. By reciprocal coprecipitation, we were able to verify the physical association between STAT3 and selected interactors, including the novel interaction with TOX4, a member of the TOX high mobility group box family. Applying the same method, we next investigated the activation-dependency of the STAT3 interactome. Again, we identified both known and novel interactions. Thus, our approach allows to study protein-protein interaction effectively and comprehensively. The location, activity, function, degradation, and synthesis of proteins are significantly regulated by interactions of proteins with other proteins, biopolymers and small molecules. Thus, the comprehensive characterization of interactions of proteins in a given proteome is the next milestone on the path to understanding the biochemistry of the cell. In order to generate a comprehensive interactome dataset of proteins specifically interacting with a selected bait protein, we fused our bait protein STAT3 with a short peptide tag allowing biotinylation in situ (bio-tag). This bio-tag allows an affinity pull-down using streptavidin but affected neither the activation of STAT3 by tyrosine phosphorylation nor its transactivating potential. We combined SILAC for accurate relative protein quantification, subcellular fractionation to increase the coverage of interacting proteins, high-affinity pull-down and a stringent filtering method to successfully analyze the interactome of STAT3. With our approach we confirmed several already known and identified numerous novel STAT3 interactors. The approach applied provides a rapid and effective method, which is broadly applicable for studying protein-protein interactions and their dependency on post-translational modifications. © 2013. Published by Elsevier B.V. All rights reserved.
A Novel Calibration-Minimum Method for Prediction of Mole Fraction in Non-Ideal Mixture.

PubMed

Shibayama, Shojiro; Kaneko, Hiromasa; Funatsu, Kimito

2017-04-01

This article proposes a novel concentration prediction model that requires little training data and is useful for rapid process understanding. Process analytical technology is currently popular, especially in the pharmaceutical industry, for enhancement of process understanding and process control. A calibration-free method, iterative optimization technology (IOT), was proposed to predict pure component concentrations, because calibration methods such as partial least squares, require a large number of training samples, leading to high costs. However, IOT cannot be applied to concentration prediction in non-ideal mixtures because its basic equation is derived from the Beer-Lambert law, which cannot be applied to non-ideal mixtures. We proposed a novel method that realizes prediction of pure component concentrations in mixtures from a small number of training samples, assuming that spectral changes arising from molecular interactions can be expressed as a function of concentration. The proposed method is named IOT with virtual molecular interaction spectra (IOT-VIS) because the method takes spectral change as a virtual spectrum x nonlin,i into account. It was confirmed through the two case studies that the predictive accuracy of IOT-VIS was the highest among existing IOT methods.
Evolutionary model selection and parameter estimation for protein-protein interaction network based on differential evolution algorithm

PubMed Central

Huang, Lei; Liao, Li; Wu, Cathy H.

2016-01-01

Revealing the underlying evolutionary mechanism plays an important role in understanding protein interaction networks in the cell. While many evolutionary models have been proposed, the problem about applying these models to real network data, especially for differentiating which model can better describe evolutionary process for the observed network urgently remains as a challenge. The traditional way is to use a model with presumed parameters to generate a network, and then evaluate the fitness by summary statistics, which however cannot capture the complete network structures information and estimate parameter distribution. In this work we developed a novel method based on Approximate Bayesian Computation and modified Differential Evolution (ABC-DEP) that is capable of conducting model selection and parameter estimation simultaneously and detecting the underlying evolutionary mechanisms more accurately. We tested our method for its power in differentiating models and estimating parameters on the simulated data and found significant improvement in performance benchmark, as compared with a previous method. We further applied our method to real data of protein interaction networks in human and yeast. Our results show Duplication Attachment model as the predominant evolutionary mechanism for human PPI networks and Scale-Free model as the predominant mechanism for yeast PPI networks. PMID:26357273
An Interactive Image Segmentation Method in Hand Gesture Recognition

PubMed Central

Chen, Disi; Li, Gongfa; Sun, Ying; Kong, Jianyi; Jiang, Guozhang; Tang, Heng; Ju, Zhaojie; Yu, Hui; Liu, Honghai

2017-01-01

In order to improve the recognition rate of hand gestures a new interactive image segmentation method for hand gesture recognition is presented, and popular methods, e.g., Graph cut, Random walker, Interactive image segmentation using geodesic star convexity, are studied in this article. The Gaussian Mixture Model was employed for image modelling and the iteration of Expectation Maximum algorithm learns the parameters of Gaussian Mixture Model. We apply a Gibbs random field to the image segmentation and minimize the Gibbs Energy using Min-cut theorem to find the optimal segmentation. The segmentation result of our method is tested on an image dataset and compared with other methods by estimating the region accuracy and boundary accuracy. Finally five kinds of hand gestures in different backgrounds are tested on our experimental platform, and the sparse representation algorithm is used, proving that the segmentation of hand gesture images helps to improve the recognition accuracy. PMID:28134818
Analysis of iced wings

NASA Technical Reports Server (NTRS)

Cebeci, T.; Chen, H. H.; Kaups, K.; Schimke, S.; Shin, J.

1992-01-01

A method for computing ice shapes along the leading edge of a wing and a method for predicting its aerodynamic performance degradation due to icing is described. Ice shapes are computed using an extension of the LEWICE code which was developed for airfoils. The aerodynamic properties of the iced wing are determined with an interactive scheme in which the solutions of the inviscid flow equations are obtained from a panel method and the solutions of the viscous flow equations are obtained from an inverse three-dimensional finite-difference boundary-layer method. A new interaction law is used to couple the inviscid and viscous flow solutions. The application of the LEWICE wing code to the calculation of ice shapes on a MS-317 swept wing shows good agreement with measurements. The interactive boundary-layer method is applied to a tapered ice wing in order to study the effect of icing on the aerodynamic properties of the wing at several angles of attack.
Lagrangian methods in the analysis of nonlinear wave interactions in plasma

NASA Technical Reports Server (NTRS)

Galloway, J. J.

1972-01-01

An averaged-Lagrangian method is developed for obtaining the equations which describe the nonlinear interactions of the wave (oscillatory) and background (nonoscillatory) components which comprise a continuous medium. The method applies to monochromatic waves in any continuous medium that can be described by a Lagrangian density, but is demonstrated in the context of plasma physics. The theory is presented in a more general and unified form by way of a new averaged-Lagrangian formalism which simplifies the perturbation ordering procedure. Earlier theory is extended to deal with a medium distributed in velocity space and to account for the interaction of the background with the waves. The analytic steps are systematized, so as to maximize calculational efficiency. An assessment of the applicability and limitations of the method shows that it has some definite advantages over other approaches in efficiency and versatility.
Multivariate generalized multifactor dimensionality reduction to detect gene-gene interactions

PubMed Central

2013-01-01

Background Recently, one of the greatest challenges in genome-wide association studies is to detect gene-gene and/or gene-environment interactions for common complex human diseases. Ritchie et al. (2001) proposed multifactor dimensionality reduction (MDR) method for interaction analysis. MDR is a combinatorial approach to reduce multi-locus genotypes into high-risk and low-risk groups. Although MDR has been widely used for case-control studies with binary phenotypes, several extensions have been proposed. One of these methods, a generalized MDR (GMDR) proposed by Lou et al. (2007), allows adjusting for covariates and applying to both dichotomous and continuous phenotypes. GMDR uses the residual score of a generalized linear model of phenotypes to assign either high-risk or low-risk group, while MDR uses the ratio of cases to controls. Methods In this study, we propose multivariate GMDR, an extension of GMDR for multivariate phenotypes. Jointly analysing correlated multivariate phenotypes may have more power to detect susceptible genes and gene-gene interactions. We construct generalized estimating equations (GEE) with multivariate phenotypes to extend generalized linear models. Using the score vectors from GEE we discriminate high-risk from low-risk groups. We applied the multivariate GMDR method to the blood pressure data of the 7,546 subjects from the Korean Association Resource study: systolic blood pressure (SBP) and diastolic blood pressure (DBP). We compare the results of multivariate GMDR for SBP and DBP to the results from separate univariate GMDR for SBP and DBP, respectively. We also applied the multivariate GMDR method to the repeatedly measured hypertension status from 5,466 subjects and compared its result with those of univariate GMDR at each time point. Results Results from the univariate GMDR and multivariate GMDR in two-locus model with both blood pressures and hypertension phenotypes indicate best combinations of SNPs whose interaction has significant association with risk for high blood pressures or hypertension. Although the test balanced accuracy (BA) of multivariate analysis was not always greater than that of univariate analysis, the multivariate BAs were more stable with smaller standard deviations. Conclusions In this study, we have developed multivariate GMDR method using GEE approach. It is useful to use multivariate GMDR with correlated multiple phenotypes of interests. PMID:24565370
A new method for finding the minimum free energy pathway of ions and small molecule transportation through protein based on 3D-RISM theory and the string method

NASA Astrophysics Data System (ADS)

Yoshida, Norio

2018-05-01

A new method for finding the minimum free energy pathway (MFEP) of ions and small molecule transportation through a protein based on the three-dimensional reference interaction site model (3D-RISM) theory combined with the string method has been proposed. The 3D-RISM theory produces the distribution function, or the potential of mean force (PMF), for transporting substances around the given protein structures. By applying the string method to the PMF surface, one can readily determine the MFEP on the PMF surface. The method has been applied to consider the Na+ conduction pathway of channelrhodopsin as an example.

SPH Numerical Modeling for the Wave-Thin Structure Interaction

NASA Astrophysics Data System (ADS)

Ren, Xi-feng; Sun, Zhao-chen; Wang, Xing-gang; Liang, Shu-xiu

2018-04-01

In this paper, a numerical model of 2D weakly compressible smoothed particle hydrodynamics (WCSPH) is developed to simulate the interaction between waves and thin structures. A new color domain particle (CDP) technique is proposed to overcome difficulties of applying the ghost particle method to thin structures in dealing with solid boundaries. The new technique can deal with zero-thickness structures. To apply this enforcing technique, the computational fluid domain is divided into sub domains, i.e., boundary domains and internal domains. A color value is assigned to each particle, and contains the information of the domains in which the particle belongs to and the particles can interact with. A particle, nearby a thin boundary, is prevented from interacting with particles, which should not interact with on the other side of the structure. It is possible to model thin structures, or the structures with the thickness negligible with this technique. The proposed WCSPH module is validated for a still water tank, divided by a thin plate at the middle section, with different water levels in the subdomains, and is applied to simulate the interaction between regular waves and a perforated vertical plate. Finally, the computation is carried out for waves and submerged twin-horizontal plate interaction. It is shown that the numerical results agree well with experimental data in terms of the pressure distribution, pressure time series and wave transmission.
Mass Spectrometry Analysis of Spatial Protein Networks by Colocalization Analysis (COLA).

PubMed

Mardakheh, Faraz K

2017-01-01

A major challenge in systems biology is comprehensive mapping of protein interaction networks. Crucially, such interactions are often dynamic in nature, necessitating methods that can rapidly mine the interactome across varied conditions and treatments to reveal change in the interaction networks. Recently, we described a fast mass spectrometry-based method to reveal functional interactions in mammalian cells on a global scale, by revealing spatial colocalizations between proteins (COLA) (Mardakheh et al., Mol Biosyst 13:92-105, 2017). As protein localization and function are inherently linked, significant colocalization between two proteins is a strong indication for their functional interaction. COLA uses rapid complete subcellular fractionation, coupled with quantitative proteomics to generate a subcellular localization profile for each protein quantified by the mass spectrometer. Robust clustering is then applied to reveal significant similarities in protein localization profiles, indicative of colocalization.
FAST TRACK COMMUNICATION Solving the ultradiscrete KdV equation

NASA Astrophysics Data System (ADS)

Willox, Ralph; Nakata, Yoichi; Satsuma, Junkichi; Ramani, Alfred; Grammaticos, Basile

2010-12-01

We show that a generalized cellular automaton, exhibiting solitonic interactions, can be explicitly solved by means of techniques first introduced in the context of the scattering problem for the KdV equation. We apply this method to calculate the phase-shifts caused by interactions between the solitonic and non-solitonic parts into which arbitrary initial states separate in time.
Innovative Second Language Speaking Practice with Interactive Videos in a Rich Internet Application Environment

ERIC Educational Resources Information Center

Pereira, Juan A.; Sanz-Santamaría, Silvia; Montero, Raúl; Gutiérrez, Julián

2012-01-01

Attaining a satisfactory level of oral communication in a second language is a laborious process. In this action research paper we describe a new method applied through the use of interactive videos and the Babelium Project Rich Internet Application (RIA), which allows students to practice speaking skills through a variety of exercises. We present…
Beyond Astro 101: A First Report on Applying Interactive Education Techniques to an Astronphysics Class for Majors

NASA Astrophysics Data System (ADS)

Perrin, Marshall D.; Ghez, A. M.

2009-05-01

Learner-centered interactive instruction methods now have a proven track record in improving learning in "Astro 101" courses for non-majors, but have rarely been applied to higher-level astronomy courses. Can we hope for similar gains in classes aimed at astrophysics majors, or is the subject matter too fundamentally different for those techniques to apply? We present here an initial report on an updated calculus-based Introduction to Astrophysics class at UCLA that suggests such techniques can indeed result in increased learning for major students. We augmented the traditional blackboard-derivation lectures and challenging weekly problem sets by adding online questions on pre-reading assignments (''just-in-time teaching'') and frequent multiple-choice questions in class ("Think-Pair-Share''). We describe our approach, and present examples of the new Think-Pair-Share questions developed for this more sophisticated material. Our informal observations after one term are that with this approach, students are more engaged and alert, and score higher on exams than typical in previous years. This is anecdotal evidence, not hard data yet, and there is clearly a vast amount of work to be done in this area. But our first impressions strongly encourage us that interactive methods should be able improve the astrophysics major just as they have improved Astro 101.
A combined TLD/emulsion method of sampling dosimetry applied to Apollo missions

NASA Technical Reports Server (NTRS)

Schaefer, H. J.

1979-01-01

A system which simplifies the complex monitoring methods used to measure the astronaut's radiation exposure in space is proposed. The excess dose equivalents of trapped protons and secondary neutrons, protons, and alpha particles from local nuclear interactions are determined and a combined thermoluminescent dosimeter (TLD)/nuclear emulsion method which measures the absorbed dose with thermoluminescent dosimeter chips is presented.
A numerical model of a red blood cell infected by Plasmodium falciparum malaria: coupling cell mechanics with ligand-receptor interactions

NASA Astrophysics Data System (ADS)

Ishida, Shunichi; Imai, Yohsuke; Ichikawa, Yuki; Nix, Stephanie; Matsunaga, Daiki; Omori, Toshihiro; Ishikawa, Takuji

2016-01-01

We developed a numerical model of the behavior of a red blood cell infected by Plasmodium falciparum malaria on a wall in shear flow. The fluid and solid mechanics of an infected red blood cell (Pf-IRBC) were coupled with the biochemical interaction of ligand-receptor bindings. We used the boundary element method for fluid mechanics, the finite element method for membrane mechanics, and the Monte Carlo method for ligand-receptor interactions. We simulated the behavior of a Pf-IRBC in shear flow, focusing on the effects of bond type. For slip bonds, the Pf-IRBC exhibited firm adhesion, tumbling motion, and tank-treading motion, depending on the applied shear rate. The behavior of catch bonds resembled that of slip bonds, except for a 'catch' state at high shear stress. When the reactive compliance decreased to a value in the order of ? nm, both the slip and catch bonds behaved like an ideal bond. Such bonds do not respond to the force applied to the bond, and the velocity is stabilized at a high shear rate. Finally, we compared the numerical results with previous experiments for A4- and ItG-infected cells. We found that the interaction between PfEMP1 and ICAM-1 could be a nearly ideal bond, with a dissociation rate ranging from ? to ?.
Collaborative simulation method with spatiotemporal synchronization process control

NASA Astrophysics Data System (ADS)

Zou, Yisheng; Ding, Guofu; Zhang, Weihua; Zhang, Jian; Qin, Shengfeng; Tan, John Kian

2016-10-01

When designing a complex mechatronics system, such as high speed trains, it is relatively difficult to effectively simulate the entire system's dynamic behaviors because it involves multi-disciplinary subsystems. Currently,a most practical approach for multi-disciplinary simulation is interface based coupling simulation method, but it faces a twofold challenge: spatial and time unsynchronizations among multi-directional coupling simulation of subsystems. A new collaborative simulation method with spatiotemporal synchronization process control is proposed for coupling simulating a given complex mechatronics system across multiple subsystems on different platforms. The method consists of 1) a coupler-based coupling mechanisms to define the interfacing and interaction mechanisms among subsystems, and 2) a simulation process control algorithm to realize the coupling simulation in a spatiotemporal synchronized manner. The test results from a case study show that the proposed method 1) can certainly be used to simulate the sub-systems interactions under different simulation conditions in an engineering system, and 2) effectively supports multi-directional coupling simulation among multi-disciplinary subsystems. This method has been successfully applied in China high speed train design and development processes, demonstrating that it can be applied in a wide range of engineering systems design and simulation with improved efficiency and effectiveness.
Interactive visual exploration and analysis of origin-destination data

NASA Astrophysics Data System (ADS)

Ding, Linfang; Meng, Liqiu; Yang, Jian; Krisp, Jukka M.

2018-05-01

In this paper, we propose a visual analytics approach for the exploration of spatiotemporal interaction patterns of massive origin-destination data. Firstly, we visually query the movement database for data at certain time windows. Secondly, we conduct interactive clustering to allow the users to select input variables/features (e.g., origins, destinations, distance, and duration) and to adjust clustering parameters (e.g. distance threshold). The agglomerative hierarchical clustering method is applied for the multivariate clustering of the origin-destination data. Thirdly, we design a parallel coordinates plot for visualizing the precomputed clusters and for further exploration of interesting clusters. Finally, we propose a gradient line rendering technique to show the spatial and directional distribution of origin-destination clusters on a map view. We implement the visual analytics approach in a web-based interactive environment and apply it to real-world floating car data from Shanghai. The experiment results show the origin/destination hotspots and their spatial interaction patterns. They also demonstrate the effectiveness of our proposed approach.
Assessment of PIV-based unsteady load determination of an airfoil with actuated flap

NASA Astrophysics Data System (ADS)

Sterenborg, J. J. H. M.; Lindeboom, R. C. J.; Simão Ferreira, C. J.; van Zuijlen, A. H.; Bijl, H.

2014-02-01

For complex experimental setups involving movable structures it is not trivial to directly measure unsteady loads. An alternative is to deduce unsteady loads indirectly from measured velocity fields using Noca's method. The ultimate aim is to use this method in future work to determine unsteady loads for fluid-structure interaction problems. The focus in this paper is first on the application and assessment of Noca's method for an airfoil with an oscillating trailing edge flap. To our best knowledge Noca's method has not been applied yet to airfoils with moving control surfaces or fluid-structure interaction problems. In addition, wind tunnel corrections for this type of unsteady flow problem are considered.
Interactive and Hands-on Methods for Professional Development of Undergraduate Researchers

NASA Astrophysics Data System (ADS)

Pressley, S. N.; LeBeau, J. E.

2016-12-01

Professional development workshops for undergraduate research programs can range from communicating science (i.e. oral, technical writing, poster presentations), applying for fellowships and scholarships, applying to graduate school, and learning about careers, among others. Novel methods of presenting the information on the above topics can result in positive outcomes beyond the obvious of transferring knowledge. Examples of innovative methods to present professional development information include 1) An interactive session on how to write an abstract where students are given an opportunity to draft an abstract from a short technical article, followed by discussion amongst a group of peers, and comparison with the "published" abstract. 2) Using the Process Oriented Guided Inquiry Learning (POGIL) method to evaluate and critique a research poster. 3) Inviting "experts" such as a Fulbright scholar graduate student to present on applying for fellowships and scholarships. These innovative methods of delivery provide more hands-on activities that engage the students, and in some cases (abstract writing) provide practice for the student. The methods also require that students develop team work skills, communicate amongst their peers, and develop networks with their cohort. All of these are essential non-technical skills needed for success in any career. Feedback from students on these sessions are positive and most importantly, the students walk out of the session with a smile on their face saying how much fun it was. Evaluating the impact of these sessions is more challenging and under investigation currently.
Application of interactive computer graphics in wind-tunnel dynamic model testing

NASA Technical Reports Server (NTRS)

Doggett, R. V., Jr.; Hammond, C. E.

1975-01-01

The computer-controlled data-acquisition system recently installed for use with a transonic dynamics tunnel was described. This includes a discussion of the hardware/software features of the system. A subcritical response damping technique, called the combined randomdec/moving-block method, for use in windtunnel-model flutter testing, that has been implemented on the data-acquisition system, is described in some detail. Some results using the method are presented and the importance of using interactive graphics in applying the technique in near real time during wind-tunnel test operations is discussed.
Inference of Time-Evolving Coupled Dynamical Systems in the Presence of Noise

NASA Astrophysics Data System (ADS)

Stankovski, Tomislav; Duggento, Andrea; McClintock, Peter V. E.; Stefanovska, Aneta

2012-07-01

A new method is introduced for analysis of interactions between time-dependent coupled oscillators, based on the signals they generate. It distinguishes unsynchronized dynamics from noise-induced phase slips and enables the evolution of the coupling functions and other parameters to be followed. It is based on phase dynamics, with Bayesian inference of the time-evolving parameters achieved by shaping the prior densities to incorporate knowledge of previous samples. The method is tested numerically and applied to reveal and quantify the time-varying nature of cardiorespiratory interactions.
Laser Interferometry Method as a Novel Tool in Endotoxins Research.

PubMed

Arabski, Michał; Wąsik, Sławomir

2017-01-01

Optical properties of chemical substances are widely used at present for assays thereof in a variety of scientific disciplines. One of the measurement techniques applied in physical sciences, with a potential for novel applications in biology, is laser interferometry. This method enables to record the diffusion properties of chemical substances. Here we describe the novel application of laser interferometry in chitosan interactions with lipopolysaccharide by detection of colistin diffusion. The proposed model could be used in simple measurements of polymer interactions with endotoxins and/or biological active compounds, like antibiotics.
Floating Node Method and Virtual Crack Closure Technique for Modeling Matrix Cracking-Delamination Interaction

NASA Technical Reports Server (NTRS)

DeCarvalho, N. V.; Chen, B. Y.; Pinho, S. T.; Baiz, P. M.; Ratcliffe, J. G.; Tay, T. E.

2013-01-01

A novel approach is proposed for high-fidelity modeling of progressive damage and failure in composite materials that combines the Floating Node Method (FNM) and the Virtual Crack Closure Technique (VCCT) to represent multiple interacting failure mechanisms in a mesh-independent fashion. In this study, the approach is applied to the modeling of delamination migration in cross-ply tape laminates. Delamination, matrix cracking, and migration are all modeled using fracture mechanics based failure and migration criteria. The methodology proposed shows very good qualitative and quantitative agreement with experiments.
Configuration-interaction relativistic-many-body-perturbation-theory calculations of photoionization cross sections from quasicontinuum oscillator strengths

DOE PAGES

Savukov, I. M.; Filin, D. V.

2014-12-29

Many applications are in need of accurate photoionization cross sections, especially in the case of complex atoms. Configuration-interaction relativistic-many-body-perturbation theory (CI-RMBPT) has been successful in predicting atomic energies, matrix elements between discrete states, and other properties, which is quite promising, but it has not been applied to photoionization problems owing to extra complications arising from continuum states. In this paper a method that will allow the conversion of discrete CI-(R)MPBT oscillator strengths (OS) to photoionization cross sections with minimal modifications of the codes is introduced and CI-RMBPT cross sections of Ne, Ar, Kr, and Xe are calculated. A consistent agreementmore » with experiment is found. RMBPT corrections are particularly significant for Ar, Kr, and Xe and improve agreement with experimental results compared to the particle-hole CI method. As a result, the demonstrated conversion method can be applied to CI-RMBPT photoionization calculations for a large number of multivalence atoms and ions.« less
Interaction entropy for protein-protein binding

NASA Astrophysics Data System (ADS)

Sun, Zhaoxi; Yan, Yu N.; Yang, Maoyou; Zhang, John Z. H.

2017-03-01

Protein-protein interactions are at the heart of signal transduction and are central to the function of protein machine in biology. The highly specific protein-protein binding is quantitatively characterized by the binding free energy whose accurate calculation from the first principle is a grand challenge in computational biology. In this paper, we show how the interaction entropy approach, which was recently proposed for protein-ligand binding free energy calculation, can be applied to computing the entropic contribution to the protein-protein binding free energy. Explicit theoretical derivation of the interaction entropy approach for protein-protein interaction system is given in detail from the basic definition. Extensive computational studies for a dozen realistic protein-protein interaction systems are carried out using the present approach and comparisons of the results for these protein-protein systems with those from the standard normal mode method are presented. Analysis of the present method for application in protein-protein binding as well as the limitation of the method in numerical computation is discussed. Our study and analysis of the results provided useful information for extracting correct entropic contribution in protein-protein binding from molecular dynamics simulations.
Coupling functions: Universal insights into dynamical interaction mechanisms

NASA Astrophysics Data System (ADS)

Stankovski, Tomislav; Pereira, Tiago; McClintock, Peter V. E.; Stefanovska, Aneta

2017-10-01

The dynamical systems found in nature are rarely isolated. Instead they interact and influence each other. The coupling functions that connect them contain detailed information about the functional mechanisms underlying the interactions and prescribe the physical rule specifying how an interaction occurs. A coherent and comprehensive review is presented encompassing the rapid progress made recently in the analysis, understanding, and applications of coupling functions. The basic concepts and characteristics of coupling functions are presented through demonstrative examples of different domains, revealing the mechanisms and emphasizing their multivariate nature. The theory of coupling functions is discussed through gradually increasing complexity from strong and weak interactions to globally coupled systems and networks. A variety of methods that have been developed for the detection and reconstruction of coupling functions from measured data is described. These methods are based on different statistical techniques for dynamical inference. Stemming from physics, such methods are being applied in diverse areas of science and technology, including chemistry, biology, physiology, neuroscience, social sciences, mechanics, and secure communications. This breadth of application illustrates the universality of coupling functions for studying the interaction mechanisms of coupled dynamical systems.
VIBRA: An interactive computer program for steady-state vibration response analysis of linear damped structures

NASA Technical Reports Server (NTRS)

Bowman, L. M.

1984-01-01

An interactive steady state frequency response computer program with graphics is documented. Single or multiple forces may be applied to the structure using a modal superposition approach to calculate response. The method can be reapplied to linear, proportionally damped structures in which the damping may be viscous or structural. The theoretical approach and program organization are described. Example problems, user instructions, and a sample interactive session are given to demonstate the program's capability in solving a variety of problems.
Optimal Design for the Precise Estimation of an Interaction Threshold: The Impact of Exposure to a Mixture of 18 Polyhalogenated Aromatic Hydrocarbons

PubMed Central

Yeatts, Sharon D.; Gennings, Chris; Crofton, Kevin M.

2014-01-01

Traditional additivity models provide little flexibility in modeling the dose–response relationships of the single agents in a mixture. While the flexible single chemical required (FSCR) methods allow greater flexibility, its implicit nature is an obstacle in the formation of the parameter covariance matrix, which forms the basis for many statistical optimality design criteria. The goal of this effort is to develop a method for constructing the parameter covariance matrix for the FSCR models, so that (local) alphabetic optimality criteria can be applied. Data from Crofton et al. are provided as motivation; in an experiment designed to determine the effect of 18 polyhalogenated aromatic hydrocarbons on serum total thyroxine (T4), the interaction among the chemicals was statistically significant. Gennings et al. fit the FSCR interaction threshold model to the data. The resulting estimate of the interaction threshold was positive and within the observed dose region, providing evidence of a dose-dependent interaction. However, the corresponding likelihood-ratio-based confidence interval was wide and included zero. In order to more precisely estimate the location of the interaction threshold, supplemental data are required. Using the available data as the first stage, the Ds-optimal second-stage design criterion was applied to minimize the variance of the hypothesized interaction threshold. Practical concerns associated with the resulting design are discussed and addressed using the penalized optimality criterion. Results demonstrate that the penalized Ds-optimal second-stage design can be used to more precisely define the interaction threshold while maintaining the characteristics deemed important in practice. PMID:22640366

A semi-implicit level set method for multiphase flows and fluid-structure interaction problems

NASA Astrophysics Data System (ADS)

Cottet, Georges-Henri; Maitre, Emmanuel

2016-06-01

In this paper we present a novel semi-implicit time-discretization of the level set method introduced in [8] for fluid-structure interaction problems. The idea stems from a linear stability analysis derived on a simplified one-dimensional problem. The semi-implicit scheme relies on a simple filter operating as a pre-processing on the level set function. It applies to multiphase flows driven by surface tension as well as to fluid-structure interaction problems. The semi-implicit scheme avoids the stability constraints that explicit scheme need to satisfy and reduces significantly the computational cost. It is validated through comparisons with the original explicit scheme and refinement studies on two-dimensional benchmarks.
Coulomb interactions in charged fluids.

PubMed

Vernizzi, Graziano; Guerrero-García, Guillermo Iván; de la Cruz, Monica Olvera

2011-07-01

The use of Ewald summation schemes for calculating long-range Coulomb interactions, originally applied to ionic crystalline solids, is a very common practice in molecular simulations of charged fluids at present. Such a choice imposes an artificial periodicity which is generally absent in the liquid state. In this paper we propose a simple analytical O(N(2)) method which is based on Gauss's law for computing exactly the Coulomb interaction between charged particles in a simulation box, when it is averaged over all possible orientations of a surrounding infinite lattice. This method mitigates the periodicity typical of crystalline systems and it is suitable for numerical studies of ionic liquids, charged molecular fluids, and colloidal systems with Monte Carlo and molecular dynamics simulations.
Analysis of Tire Tractive Performance on Deformable Terrain by Finite Element-Discrete Element Method

NASA Astrophysics Data System (ADS)

Nakashima, Hiroshi; Takatsu, Yuzuru

The goal of this study is to develop a practical and fast simulation tool for soil-tire interaction analysis, where finite element method (FEM) and discrete element method (DEM) are coupled together, and which can be realized on a desktop PC. We have extended our formerly proposed dynamic FE-DE method (FE-DEM) to include practical soil-tire system interaction, where not only the vertical sinkage of a tire, but also the travel of a driven tire was considered. Numerical simulation by FE-DEM is stable, and the relationships between variables, such as load-sinkage and sinkage-travel distance, and the gross tractive effort and running resistance characteristics, are obtained. Moreover, the simulation result is accurate enough to predict the maximum drawbar pull for a given tire, once the appropriate parameter values are provided. Therefore, the developed FE-DEM program can be applied with sufficient accuracy to interaction problems in soil-tire systems.
Latent interaction effects in the theory of planned behaviour applied to quitting smoking.

PubMed

Hukkelberg, Silje Sommer; Hagtvet, Knut A; Kovac, Velibor Bobo

2014-02-01

This study applies three latent interaction models in the theory of planned behaviour (TPB; Ajzen, 1988, Attitudes, personality, and behavior. Homewood, IL: Dorsey Press; Ajzen, 1991, Organ. Behav. Hum. Decis. Process., 50, 179) to quitting smoking: (1) attitude × perceived behavioural control on intention; (2) subjective norms (SN) × attitude on intention; and (3) perceived behavioural control × intention on quitting behaviour. The data derive from a longitudinal Internet survey of 939 smokers aged 15-74 over a period of 4 months. Latent interaction effects were estimated using the double-mean-centred unconstrained approach (Lin et al., 2010, Struct. Equ. Modeling, 17, 374) in LISREL. Attitude × SN and attitude × perceived behavioural control both showed a significant interaction effect on intention. No significant interaction effect was found for perceived behavioural control × intention on quitting. The latent interaction approach is a useful method for investigating specific conditions between TPB components in the context of quitting behaviour. Theoretical and practical implications of the results are discussed. © 2013 The British Psychological Society.
Predicting the points of interaction of small molecules in the NF-κB pathway

PubMed Central

2011-01-01

Background The similarity property principle has been used extensively in drug discovery to identify small compounds that interact with specific drug targets. Here we show it can be applied to identify the interactions of small molecules within the NF-κB signalling pathway. Results Clusters that contain compounds with a predominant interaction within the pathway were created, which were then used to predict the interaction of compounds not included in the clustering analysis. Conclusions The technique successfully predicted the points of interactions of compounds that are known to interact with the NF-κB pathway. The method was also shown to be successful when compounds for which the interaction points were unknown were included in the clustering analysis. PMID:21342508
Metabolic Network Modeling of Microbial Interactions in Natural and Engineered Environmental Systems

PubMed Central

Perez-Garcia, Octavio; Lear, Gavin; Singhal, Naresh

2016-01-01

We review approaches to characterize metabolic interactions within microbial communities using Stoichiometric Metabolic Network (SMN) models for applications in environmental and industrial biotechnology. SMN models are computational tools used to evaluate the metabolic engineering potential of various organisms. They have successfully been applied to design and optimize the microbial production of antibiotics, alcohols and amino acids by single strains. To date however, such models have been rarely applied to analyze and control the metabolism of more complex microbial communities. This is largely attributed to the diversity of microbial community functions, metabolisms, and interactions. Here, we firstly review different types of microbial interaction and describe their relevance for natural and engineered environmental processes. Next, we provide a general description of the essential methods of the SMN modeling workflow including the steps of network reconstruction, simulation through Flux Balance Analysis (FBA), experimental data gathering, and model calibration. Then we broadly describe and compare four approaches to model microbial interactions using metabolic networks, i.e., (i) lumped networks, (ii) compartment per guild networks, (iii) bi-level optimization simulations, and (iv) dynamic-SMN methods. These approaches can be used to integrate and analyze diverse microbial physiology, ecology and molecular community data. All of them (except the lumped approach) are suitable for incorporating species abundance data but so far they have been used only to model simple communities of two to eight different species. Interactions based on substrate exchange and competition can be directly modeled using the above approaches. However, interactions based on metabolic feedbacks, such as product inhibition and synthropy require extensions to current models, incorporating gene regulation and compounding accumulation mechanisms. SMN models of microbial interactions can be used to analyze complex “omics” data and to infer and optimize metabolic processes. Thereby, SMN models are suitable to capitalize on advances in high-throughput molecular and metabolic data generation. SMN models are starting to be applied to describe microbial interactions during wastewater treatment, in-situ bioremediation, microalgae blooms methanogenic fermentation, and bioplastic production. Despite their current challenges, we envisage that SMN models have future potential for the design and development of novel growth media, biochemical pathways and synthetic microbial associations. PMID:27242701
Multi-View Interaction Modelling of human collaboration processes: a business process study of head and neck cancer care in a Dutch academic hospital.

PubMed

Stuit, Marco; Wortmann, Hans; Szirbik, Nick; Roodenburg, Jan

2011-12-01

In the healthcare domain, human collaboration processes (HCPs), which consist of interactions between healthcare workers from different (para)medical disciplines and departments, are of growing importance as healthcare delivery becomes increasingly integrated. Existing workflow-based process modelling tools for healthcare process management, which are the most commonly applied, are not suited for healthcare HCPs mainly due to their focus on the definition of task sequences instead of the graphical description of human interactions. This paper uses a case study of a healthcare HCP at a Dutch academic hospital to evaluate a novel interaction-centric process modelling method. The HCP under study is the care pathway performed by the head and neck oncology team. The evaluation results show that the method brings innovative, effective, and useful features. First, it collects and formalizes the tacit domain knowledge of the interviewed healthcare workers in individual interaction diagrams. Second, the method automatically integrates these local diagrams into a single global interaction diagram that reflects the consolidated domain knowledge. Third, the case study illustrates how the method utilizes a graphical modelling language for effective tree-based description of interactions, their composition and routing relations, and their roles. A process analysis of the global interaction diagram is shown to identify HCP improvement opportunities. The proposed interaction-centric method has wider applicability since interactions are the core of most multidisciplinary patient-care processes. A discussion argues that, although (multidisciplinary) collaboration is in many cases not optimal in the healthcare domain, it is increasingly considered a necessity to improve integration, continuity, and quality of care. The proposed method is helpful to describe, analyze, and improve the functioning of healthcare collaboration. Copyright © 2011 Elsevier Inc. All rights reserved.
Label-enhanced surface plasmon resonance applied to label-free interaction analysis of small molecules and fragments.

PubMed

Eng, Lars; Nygren-Babol, Linnéa; Hanning, Anders

2016-10-01

Surface plasmon resonance (SPR) is a well-established method for studying interactions between small molecules and biomolecules. In particular, SPR is being increasingly applied within fragment-based drug discovery; however, within this application area, the limited sensitivity of SPR may constitute a problem. This problem can be circumvented by the use of label-enhanced SPR that shows a 100-fold higher sensitivity as compared with conventional SPR. Truly label-free interaction data for small molecules can be obtained by applying label-enhanced SPR in a surface competition assay format. The enhanced sensitivity is accompanied by an increased specificity and inertness toward disturbances (e.g., bulk refractive index disturbances). Label-enhanced SPR can be used for fragment screening in a competitive assay format; the competitive format has the added advantage of confirming the specificity of the molecular interaction. In addition, label-enhanced SPR extends the accessible kinetic regime of SPR to the analysis of very fast fragment binding kinetics. In this article, we demonstrate the working principles and benchmark the performance of label-enhanced SPR in a model system-the interaction between carbonic anhydrase II and a number of small-molecule sulfonamide-based inhibitors. Copyright © 2016 Elsevier Inc. All rights reserved.
Masses of constituent quarks confined in open bottom hadrons

NASA Astrophysics Data System (ADS)

Borka Jovanović, V.; Borka, D.; Jovanović, P.; Milošević, J.; Ignjatović, S. R.

2014-12-01

We apply color-spin and flavor-spin quark-quark interactions to the meson and baryon constituent quarks, and calculate constituent quark masses, as well as the coupling constants of these interactions. The main goal of this paper was to determine constituent quark masses from light and open bottom hadron masses, using the fitting method we have developed and clustering of hadron groups. We use color-spin Fermi-Breit (FB) and flavor-spin Glozman-Riska (GR) hyperfine interaction (HFI) to determine constituent quark masses (especially b quark mass). Another aim was to discern between the FB and GR HFI because our previous findings had indicated that both interactions were satisfactory. Our improved fitting procedure of constituent quark masses showed that on average color-spin (FB) HFI yields better fits. The method also shows the way how the constituent quark masses and the strength of the interaction constants appear in different hadron environments.
Final state interactions and the transverse structure of the pion using non-perturbative eikonal methods

DOE PAGES

Gamberg, Leonard; Schlegel, Marc

2010-01-18

In the factorized picture of semi-inclusive hadronic processes the naive time reversal-odd parton distributions exist by virtue of the gauge link which renders it color gauge invariant. The link characterizes the dynamical effect of initial/final-state interactions of the active parton due soft gluon exchanges with the target remnant. Though these interactions are non-perturbative, studies of final-state interaction have been approximated by perturbative one-gluon approximation in Abelian models. We include higher-order contributions by applying non-perturbative eikonal methods incorporating color degrees of freedom in a calculation of the Boer-Mulders function of the pion. Lastly, using this framework we explore under what conditionsmore » the Boer Mulders function can be described in terms of factorization of final state interactions and a spatial distribution in impact parameter space.« less
Automated identification of social interaction criteria in Drosophila melanogaster.

PubMed

Schneider, J; Levine, J D

2014-10-01

The study of social behaviour within groups has relied on fixed definitions of an 'interaction'. Criteria used in these definitions often involve a subjectively defined cut-off value for proximity, orientation and time (e.g. courtship, aggression and social interaction networks) and the same numerical values for these criteria are applied to all of the treatment groups within an experiment. One universal definition of an interaction could misidentify interactions within groups that differ in life histories, study treatments and/or genetic mutations. Here, we present an automated method for determining the values of interaction criteria using a pre-defined rule set rather than pre-defined values. We use this approach and show changing social behaviours in different manipulations of Drosophila melanogaster. We also show that chemosensory cues are an important modality of social spacing and interaction. This method will allow a more robust analysis of the properties of interacting groups, while helping us understand how specific groups regulate their social interaction space. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Interactive design optimization of magnetorheological-brake actuators using the Taguchi method

NASA Astrophysics Data System (ADS)

Erol, Ozan; Gurocak, Hakan

2011-10-01

This research explored an optimization method that would automate the process of designing a magnetorheological (MR)-brake but still keep the designer in the loop. MR-brakes apply resistive torque by increasing the viscosity of an MR fluid inside the brake. This electronically controllable brake can provide a very large torque-to-volume ratio, which is very desirable for an actuator. However, the design process is quite complex and time consuming due to many parameters. In this paper, we adapted the popular Taguchi method, widely used in manufacturing, to the problem of designing a complex MR-brake. Unlike other existing methods, this approach can automatically identify the dominant parameters of the design, which reduces the search space and the time it takes to find the best possible design. While automating the search for a solution, it also lets the designer see the dominant parameters and make choices to investigate only their interactions with the design output. The new method was applied for re-designing MR-brakes. It reduced the design time from a week or two down to a few minutes. Also, usability experiments indicated significantly better brake designs by novice users.
FLUORESCENT IN SITU HYBRIDIZATION AND MICROAUTORADIOGRAPHY APPLIED TO ECOPHYSIOLOGY IN SOIL

EPA Science Inventory

Soil microbial communities perform many important processes, including nutrient cycling, plant-microorganism interactions, and degradation of xenobiotics. The study of microbial communities, however, has been limited by cultural methods, which may greatly underestimate diversity....
The Interaction between Heterotrophic Bacteria and Coliform, Fecal Coliform, Fecal Streptococci Bacteria in the Water Supply Networks

PubMed Central

AMANIDAZ, Nazak; ZAFARZADEH, Ali; MAHVI, Amir Hossein

2015-01-01

Background: This study investigated the interaction between heterotrophic bacteria and coliform, fecal coliforms, fecal streptococci bacteria in water supply networks. Methods: This study was conducted during 2013 on water supply distribution network in Aq Qala City, Golestan Province, Northern Iran and standard methods were applied for microbiological analysis. The surface method was applied to test the heterotrophic bacteria and MPN method was used for coliform, fecal coliform and fecal streptococci bacteria measurements. Results: In 114 samples, heterotrophic bacteria count were over 500 CFU/ml, which the amount of fecal coliform, coliform, and fecal streptococci were 8, 32, and 20 CFU/100 ml, respectively. However, in the other 242 samples, with heterotrophic bacteria count being less than 500 CFU/ml, the amount of fecal coliform, coliform, and fecal streptococci was 7, 23, and 11 CFU/100ml, respectively. The relationship between heterotrophic bacteria, coliforms and fecal streptococci was highly significant (P<0.05). We observed the concentration of coliforms, fecal streptococci bacteria being high, whenever the concentration of heterotrophic bacteria in the water network systems was high. Conclusion: Interaction between heterotrophic bacteria and coliform, fecal coliforms, fecal streptococci bacteria in the Aq Qala City water supply networks was not notable. It can be due to high concentrations of organic carbon, bio-films and nutrients, which are necessary for growth, and survival of all microorganisms. PMID:26811820
Influence of nuclear interactions in body tissues on tumor dose in carbon-ion radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Inaniwa, T., E-mail: taku@nirs.go.jp; Kanematsu, N.; Tsuji, H.

2015-12-15

Purpose: In carbon-ion radiotherapy treatment planning, the planar integrated dose (PID) measured in water is applied to the patient dose calculation with density scaling using the stopping power ratio. Since body tissues are chemically different from water, this dose calculation can be subject to errors, particularly due to differences in inelastic nuclear interactions. In recent studies, the authors proposed and validated a PID correction method for these errors. In the present study, the authors used this correction method to assess the influence of these nuclear interactions in body tissues on tumor dose in various clinical cases. Methods: Using 10–20 casesmore » each of prostate, head and neck (HN), bone and soft tissue (BS), lung, liver, pancreas, and uterine neoplasms, the authors first used treatment plans for carbon-ion radiotherapy without nuclear interaction correction to derive uncorrected dose distributions. The authors then compared these distributions with recalculated distributions using the nuclear interaction correction (corrected dose distributions). Results: Median (25%/75% quartiles) differences between the target mean uncorrected doses and corrected doses were 0.2% (0.1%/0.2%), 0.0% (0.0%/0.0%), −0.3% (−0.4%/−0.2%), −0.1% (−0.2%/−0.1%), −0.1% (−0.2%/0.0%), −0.4% (−0.5%/−0.1%), and −0.3% (−0.4%/0.0%) for the prostate, HN, BS, lung, liver, pancreas, and uterine cases, respectively. The largest difference of −1.6% in target mean and −2.5% at maximum were observed in a uterine case. Conclusions: For most clinical cases, dose calculation errors due to the water nonequivalence of the tissues in nuclear interactions would be marginal compared to intrinsic uncertainties in treatment planning, patient setup, beam delivery, and clinical response. In some extreme cases, however, these errors can be substantial. Accordingly, this correction method should be routinely applied to treatment planning in clinical practice.« less
Parallel tempering Monte Carlo simulations of lysozyme orientation on charged surfaces

NASA Astrophysics Data System (ADS)

Xie, Yun; Zhou, Jian; Jiang, Shaoyi

2010-02-01

In this work, the parallel tempering Monte Carlo (PTMC) algorithm is applied to accurately and efficiently identify the global-minimum-energy orientation of a protein adsorbed on a surface in a single simulation. When applying the PTMC method to simulate lysozyme orientation on charged surfaces, it is found that lysozyme could easily be adsorbed on negatively charged surfaces with "side-on" and "back-on" orientations. When driven by dominant electrostatic interactions, lysozyme tends to be adsorbed on negatively charged surfaces with the side-on orientation for which the active site of lysozyme faces sideways. The side-on orientation agrees well with the experimental results where the adsorbed orientation of lysozyme is determined by electrostatic interactions. As the contribution from van der Waals interactions gradually dominates, the back-on orientation becomes the preferred one. For this orientation, the active site of lysozyme faces outward, which conforms to the experimental results where the orientation of adsorbed lysozyme is co-determined by electrostatic interactions and van der Waals interactions. It is also found that despite of its net positive charge, lysozyme could be adsorbed on positively charged surfaces with both "end-on" and back-on orientations owing to the nonuniform charge distribution over lysozyme surface and the screening effect from ions in solution. The PTMC simulation method provides a way to determine the preferred orientation of proteins on surfaces for biosensor and biomaterial applications.
Design of Intelligent Robot as A Tool for Teaching Media Based on Computer Interactive Learning and Computer Assisted Learning to Improve the Skill of University Student

NASA Astrophysics Data System (ADS)

Zuhrie, M. S.; Basuki, I.; Asto B, I. G. P.; Anifah, L.

2018-01-01

The focus of the research is the teaching module which incorporates manufacturing, planning mechanical designing, controlling system through microprocessor technology and maneuverability of the robot. Computer interactive and computer-assisted learning is strategies that emphasize the use of computers and learning aids (computer assisted learning) in teaching and learning activity. This research applied the 4-D model research and development. The model is suggested by Thiagarajan, et.al (1974). 4-D Model consists of four stages: Define Stage, Design Stage, Develop Stage, and Disseminate Stage. This research was conducted by applying the research design development with an objective to produce a tool of learning in the form of intelligent robot modules and kit based on Computer Interactive Learning and Computer Assisted Learning. From the data of the Indonesia Robot Contest during the period of 2009-2015, it can be seen that the modules that have been developed confirm the fourth stage of the research methods of development; disseminate method. The modules which have been developed for students guide students to produce Intelligent Robot Tool for Teaching Based on Computer Interactive Learning and Computer Assisted Learning. Results of students’ responses also showed a positive feedback to relate to the module of robotics and computer-based interactive learning.
Comparison of fuzzy AHP and fuzzy TODIM methods for landfill location selection.

PubMed

Hanine, Mohamed; Boutkhoum, Omar; Tikniouine, Abdessadek; Agouti, Tarik

2016-01-01

Landfill location selection is a multi-criteria decision problem and has a strategic importance for many regions. The conventional methods for landfill location selection are insufficient in dealing with the vague or imprecise nature of linguistic assessment. To resolve this problem, fuzzy multi-criteria decision-making methods are proposed. The aim of this paper is to use fuzzy TODIM (the acronym for Interactive and Multi-criteria Decision Making in Portuguese) and the fuzzy analytic hierarchy process (AHP) methods for the selection of landfill location. The proposed methods have been applied to a landfill location selection problem in the region of Casablanca, Morocco. After determining the criteria affecting the landfill location decisions, fuzzy TODIM and fuzzy AHP methods are applied to the problem and results are presented. The comparisons of these two methods are also discussed.
Mining association patterns of drug-interactions using post marketing FDA's spontaneous reporting data.

PubMed

Ibrahim, Heba; Saad, Amr; Abdo, Amany; Sharaf Eldin, A

2016-04-01

Pharmacovigilance (PhV) is an important clinical activity with strong implications for population health and clinical research. The main goal of PhV is the timely detection of adverse drug events (ADEs) that are novel in their clinical nature, severity and/or frequency. Drug interactions (DI) pose an important problem in the development of new drugs and post marketing PhV that contribute to 6-30% of all unexpected ADEs. Therefore, the early detection of DI is vital. Spontaneous reporting systems (SRS) have served as the core data collection system for post marketing PhV since the 1960s. The main objective of our study was to particularly identify signals of DI from SRS. In addition, we are presenting an optimized tailored mining algorithm called "hybrid Apriori". The proposed algorithm is based on an optimized and modified association rule mining (ARM) approach. A hybrid Apriori algorithm has been applied to the SRS of the United States Food and Drug Administration's (U.S. FDA) adverse events reporting system (FAERS) in order to extract significant association patterns of drug interaction-adverse event (DIAE). We have assessed the resulting DIAEs qualitatively and quantitatively using two different triage features: a three-element taxonomy and three performance metrics. These features were applied on two random samples of 100 interacting and 100 non-interacting DIAE patterns. Additionally, we have employed logistic regression (LR) statistic method to quantify the magnitude and direction of interactions in order to test for confounding by co-medication in unknown interacting DIAE patterns. Hybrid Apriori extracted 2933 interacting DIAE patterns (including 1256 serious ones) and 530 non-interacting DIAE patterns. Referring to the current knowledge using four different reliable resources of DI, the results showed that the proposed method can extract signals of serious interacting DIAEs. Various association patterns could be identified based on the relationships among the elements which composed a pattern. The average performance of the method showed 85% precision, 80% negative predictive value, 81% sensitivity and 84% specificity. The LR modeling could provide the statistical context to guard against spurious DIAEs. The proposed method could efficiently detect DIAE signals from SRS data as well as, identifying rare adverse drug reactions (ADRs). Copyright © 2016 Elsevier Inc. All rights reserved.
Discontinuous Galerkin method for coupled problems of compressible flow and elastic structures

NASA Astrophysics Data System (ADS)

Kosík, A.; Feistauer, M.; Hadrava, M.; Horáček, J.

2013-10-01

This paper is concerned with the numerical simulation of the interaction of 2D compressible viscous flow and an elastic structure. We consider the model of dynamical linear elasticity. Each individual problem is discretized in space by the discontinuous Galerkin method (DGM). For the time discretization we can use either the BDF (backward difference formula) method or also the DGM. The time dependence of the domain occupied by the fluid is given by the deformation of the elastic structure adjacent to the flow domain. It is treated with the aid of the Arbitrary Lagrangian-Eulerian (ALE) method. The fluid-structure interaction, given by transient conditions, is realized by an iterative process. The developed method is applied to the simulation of the biomechanical problem containing the onset of the voice production.

Change Point Detection in Correlation Networks

NASA Astrophysics Data System (ADS)

Barnett, Ian; Onnela, Jukka-Pekka

2016-01-01

Many systems of interacting elements can be conceptualized as networks, where network nodes represent the elements and network ties represent interactions between the elements. In systems where the underlying network evolves, it is useful to determine the points in time where the network structure changes significantly as these may correspond to functional change points. We propose a method for detecting change points in correlation networks that, unlike previous change point detection methods designed for time series data, requires minimal distributional assumptions. We investigate the difficulty of change point detection near the boundaries of the time series in correlation networks and study the power of our method and competing methods through simulation. We also show the generalizable nature of the method by applying it to stock price data as well as fMRI data.
Kinetic Titration Series with Biolayer Interferometry

PubMed Central

Frenzel, Daniel; Willbold, Dieter

2014-01-01

Biolayer interferometry is a method to analyze protein interactions in real-time. In this study, we illustrate the usefulness to quantitatively analyze high affinity protein ligand interactions employing a kinetic titration series for characterizing the interactions between two pairs of interaction patterns, in particular immunoglobulin G and protein G B1 as well as scFv IC16 and amyloid beta (1–42). Kinetic titration series are commonly used in surface plasmon resonance and involve sequential injections of analyte over a desired concentration range on a single ligand coated sensor chip without waiting for complete dissociation between the injections. We show that applying this method to biolayer interferometry is straightforward and i) circumvents problems in data evaluation caused by unavoidable sensor differences, ii) saves resources and iii) increases throughput if screening a multitude of different analyte/ligand combinations. PMID:25229647
Kinetic titration series with biolayer interferometry.

PubMed

Frenzel, Daniel; Willbold, Dieter

2014-01-01

Biolayer interferometry is a method to analyze protein interactions in real-time. In this study, we illustrate the usefulness to quantitatively analyze high affinity protein ligand interactions employing a kinetic titration series for characterizing the interactions between two pairs of interaction patterns, in particular immunoglobulin G and protein G B1 as well as scFv IC16 and amyloid beta (1-42). Kinetic titration series are commonly used in surface plasmon resonance and involve sequential injections of analyte over a desired concentration range on a single ligand coated sensor chip without waiting for complete dissociation between the injections. We show that applying this method to biolayer interferometry is straightforward and i) circumvents problems in data evaluation caused by unavoidable sensor differences, ii) saves resources and iii) increases throughput if screening a multitude of different analyte/ligand combinations.
Pathway redundancy and protein essentiality revealed in the Saccharomyces cerevisiae interaction networks

PubMed Central

Ulitsky, Igor; Shamir, Ron

2007-01-01

The biological interpretation of genetic interactions is a major challenge. Recently, Kelley and Ideker proposed a method to analyze together genetic and physical networks, which explains many of the known genetic interactions as linking different pathways in the physical network. Here, we extend this method and devise novel analytic tools for interpreting genetic interactions in a physical context. Applying these tools on a large-scale Saccharomyces cerevisiae data set, our analysis reveals 140 between-pathway models that explain 3765 genetic interactions, roughly doubling those that were previously explained. Model genes tend to have short mRNA half-lives and many phosphorylation sites, suggesting that their stringent regulation is linked to pathway redundancy. We also identify ‘pivot' proteins that have many physical interactions with both pathways in our models, and show that pivots tend to be essential and highly conserved. Our analysis of models and pivots sheds light on the organization of the cellular machinery as well as on the roles of individual proteins. PMID:17437029
Interactive Acoustic Simulation in Urban and Complex Environments

DTIC Science & Technology

2015-03-21

and validity of the solution given by the two methods. Transfer functions are used to model two-way couplings to allow multiple orders of acoustic...Function ( BRDF )[79, 137]. The ray models have also been applied to inhomogeneous outdoor media by numerical integration of the differential ray...surface, the interaction can be modeled by specular reflection, Snell’s law refraction, or BRDF -based reflection, depending on the surface properties
Synergistic interaction between the fungus Beauveria bassiana and desiccant dusts applied against poultry red mites (Dermanyssus gallinae).

PubMed

Steenberg, Tove; Kilpinen, Ole

2014-04-01

The poultry red mite, Dermanyssus gallinae, is a major pest in egg production, feeding on laying hens. Widely used non-chemical control methods include desiccant dusts, although their persistence under field conditions is often short. Entomopathogenic fungi may also hold potential for mite control, but these fungi often take several days to kill mites. Laboratory experiments were carried out to study the efficacy of 3 types of desiccant dusts, the fungus Beauveria bassiana and combinations of the two control agents against D. gallinae. There was significant synergistic interaction between each of the desiccant dusts and the fungus, with observed levels of mite mortality significantly higher than those expected for an additive effect (up to 38 % higher). Synergistic interaction between desiccant dust and fungus was found also when different application methods were used for the fungus and at different levels of relative humidity. Although increased levels of mortality were reached due to the synergistic interaction, the speed of lethal action was not influenced by combining the two components. The persistence of the control agents applied separately or in combination did not change over a period of 4 weeks. Overall, combinations of desiccant dusts and fungus conidia seem to hold considerable promise for future non-chemical control of poultry red mites.
Applying dynamic Bayesian networks to perturbed gene expression data.

PubMed

Dojer, Norbert; Gambin, Anna; Mizera, Andrzej; Wilczyński, Bartek; Tiuryn, Jerzy

2006-05-08

A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics, allowing to deal with the stochastic aspects of gene expressions and noisy measurements in a natural way, Bayesian networks appear attractive in the field of inferring gene interactions structure from microarray experiments data. However, the basic formalism has some disadvantages, e.g. it is sometimes hard to distinguish between the origin and the target of an interaction. Two kinds of microarray experiments yield data particularly rich in information regarding the direction of interactions: time series and perturbation experiments. In order to correctly handle them, the basic formalism must be modified. For example, dynamic Bayesian networks (DBN) apply to time series microarray data. To our knowledge the DBN technique has not been applied in the context of perturbation experiments. We extend the framework of dynamic Bayesian networks in order to incorporate perturbations. Moreover, an exact algorithm for inferring an optimal network is proposed and a discretization method specialized for time series data from perturbation experiments is introduced. We apply our procedure to realistic simulations data. The results are compared with those obtained by standard DBN learning techniques. Moreover, the advantages of using exact learning algorithm instead of heuristic methods are analyzed. We show that the quality of inferred networks dramatically improves when using data from perturbation experiments. We also conclude that the exact algorithm should be used when it is possible, i.e. when considered set of genes is small enough.
Detecting Genetic Interactions for Quantitative Traits Using m-Spacing Entropy Measure

PubMed Central

Yee, Jaeyong; Kwon, Min-Seok; Park, Taesung; Park, Mira

2015-01-01

A number of statistical methods for detecting gene-gene interactions have been developed in genetic association studies with binary traits. However, many phenotype measures are intrinsically quantitative and categorizing continuous traits may not always be straightforward and meaningful. Association of gene-gene interactions with an observed distribution of such phenotypes needs to be investigated directly without categorization. Information gain based on entropy measure has previously been successful in identifying genetic associations with binary traits. We extend the usefulness of this information gain by proposing a nonparametric evaluation method of conditional entropy of a quantitative phenotype associated with a given genotype. Hence, the information gain can be obtained for any phenotype distribution. Because any functional form, such as Gaussian, is not assumed for the entire distribution of a trait or a given genotype, this method is expected to be robust enough to be applied to any phenotypic association data. Here, we show its use to successfully identify the main effect, as well as the genetic interactions, associated with a quantitative trait. PMID:26339620
Inferring Interaction Force from Visual Information without Using Physical Force Sensors.

PubMed

Hwang, Wonjun; Lim, Soo-Chul

2017-10-26

In this paper, we present an interaction force estimation method that uses visual information rather than that of a force sensor. Specifically, we propose a novel deep learning-based method utilizing only sequential images for estimating the interaction force against a target object, where the shape of the object is changed by an external force. The force applied to the target can be estimated by means of the visual shape changes. However, the shape differences in the images are not very clear. To address this problem, we formulate a recurrent neural network-based deep model with fully-connected layers, which models complex temporal dynamics from the visual representations. Extensive evaluations show that the proposed learning models successfully estimate the interaction forces using only the corresponding sequential images, in particular in the case of three objects made of different materials, a sponge, a PET bottle, a human arm, and a tube. The forces predicted by the proposed method are very similar to those measured by force sensors.
A Combinatorial Approach to Detecting Gene-Gene and Gene-Environment Interactions in Family Studies

PubMed Central

Lou, Xiang-Yang; Chen, Guo-Bo; Yan, Lei; Ma, Jennie Z.; Mangold, Jamie E.; Zhu, Jun; Elston, Robert C.; Li, Ming D.

2008-01-01

Widespread multifactor interactions present a significant challenge in determining risk factors of complex diseases. Several combinatorial approaches, such as the multifactor dimensionality reduction (MDR) method, have emerged as a promising tool for better detecting gene-gene (G × G) and gene-environment (G × E) interactions. We recently developed a general combinatorial approach, namely the generalized multifactor dimensionality reduction (GMDR) method, which can entertain both qualitative and quantitative phenotypes and allows for both discrete and continuous covariates to detect G × G and G × E interactions in a sample of unrelated individuals. In this article, we report the development of an algorithm that can be used to study G × G and G × E interactions for family-based designs, called pedigree-based GMDR (PGMDR). Compared to the available method, our proposed method has several major improvements, including allowing for covariate adjustments and being applicable to arbitrary phenotypes, arbitrary pedigree structures, and arbitrary patterns of missing marker genotypes. Our Monte Carlo simulations provide evidence that the PGMDR method is superior in performance to identify epistatic loci compared to the MDR-pedigree disequilibrium test (PDT). Finally, we applied our proposed approach to a genetic data set on tobacco dependence and found a significant interaction between two taste receptor genes (i.e., TAS2R16 and TAS2R38) in affecting nicotine dependence. PMID:18834969
A New Method, "Reverse Yeast Two-Hybrid Array" (RYTHA), Identifies Mutants that Dissociate the Physical Interaction Between Elg1 and Slx5.

PubMed

Lev, Ifat; Shemesh, Keren; Volpe, Marina; Sau, Soumitra; Levinton, Nelly; Molco, Maya; Singh, Shivani; Liefshitz, Batia; Ben Aroya, Shay; Kupiec, Martin

2017-07-01

The vast majority of processes within the cell are carried out by proteins working in conjunction. The Yeast Two-Hybrid (Y2H) methodology allows the detection of physical interactions between any two interacting proteins. Here, we describe a novel systematic genetic methodology, "Reverse Yeast Two-Hybrid Array" (RYTHA), that allows the identification of proteins required for modulating the physical interaction between two given proteins. Our assay starts with a yeast strain in which the physical interaction of interest can be detected by growth on media lacking histidine, in the context of the Y2H methodology. By combining the synthetic genetic array technology, we can systematically screen mutant libraries of the yeast Saccharomyces cerevisiae to identify trans -acting mutations that disrupt the physical interaction of interest. We apply this novel method in a screen for mutants that disrupt the interaction between the N-terminus of Elg1 and the Slx5 protein. Elg1 is part of an alternative replication factor C-like complex that unloads PCNA during DNA replication and repair. Slx5 forms, together with Slx8, a SUMO-targeted ubiquitin ligase (STUbL) believed to send proteins to degradation. Our results show that the interaction requires both the STUbL activity and the PCNA unloading by Elg1, and identify topoisomerase I DNA-protein cross-links as a major factor in separating the two activities. Thus, we demonstrate that RYTHA can be applied to gain insights about particular pathways in yeast, by uncovering the connection between the proteasomal ubiquitin-dependent degradation pathway, DNA replication, and repair machinery, which can be separated by the topoisomerase-mediated cross-links to DNA. Copyright © 2017 by the Genetics Society of America.
Exploring Dance Movement Data Using Sequence Alignment Methods

PubMed Central

Chavoshi, Seyed Hossein; De Baets, Bernard; Neutens, Tijs; De Tré, Guy; Van de Weghe, Nico

2015-01-01

Despite the abundance of research on knowledge discovery from moving object databases, only a limited number of studies have examined the interaction between moving point objects in space over time. This paper describes a novel approach for measuring similarity in the interaction between moving objects. The proposed approach consists of three steps. First, we transform movement data into sequences of successive qualitative relations based on the Qualitative Trajectory Calculus (QTC). Second, sequence alignment methods are applied to measure the similarity between movement sequences. Finally, movement sequences are grouped based on similarity by means of an agglomerative hierarchical clustering method. The applicability of this approach is tested using movement data from samba and tango dancers. PMID:26181435
Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering.

PubMed

Guo, Xuan; Meng, Yu; Yu, Ning; Pan, Yi

2014-04-10

Taking the advantage of high-throughput single nucleotide polymorphism (SNP) genotyping technology, large genome-wide association studies (GWASs) have been considered to hold promise for unravelling complex relationships between genotype and phenotype. At present, traditional single-locus-based methods are insufficient to detect interactions consisting of multiple-locus, which are broadly existing in complex traits. In addition, statistic tests for high order epistatic interactions with more than 2 SNPs propose computational and analytical challenges because the computation increases exponentially as the cardinality of SNPs combinations gets larger. In this paper, we provide a simple, fast and powerful method using dynamic clustering and cloud computing to detect genome-wide multi-locus epistatic interactions. We have constructed systematic experiments to compare powers performance against some recently proposed algorithms, including TEAM, SNPRuler, EDCF and BOOST. Furthermore, we have applied our method on two real GWAS datasets, Age-related macular degeneration (AMD) and Rheumatoid arthritis (RA) datasets, where we find some novel potential disease-related genetic factors which are not shown up in detections of 2-loci epistatic interactions. Experimental results on simulated data demonstrate that our method is more powerful than some recently proposed methods on both two- and three-locus disease models. Our method has discovered many novel high-order associations that are significantly enriched in cases from two real GWAS datasets. Moreover, the running time of the cloud implementation for our method on AMD dataset and RA dataset are roughly 2 hours and 50 hours on a cluster with forty small virtual machines for detecting two-locus interactions, respectively. Therefore, we believe that our method is suitable and effective for the full-scale analysis of multiple-locus epistatic interactions in GWAS.
Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering

PubMed Central

2014-01-01

Backgroud Taking the advan tage of high-throughput single nucleotide polymorphism (SNP) genotyping technology, large genome-wide association studies (GWASs) have been considered to hold promise for unravelling complex relationships between genotype and phenotype. At present, traditional single-locus-based methods are insufficient to detect interactions consisting of multiple-locus, which are broadly existing in complex traits. In addition, statistic tests for high order epistatic interactions with more than 2 SNPs propose computational and analytical challenges because the computation increases exponentially as the cardinality of SNPs combinations gets larger. Results In this paper, we provide a simple, fast and powerful method using dynamic clustering and cloud computing to detect genome-wide multi-locus epistatic interactions. We have constructed systematic experiments to compare powers performance against some recently proposed algorithms, including TEAM, SNPRuler, EDCF and BOOST. Furthermore, we have applied our method on two real GWAS datasets, Age-related macular degeneration (AMD) and Rheumatoid arthritis (RA) datasets, where we find some novel potential disease-related genetic factors which are not shown up in detections of 2-loci epistatic interactions. Conclusions Experimental results on simulated data demonstrate that our method is more powerful than some recently proposed methods on both two- and three-locus disease models. Our method has discovered many novel high-order associations that are significantly enriched in cases from two real GWAS datasets. Moreover, the running time of the cloud implementation for our method on AMD dataset and RA dataset are roughly 2 hours and 50 hours on a cluster with forty small virtual machines for detecting two-locus interactions, respectively. Therefore, we believe that our method is suitable and effective for the full-scale analysis of multiple-locus epistatic interactions in GWAS. PMID:24717145
Adult Learning Principles and Presentation Pearls

PubMed Central

Palis, Ana G.; Quiros, Peter A.

2014-01-01

Although lectures are one of the most common methods of knowledge transfer in medicine, their effectiveness has been questioned. Passive formats, lack of relevance and disconnection from the student's needs are some of the arguments supporting this apparent lack of efficacy. However, many authors have suggested that applying adult learning principles (i.e., relevance, congruence with student's needs, interactivity, connection to student's previous knowledge and experience) to this method increases learning by lectures and the effectiveness of lectures. This paper presents recommendations for applying adult learning principles during planning, creation and development of lectures to make them more effective. PMID:24791101
A Kernel Machine Method for Detecting Effects of Interaction Between Multidimensional Variable Sets: An Imaging Genetics Application

PubMed Central

Ge, Tian; Nichols, Thomas E.; Ghosh, Debashis; Mormino, Elizabeth C.

2015-01-01

Measurements derived from neuroimaging data can serve as markers of disease and/or healthy development, are largely heritable, and have been increasingly utilized as (intermediate) phenotypes in genetic association studies. To date, imaging genetic studies have mostly focused on discovering isolated genetic effects, typically ignoring potential interactions with non-genetic variables such as disease risk factors, environmental exposures, and epigenetic markers. However, identifying significant interaction effects is critical for revealing the true relationship between genetic and phenotypic variables, and shedding light on disease mechanisms. In this paper, we present a general kernel machine based method for detecting effects of interaction between multidimensional variable sets. This method can model the joint and epistatic effect of a collection of single nucleotide polymorphisms (SNPs), accommodate multiple factors that potentially moderate genetic influences, and test for nonlinear interactions between sets of variables in a flexible framework. As a demonstration of application, we applied the method to data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to detect the effects of the interactions between candidate Alzheimer's disease (AD) risk genes and a collection of cardiovascular disease (CVD) risk factors, on hippocampal volume measurements derived from structural brain magnetic resonance imaging (MRI) scans. Our method identified that two genes, CR1 and EPHA1, demonstrate significant interactions with CVD risk factors on hippocampal volume, suggesting that CR1 and EPHA1 may play a role in influencing AD-related neurodegeneration in the presence of CVD risks. PMID:25600633
An interacting boundary layer model for cascades

NASA Technical Reports Server (NTRS)

Davis, R. T.; Rothmayer, A. P.

1983-01-01

A laminar, incompressible interacting boundary layer model is developed for two-dimensional cascades. In the limit of large cascade spacing these equations reduce to the interacting boundary layer equations for a single body immersed in an infinite stream. A fully implicit numerical method is used to solve the governing equations, and is found to be at least as efficient as the same technique applied to the single body problem. Solutions are then presented for a cascade of finite flat plates and a cascade of finite sine-waves, with cusped leading and trailing edges.
An interactive program on digitizing historical seismograms

NASA Astrophysics Data System (ADS)

Xu, Yihe; Xu, Tao

2014-02-01

Retrieving information from analog seismograms is of great importance since they are considered as the unique sources that provide quantitative information of historical earthquakes. We present an algorithm for automatic digitization of the seismograms as an inversion problem that forms an interactive program using Matlab® GUI. The program integrates automatic digitization with manual digitization and users can easily switch between the two modalities and carry out different combinations for the optimal results. Several examples about applying the interactive program are given to illustrate the merits of the method.
Macroscopic Lagrangian description of warm plasmas. II Nonlinear wave interactions

NASA Technical Reports Server (NTRS)

Kim, H.; Crawford, F. W.

1983-01-01

A macroscopic Lagrangian is simplified to the adiabatic limit and expanded about equilibrium, to third order in perturbation, for three illustrative cases: one-dimensional compression parallel to the static magnetic field, two-dimensional compression perpendicular to the static magnetic field, and three-dimensional compression. As examples of the averaged-Lagrangian method applied to nonlinear wave interactions, coupling coefficients are derived for interactions between two electron plasma waves and an ion acoustic wave, and between an ordinary wave, an electron plasma wave, and an ion acoustic wave.
Application of multi-factorial design of experiments to successfully optimize immunoassays for robust measurements of therapeutic proteins.

PubMed

Ray, Chad A; Patel, Vimal; Shih, Judy; Macaraeg, Chris; Wu, Yuling; Thway, Theingi; Ma, Mark; Lee, Jean W; Desilva, Binodh

2009-02-20

Developing a process that generates robust immunoassays that can be used to support studies with tight timelines is a common challenge for bioanalytical laboratories. Design of experiments (DOEs) is a tool that has been used by many industries for the purpose of optimizing processes. The approach is capable of identifying critical factors and their interactions with a minimal number of experiments. The challenge for implementing this tool in the bioanalytical laboratory is to develop a user-friendly approach that scientists can understand and apply. We have successfully addressed these challenges by eliminating the screening design, introducing automation, and applying a simple mathematical approach for the output parameter. A modified central composite design (CCD) was applied to three ligand binding assays. The intra-plate factors selected were coating, detection antibody concentration, and streptavidin-HRP concentrations. The inter-plate factors included incubation times for each step. The objective was to maximize the logS/B (S/B) of the low standard to the blank. The maximum desirable conditions were determined using JMP 7.0. To verify the validity of the predictions, the logS/B prediction was compared against the observed logS/B during pre-study validation experiments. The three assays were optimized using the multi-factorial DOE. The total error for all three methods was less than 20% which indicated method robustness. DOE identified interactions in one of the methods. The model predictions for logS/B were within 25% of the observed pre-study validation values for all methods tested. The comparison between the CCD and hybrid screening design yielded comparable parameter estimates. The user-friendly design enables effective application of multi-factorial DOE to optimize ligand binding assays for therapeutic proteins. The approach allows for identification of interactions between factors, consistency in optimal parameter determination, and reduced method development time.

Template-free electrochemical nanofabrication of polyaniline nanobrush and hybrid polyaniline with carbon nanohorns for supercapacitors.

PubMed

Wei, Di; Wang, Haolan; Hiralal, Pritesh; Andrew, Piers; Ryhänen, Tapani; Hayashi, Yasuhiko; Amaratunga, Gehan A J

2010-10-29

Polyaniline (PANI) nanobrushes were synthesized by template-free electrochemical galvanostatic methods. When the same method was applied to the carbon nanohorn (CNH) solution containing aniline monomers, a hybrid nanostructure containing PANI and CNHs was enabled after electropolymerization. This is the first report on the template-free method to make PANI nanobrushes and homogeneous hybrid soft matter (PANI) with carbon nanoparticles. Raman spectroscopy was used to analyze the interaction between CNH and PANI. Electrochemical nanofabrication offers simplicity and good control when used to make electronic devices. Both of these materials were applied in supercapacitors and an improvement capacitive current by using the hybrid material was observed.
Template-free electrochemical nanofabrication of polyaniline nanobrush and hybrid polyaniline with carbon nanohorns for supercapacitors

NASA Astrophysics Data System (ADS)

Wei, Di; Wang, Haolan; Hiralal, Pritesh; Andrew, Piers; Ryhänen, Tapani; Hayashi, Yasuhiko; Amaratunga, Gehan A. J.

2010-10-01

Polyaniline (PANI) nanobrushes were synthesized by template-free electrochemical galvanostatic methods. When the same method was applied to the carbon nanohorn (CNH) solution containing aniline monomers, a hybrid nanostructure containing PANI and CNHs was enabled after electropolymerization. This is the first report on the template-free method to make PANI nanobrushes and homogeneous hybrid soft matter (PANI) with carbon nanoparticles. Raman spectroscopy was used to analyze the interaction between CNH and PANI. Electrochemical nanofabrication offers simplicity and good control when used to make electronic devices. Both of these materials were applied in supercapacitors and an improvement capacitive current by using the hybrid material was observed.
Flux splitting algorithms for two-dimensional viscous flows with finite-rate chemistry

NASA Technical Reports Server (NTRS)

Shuen, Jian-Shun; Liou, Meng-Sing

1989-01-01

The Roe flux difference splitting method was extended to treat 2-D viscous flows with nonequilibrium chemistry. The derivations have avoided unnecessary assumptions or approximations. For spatial discretization, the second-order Roe upwind differencing is used for the convective terms and central differencing for the viscous terms. An upwind-based TVD scheme is applied to eliminate oscillations and obtain a sharp representation of discontinuities. A two-state Runge-Kutta method is used to time integrate the discretized Navier-Stokes and species transport equations for the asymptotic steady solutions. The present method is then applied to two types of flows: the shock wave/boundary layer interaction problems and the jet in cross flows.
Flux splitting algorithms for two-dimensional viscous flows with finite-rate chemistry

NASA Technical Reports Server (NTRS)

Shuen, Jian-Shun; Liou, Meng-Sing

1989-01-01

The Roe flux-difference splitting method has been extended to treat two-dimensional viscous flows with nonequilibrium chemistry. The derivations have avoided unnecessary assumptions or approximations. For spatial discretization, the second-order Roe upwind differencing is used for the convective terms and central differencing for the viscous terms. An upwind-based TVD scheme is applied to eliminate oscillations and obtain a sharp representation of discontinuities. A two-stage Runge-Kutta method is used to time integrate the discretized Navier-Stokes and species transport equations for the asymptotic steady solutions. The present method is then applied to two types of flows: the shock wave/boundary layer interaction problems and the jet in cross flows.
Explicit and exact nontraveling wave solutions of the (3+1)-dimensional potential Yu-Toda-Sasa-Fukuyama equation

NASA Astrophysics Data System (ADS)

Yuan, Na

2018-04-01

With the aid of the symbolic computation, we present an improved ( G ‧ / G ) -expansion method, which can be applied to seek more types of exact solutions for certain nonlinear evolution equations. In illustration, we choose the (3 + 1)-dimensional potential Yu-Toda-Sasa-Fukuyama equation to demonstrate the validity and advantages of the method. As a result, abundant explicit and exact nontraveling wave solutions are obtained including two solitary waves solutions, nontraveling wave solutions and dromion soliton solutions. Some particular localized excitations and the interactions between two solitary waves are researched. The method can be also applied to other nonlinear partial differential equations.
Interaction energies for the purine inhibitor roscovitine with cyclin-dependent kinase 2: correlated ab initio quantum-chemical, DFT and empirical calculations.

PubMed

Dobes, Petr; Otyepka, Michal; Strnad, Miroslav; Hobza, Pavel

2006-05-24

The interaction between roscovitine and cyclin-dependent kinase 2 (cdk2) was investigated by performing correlated ab initio quantum-chemical calculations. The whole protein was fragmented into smaller systems consisting of one or a few amino acids, and the interaction energies of these fragments with roscovitine were determined by using the MP2 method with the extended aug-cc-pVDZ basis set. For selected complexes, the complete basis set limit MP2 interaction energies, as well as the coupled-cluster corrections with inclusion of single, double and noninteractive triples contributions [CCSD(T)], were also evaluated. The energies of interaction between roscovitine and small fragments and between roscovitine and substantial sections of protein (722 atoms) were also computed by using density-functional tight-binding methods covering dispersion energy (DFTB-D) and the Cornell empirical potential. Total stabilisation energy originates predominantly from dispersion energy and methods that do not account for the dispersion energy cannot, therefore, be recommended for the study of protein-inhibitor interactions. The Cornell empirical potential describes reasonably well the interaction between roscovitine and protein; therefore, this method can be applied in future thermodynamic calculations. A limited number of amino acid residues contribute significantly to the binding of roscovitine and cdk2, whereas a rather large number of amino acids make a negligible contribution.
Dictionaries and distributions: Combining expert knowledge and large scale textual data content analysis : Distributed dictionary representation.

PubMed

Garten, Justin; Hoover, Joe; Johnson, Kate M; Boghrati, Reihane; Iskiwitch, Carol; Dehghani, Morteza

2018-02-01

Theory-driven text analysis has made extensive use of psychological concept dictionaries, leading to a wide range of important results. These dictionaries have generally been applied through word count methods which have proven to be both simple and effective. In this paper, we introduce Distributed Dictionary Representations (DDR), a method that applies psychological dictionaries using semantic similarity rather than word counts. This allows for the measurement of the similarity between dictionaries and spans of text ranging from complete documents to individual words. We show how DDR enables dictionary authors to place greater emphasis on construct validity without sacrificing linguistic coverage. We further demonstrate the benefits of DDR on two real-world tasks and finally conduct an extensive study of the interaction between dictionary size and task performance. These studies allow us to examine how DDR and word count methods complement one another as tools for applying concept dictionaries and where each is best applied. Finally, we provide references to tools and resources to make this method both available and accessible to a broad psychological audience.
A method to assess how interactive water simulation tools influence transdisciplinary decision-making processes in water management

NASA Astrophysics Data System (ADS)

Leskens, Johannes

2015-04-01

In modern water management, often transdisciplinary work sessions are organized in which various stakeholders participate to jointly define problems, choose measures and divide responsibilities to take actions. Involved stakeholders are for example policy analysts or decision-makers from municipalities, water boards or provinces, representatives of pressure groups and researchers from knowledge institutes. Parallel to this increasing attention for transdisciplinary work sessions, we see a growing availability of interactive IT-tools that can be applied during these sessions. For example, dynamic flood risk maps have become recently available that allow users during a work sessions to instantaneously assess the impact of storm surges or dam breaches, displayed on digital maps. Other examples are serious games, realistic visualizations and participatory simulations. However, the question is if and how these interactive IT-tools contribute to better decision-making. To assess this, we take the process of knowledge construction during a work session as a measure for the quality of decision-making. Knowledge construction can be defined as the process in which ideas, perspectives and opinions of different stakeholders, all having their own expertise and experience, are confronted with each other and new shared meanings towards water management issues are created. We present an assessment method to monitor the process of knowledge construction during work sessions in water management in which interactive IT tools are being used. The assessment method is based on a literature review, focusing on studies in which knowledge construction was monitored in other contexts that water management. To test the applicability of the assessment method, we applied it during a multi-stakeholder work session in Westland, located in the southwest of the Netherlands. The discussions during the work session were observed by camera. All statements, expressed by the various members of a stakeholder session, were classified according to our assessment method. We can draw the following preliminary conclusions. First, the case study showed that the method was useful to show the knowledge construction process over time, in terms of content and cognitive level of statements and interaction, attention and response between stakeholders. It was observed that the various aspects of knowledge construction all were influenced by the use of the 3Di model. The model focused discussions on technical issues of flood risk management, non-flood specialists were able to participate in discussions and in suggesting solutions and more topics could be evaluated in respect to non-interactive flood maps. Second, the method is considered useful as a benchmark for different interactive IT tools. The method is also considered useful to gain insight in how to optimally set-up multi-stakeholder meetings in which interactive IT-tools are being used. Further, the method can provide model developers insight in how to better meet the technical requirements of interactive IT tools to support the knowledge construction process during multi-stakeholder meeting
Perspectives on the simulation of protein–surface interactions using empirical force field methods

PubMed Central

Latour, Robert A.

2014-01-01

Protein–surface interactions are of fundamental importance for a broad range of applications in the fields of biomaterials and biotechnology. Present experimental methods are limited in their ability to provide a comprehensive depiction of these interactions at the atomistic level. In contrast, empirical force field based simulation methods inherently provide the ability to predict and visualize protein–surface interactions with full atomistic detail. These methods, however, must be carefully developed, validated, and properly applied before confidence can be placed in results from the simulations. In this perspectives paper, I provide an overview of the critical aspects that I consider being of greatest importance for the development of these methods, with a focus on the research that my combined experimental and molecular simulation groups have conducted over the past decade to address these issues. These critical issues include the tuning of interfacial force field parameters to accurately represent the thermodynamics of interfacial behavior, adequate sampling of these types of complex molecular systems to generate results that can be comparable with experimental data, and the generation of experimental data that can be used for simulation results evaluation and validation. PMID:25028242
A Statistical Method of Identifying Interactions in Neuron–Glia Systems Based on Functional Multicell Ca2+ Imaging

PubMed Central

Nakae, Ken; Ikegaya, Yuji; Ishikawa, Tomoe; Oba, Shigeyuki; Urakubo, Hidetoshi; Koyama, Masanori; Ishii, Shin

2014-01-01

Crosstalk between neurons and glia may constitute a significant part of information processing in the brain. We present a novel method of statistically identifying interactions in a neuron–glia network. We attempted to identify neuron–glia interactions from neuronal and glial activities via maximum-a-posteriori (MAP)-based parameter estimation by developing a generalized linear model (GLM) of a neuron–glia network. The interactions in our interest included functional connectivity and response functions. We evaluated the cross-validated likelihood of GLMs that resulted from the addition or removal of connections to confirm the existence of specific neuron-to-glia or glia-to-neuron connections. We only accepted addition or removal when the modification improved the cross-validated likelihood. We applied the method to a high-throughput, multicellular in vitro Ca2+ imaging dataset obtained from the CA3 region of a rat hippocampus, and then evaluated the reliability of connectivity estimates using a statistical test based on a surrogate method. Our findings based on the estimated connectivity were in good agreement with currently available physiological knowledge, suggesting our method can elucidate undiscovered functions of neuron–glia systems. PMID:25393874
Quantum dynamics modeled by interacting trajectories

NASA Astrophysics Data System (ADS)

Cruz-Rodríguez, L.; Uranga-Piña, L.; Martínez-Mesa, A.; Meier, C.

2018-03-01

We present quantum dynamical simulations based on the propagation of interacting trajectories where the effect of the quantum potential is mimicked by effective pseudo-particle interactions. The method is applied to several quantum systems, both for bound and scattering problems. For the bound systems, the quantum ground state density and zero point energy are shown to be perfectly obtained by the interacting trajectories. In the case of time-dependent quantum scattering, the Eckart barrier and uphill ramp are considered, with transmission coefficients in very good agreement with standard quantum calculations. Finally, we show that via wave function synthesis along the trajectories, correlation functions and energy spectra can be obtained based on the dynamics of interacting trajectories.
VISUAL DATA MINING IN ATMOSPHERIC SCIENCE DATA

EPA Science Inventory

This paper discusses the use of simple visual tools to explore multivariate spatially-referenced data. It describes interactive approaches such as linked brushing, and dynamic methods such as the grand tour. applied to studying the Comprehensive Ocean-Atmosphere Data Set (COADS)....
Prediction of molecular crystal structures by a crystallographic QM/MM model with full space-group symmetry.

PubMed

Mörschel, Philipp; Schmidt, Martin U

2015-01-01

A crystallographic quantum-mechanical/molecular-mechanical model (c-QM/MM model) with full space-group symmetry has been developed for molecular crystals. The lattice energy was calculated by quantum-mechanical methods for short-range interactions and force-field methods for long-range interactions. The quantum-mechanical calculations covered the interactions within the molecule and the interactions of a reference molecule with each of the surrounding 12-15 molecules. The interactions with all other molecules were treated by force-field methods. In each optimization step the energies in the QM and MM shells were calculated separately as single-point energies; after adding both energy contributions, the crystal structure (including the lattice parameters) was optimized accordingly. The space-group symmetry was maintained throughout. Crystal structures with more than one molecule per asymmetric unit, e.g. structures with Z' = 2, hydrates and solvates, have been optimized as well. Test calculations with different quantum-mechanical methods on nine small organic molecules revealed that the density functional theory methods with dispersion correction using the B97-D functional with 6-31G* basis set in combination with the DREIDING force field reproduced the experimental crystal structures with good accuracy. Subsequently the c-QM/MM method was applied to nine compounds from the CCDC blind tests resulting in good energy rankings and excellent geometric accuracies.
Using the surface panel method to predict the steady performance of ducted propellers

NASA Astrophysics Data System (ADS)

Cai, Hao-Peng; Su, Yu-Min; Li, Xin; Shen, Hai-Long

2009-12-01

A new numerical method was developed for predicting the steady hydrodynamic performance of ducted propellers. A potential based surface panel method was applied both to the duct and the propeller, and the interaction between them was solved by an induced velocity potential iterative method. Compared with the induced velocity iterative method, the method presented can save programming and calculating time. Numerical results for a JD simplified ducted propeller series showed that the method presented is effective for predicting the steady hydrodynamic performance of ducted propellers.
Exploring pathway interactions in insulin resistant mouse liver

PubMed Central

2011-01-01

Background Complex phenotypes such as insulin resistance involve different biological pathways that may interact and influence each other. Interpretation of related experimental data would be facilitated by identifying relevant pathway interactions in the context of the dataset. Results We developed an analysis approach to study interactions between pathways by integrating gene and protein interaction networks, biological pathway information and high-throughput data. This approach was applied to a transcriptomics dataset to investigate pathway interactions in insulin resistant mouse liver in response to a glucose challenge. We identified regulated pathway interactions at different time points following the glucose challenge and also studied the underlying protein interactions to find possible mechanisms and key proteins involved in pathway cross-talk. A large number of pathway interactions were found for the comparison between the two diet groups at t = 0. The initial response to the glucose challenge (t = 0.6) was typed by an acute stress response and pathway interactions showed large overlap between the two diet groups, while the pathway interaction networks for the late response were more dissimilar. Conclusions Studying pathway interactions provides a new perspective on the data that complements established pathway analysis methods such as enrichment analysis. This study provided new insights in how interactions between pathways may be affected by insulin resistance. In addition, the analysis approach described here can be generally applied to different types of high-throughput data and will therefore be useful for analysis of other complex datasets as well. PMID:21843341
Mapping the ecological networks of microbial communities.

PubMed

Xiao, Yandong; Angulo, Marco Tulio; Friedman, Jonathan; Waldor, Matthew K; Weiss, Scott T; Liu, Yang-Yu

2017-12-11

Mapping the ecological networks of microbial communities is a necessary step toward understanding their assembly rules and predicting their temporal behavior. However, existing methods require assuming a particular population dynamics model, which is not known a priori. Moreover, those methods require fitting longitudinal abundance data, which are often not informative enough for reliable inference. To overcome these limitations, here we develop a new method based on steady-state abundance data. Our method can infer the network topology and inter-taxa interaction types without assuming any particular population dynamics model. Additionally, when the population dynamics is assumed to follow the classic Generalized Lotka-Volterra model, our method can infer the inter-taxa interaction strengths and intrinsic growth rates. We systematically validate our method using simulated data, and then apply it to four experimental data sets. Our method represents a key step towards reliable modeling of complex, real-world microbial communities, such as the human gut microbiota.
Viral Disease Networks?

NASA Astrophysics Data System (ADS)

Gulbahce, Natali; Yan, Han; Vidal, Marc; Barabasi, Albert-Laszlo

2010-03-01

Viral infections induce multiple perturbations that spread along the links of the biological networks of the host cells. Understanding the impact of these cascading perturbations requires an exhaustive knowledge of the cellular machinery as well as a systems biology approach that reveals how individual components of the cellular system function together. Here we describe an integrative method that provides a new approach to studying virus-human interactions and its correlations with diseases. Our method involves the combined utilization of protein - protein interactions, protein -- DNA interactions, metabolomics and gene - disease associations to build a ``viraldiseasome''. By solely using high-throughput data, we map well-known viral associated diseases and predict new candidate viral diseases. We use microarray data of virus-infected tissues and patient medical history data to further test the implications of the viral diseasome. We apply this method to Epstein-Barr virus and Human Papillomavirus and shed light into molecular development of viral diseases and disease pathways.
Risk Factors of Falls in Community-Dwelling Older Adults: Logistic Regression Tree Analysis

ERIC Educational Resources Information Center

Yamashita, Takashi; Noe, Douglas A.; Bailer, A. John

2012-01-01

Purpose of the Study: A novel logistic regression tree-based method was applied to identify fall risk factors and possible interaction effects of those risk factors. Design and Methods: A nationally representative sample of American older adults aged 65 years and older (N = 9,592) in the Health and Retirement Study 2004 and 2006 modules was used.…
Drug-target interaction prediction using ensemble learning and dimensionality reduction.

PubMed

Ezzat, Ali; Wu, Min; Li, Xiao-Li; Kwoh, Chee-Keong

2017-10-01

Experimental prediction of drug-target interactions is expensive, time-consuming and tedious. Fortunately, computational methods help narrow down the search space for interaction candidates to be further examined via wet-lab techniques. Nowadays, the number of attributes/features for drugs and targets, as well as the amount of their interactions, are increasing, making these computational methods inefficient or occasionally prohibitive. This motivates us to derive a reduced feature set for prediction. In addition, since ensemble learning techniques are widely used to improve the classification performance, it is also worthwhile to design an ensemble learning framework to enhance the performance for drug-target interaction prediction. In this paper, we propose a framework for drug-target interaction prediction leveraging both feature dimensionality reduction and ensemble learning. First, we conducted feature subspacing to inject diversity into the classifier ensemble. Second, we applied three different dimensionality reduction methods to the subspaced features. Third, we trained homogeneous base learners with the reduced features and then aggregated their scores to derive the final predictions. For base learners, we selected two classifiers, namely Decision Tree and Kernel Ridge Regression, resulting in two variants of ensemble models, EnsemDT and EnsemKRR, respectively. In our experiments, we utilized AUC (Area under ROC Curve) as an evaluation metric. We compared our proposed methods with various state-of-the-art methods under 5-fold cross validation. Experimental results showed EnsemKRR achieving the highest AUC (94.3%) for predicting drug-target interactions. In addition, dimensionality reduction helped improve the performance of EnsemDT. In conclusion, our proposed methods produced significant improvements for drug-target interaction prediction. Copyright © 2017 Elsevier Inc. All rights reserved.
Semiempirical Quantum Mechanical Methods for Noncovalent Interactions for Chemical and Biochemical Applications

PubMed Central

2016-01-01

Semiempirical (SE) methods can be derived from either Hartree–Fock or density functional theory by applying systematic approximations, leading to efficient computational schemes that are several orders of magnitude faster than ab initio calculations. Such numerical efficiency, in combination with modern computational facilities and linear scaling algorithms, allows application of SE methods to very large molecular systems with extensive conformational sampling. To reliably model the structure, dynamics, and reactivity of biological and other soft matter systems, however, good accuracy for the description of noncovalent interactions is required. In this review, we analyze popular SE approaches in terms of their ability to model noncovalent interactions, especially in the context of describing biomolecules, water solution, and organic materials. We discuss the most significant errors and proposed correction schemes, and we review their performance using standard test sets of molecular systems for quantum chemical methods and several recent applications. The general goal is to highlight both the value and limitations of SE methods and stimulate further developments that allow them to effectively complement ab initio methods in the analysis of complex molecular systems. PMID:27074247

Computational design of protein interactions: designing proteins that neutralize influenza by inhibiting its hemagglutinin surface protein

NASA Astrophysics Data System (ADS)

Fleishman, Sarel

2012-02-01

Molecular recognition underlies all life processes. Design of interactions not seen in nature is a test of our understanding of molecular recognition and could unlock the vast potential of subtle control over molecular interaction networks, allowing the design of novel diagnostics and therapeutics for basic and applied research. We developed the first general method for designing protein interactions. The method starts by computing a region of high affinity interactions between dismembered amino acid residues and the target surface and then identifying proteins that can harbor these residues. Designs are tested experimentally for binding the target surface and successful ones are affinity matured using yeast cell surface display. Applied to the conserved stem region of influenza hemagglutinin we designed two unrelated proteins that, following affinity maturation, bound hemagglutinin at subnanomolar dissociation constants. Co-crystal structures of hemagglutinin bound to the two designed binders were within 1Angstrom RMSd of their models, validating the accuracy of the design strategy. One of the designed proteins inhibits the conformational changes that underlie hemagglutinin's cell-invasion functions and blocks virus infectivity in cell culture, suggesting that such proteins may in future serve as diagnostics and antivirals against a wide range of pathogenic influenza strains. We have used this method to obtain experimentally validated binders of several other target proteins, demonstrating the generality of the approach. We discuss the combination of modeling and high-throughput characterization of design variants which has been key to the success of this approach, as well as how we have used the data obtained in this project to enhance our understanding of molecular recognition. References: Science 332:816 JMB, in press Protein Sci 20:753
Development and application of a DNA microarray-based yeast two-hybrid system

PubMed Central

Suter, Bernhard; Fontaine, Jean-Fred; Yildirimman, Reha; Raskó, Tamás; Schaefer, Martin H.; Rasche, Axel; Porras, Pablo; Vázquez-Álvarez, Blanca M.; Russ, Jenny; Rau, Kirstin; Foulle, Raphaele; Zenkner, Martina; Saar, Kathrin; Herwig, Ralf; Andrade-Navarro, Miguel A.; Wanker, Erich E.

2013-01-01

The yeast two-hybrid (Y2H) system is the most widely applied methodology for systematic protein–protein interaction (PPI) screening and the generation of comprehensive interaction networks. We developed a novel Y2H interaction screening procedure using DNA microarrays for high-throughput quantitative PPI detection. Applying a global pooling and selection scheme to a large collection of human open reading frames, proof-of-principle Y2H interaction screens were performed for the human neurodegenerative disease proteins huntingtin and ataxin-1. Using systematic controls for unspecific Y2H results and quantitative benchmarking, we identified and scored a large number of known and novel partner proteins for both huntingtin and ataxin-1. Moreover, we show that this parallelized screening procedure and the global inspection of Y2H interaction data are uniquely suited to define specific PPI patterns and their alteration by disease-causing mutations in huntingtin and ataxin-1. This approach takes advantage of the specificity and flexibility of DNA microarrays and of the existence of solid-related statistical methods for the analysis of DNA microarray data, and allows a quantitative approach toward interaction screens in human and in model organisms. PMID:23275563
Evolutionary Influenced Interaction Pattern as Indicator for the Investigation of Natural Variants Causing Nephrogenic Diabetes Insipidus

PubMed Central

Labudde, Dirk

2015-01-01

The importance of short membrane sequence motifs has been shown in many works and emphasizes the related sequence motif analysis. Together with specific transmembrane helix-helix interactions, the analysis of interacting sequence parts is helpful for understanding the process during membrane protein folding and in retaining the three-dimensional fold. Here we present a simple high-throughput analysis method for deriving mutational information of interacting sequence parts. Applied on aquaporin water channel proteins, our approach supports the analysis of mutational variants within different interacting subsequences and finally the investigation of natural variants which cause diseases like, for example, nephrogenic diabetes insipidus. In this work we demonstrate a simple method for massive membrane protein data analysis. As shown, the presented in silico analyses provide information about interacting sequence parts which are constrained by protein evolution. We present a simple graphical visualization medium for the representation of evolutionary influenced interaction pattern pairs (EIPPs) adapted to mutagen investigations of aquaporin-2, a protein whose mutants are involved in the rare endocrine disorder known as nephrogenic diabetes insipidus, and membrane proteins in general. Furthermore, we present a new method to derive new evolutionary variations within EIPPs which can be used for further mutagen laboratory investigations. PMID:26180540
Evolutionary Influenced Interaction Pattern as Indicator for the Investigation of Natural Variants Causing Nephrogenic Diabetes Insipidus.

PubMed

Grunert, Steffen; Labudde, Dirk

2015-01-01

The importance of short membrane sequence motifs has been shown in many works and emphasizes the related sequence motif analysis. Together with specific transmembrane helix-helix interactions, the analysis of interacting sequence parts is helpful for understanding the process during membrane protein folding and in retaining the three-dimensional fold. Here we present a simple high-throughput analysis method for deriving mutational information of interacting sequence parts. Applied on aquaporin water channel proteins, our approach supports the analysis of mutational variants within different interacting subsequences and finally the investigation of natural variants which cause diseases like, for example, nephrogenic diabetes insipidus. In this work we demonstrate a simple method for massive membrane protein data analysis. As shown, the presented in silico analyses provide information about interacting sequence parts which are constrained by protein evolution. We present a simple graphical visualization medium for the representation of evolutionary influenced interaction pattern pairs (EIPPs) adapted to mutagen investigations of aquaporin-2, a protein whose mutants are involved in the rare endocrine disorder known as nephrogenic diabetes insipidus, and membrane proteins in general. Furthermore, we present a new method to derive new evolutionary variations within EIPPs which can be used for further mutagen laboratory investigations.
Correlation filtering in financial time series (Invited Paper)

NASA Astrophysics Data System (ADS)

Aste, T.; Di Matteo, Tiziana; Tumminello, M.; Mantegna, R. N.

2005-05-01

We apply a method to filter relevant information from the correlation coefficient matrix by extracting a network of relevant interactions. This method succeeds to generate networks with the same hierarchical structure of the Minimum Spanning Tree but containing a larger amount of links resulting in a richer network topology allowing loops and cliques. In Tumminello et al.,1 we have shown that this method, applied to a financial portfolio of 100 stocks in the USA equity markets, is pretty efficient in filtering relevant information about the clustering of the system and its hierarchical structure both on the whole system and within each cluster. In particular, we have found that triangular loops and 4 element cliques have important and significant relations with the market structure and properties. Here we apply this filtering procedure to the analysis of correlation in two different kind of interest rate time series (16 Eurodollars and 34 US interest rates).
Robust cooperation of connected vehicle systems with eigenvalue-bounded interaction topologies in the presence of uncertain dynamics

NASA Astrophysics Data System (ADS)

Li, Keqiang; Gao, Feng; Li, Shengbo Eben; Zheng, Yang; Gao, Hongbo

2017-12-01

This study presents a distributed H-infinity control method for uncertain platoons with dimensionally and structurally unknown interaction topologies provided that the associated topological eigenvalues are bounded by a predesigned range.With an inverse model to compensate for nonlinear powertrain dynamics, vehicles in a platoon are modeled by third-order uncertain systems with bounded disturbances. On the basis of the eigenvalue decomposition of topological matrices, we convert the platoon system to a norm-bounded uncertain part and a diagonally structured certain part by applying linear transformation. We then use a common Lyapunov method to design a distributed H-infinity controller. Numerically, two linear matrix inequalities corresponding to the minimum and maximum eigenvalues should be solved. The resulting controller can tolerate interaction topologies with eigenvalues located in a certain range. The proposed method can also ensure robustness performance and disturbance attenuation ability for the closed-loop platoon system. Hardware-in-the-loop tests are performed to validate the effectiveness of our method.
A Method for Predicting Protein Complexes from Dynamic Weighted Protein-Protein Interaction Networks.

PubMed

Liu, Lizhen; Sun, Xiaowu; Song, Wei; Du, Chao

2018-06-01

Predicting protein complexes from protein-protein interaction (PPI) network is of great significance to recognize the structure and function of cells. A protein may interact with different proteins under different time or conditions. Existing approaches only utilize static PPI network data that may lose much temporal biological information. First, this article proposed a novel method that combines gene expression data at different time points with traditional static PPI network to construct different dynamic subnetworks. Second, to further filter out the data noise, the semantic similarity based on gene ontology is regarded as the network weight together with the principal component analysis, which is introduced to deal with the weight computing by three traditional methods. Third, after building a dynamic PPI network, a predicting protein complexes algorithm based on "core-attachment" structural feature is applied to detect complexes from each dynamic subnetworks. Finally, it is revealed from the experimental results that our method proposed in this article performs well on detecting protein complexes from dynamic weighted PPI networks.
Explanation-based generalization of partially ordered plans

NASA Technical Reports Server (NTRS)

Kambhampati, Subbarao; Kedar, Smadar

1991-01-01

Most previous work in analytic generalization of plans dealt with totally ordered plans. These methods cannot be directly applied to generalizing partially ordered plans, since they do not capture all interactions among plan operators for all total orders of such plans. We introduce a new method for generalizing partially ordered plans. This method is based on providing explanation-based generalization (EBG) with explanations which systematically capture the interactions among plan operators for all the total orders of a partially-ordered plan. The explanations are based on the Modal Truth Criterion which states the necessary and sufficient conditions for ensuring the truth of a proposition at any point in a plan, for a class of partially ordered plans. The generalizations obtained by this method guarantee successful and interaction-free execution of any total order of the generalized plan. In addition, the systematic derivation of the generalization algorithms from the Modal Truth Criterion obviates the need for carrying out a separate formal proof of correctness of the EBG algorithms.
A genome-wide 3C-method for characterizing the three-dimensional architectures of genomes.

PubMed

Duan, Zhijun; Andronescu, Mirela; Schutz, Kevin; Lee, Choli; Shendure, Jay; Fields, Stanley; Noble, William S; Anthony Blau, C

2012-11-01

Accumulating evidence demonstrates that the three-dimensional (3D) organization of chromosomes within the eukaryotic nucleus reflects and influences genomic activities, including transcription, DNA replication, recombination and DNA repair. In order to uncover structure-function relationships, it is necessary first to understand the principles underlying the folding and the 3D arrangement of chromosomes. Chromosome conformation capture (3C) provides a powerful tool for detecting interactions within and between chromosomes. A high throughput derivative of 3C, chromosome conformation capture on chip (4C), executes a genome-wide interrogation of interaction partners for a given locus. We recently developed a new method, a derivative of 3C and 4C, which, similar to Hi-C, is capable of comprehensively identifying long-range chromosome interactions throughout a genome in an unbiased fashion. Hence, our method can be applied to decipher the 3D architectures of genomes. Here, we provide a detailed protocol for this method. Published by Elsevier Inc.
The Use of Two-Photon FRET-FLIM to Study Protein Interactions During Nuclear Envelope Fusion In Vivo and In Vitro.

PubMed

Byrne, Richard D; Larijani, Banafshé; Poccia, Dominic L

2016-01-01

FRET-FLIM techniques have wide application in the study of protein and protein-lipid interactions in cells. We have pioneered an imaging platform for accurate detection of functional states of proteins and their interactions in fixed cells. This platform, two-site-amplified Förster resonance energy transfer (a-FRET), allows greater signal generation while retaining minimal noise thus enabling application of fluorescence lifetime imaging microscopy (FLIM) to be routinely deployed in different types of cells and tissue. We have used the method described here, time-resolved FRET monitored by two-photon FLIM, to demonstrate the direct interaction of Phospholipase Cγ (PLCγ) by Src Family Kinase 1 (SFK1) during nuclear envelope formation and during male and female pronuclear membrane fusion in fertilized sea urchin eggs. We describe here a generic method that can be applied to monitor any proteins of interest.
Subsonic aerodynamic characteristics of interacting lifting surfaces with separated flow around sharp edges predicted by a vortex-lattice method

NASA Technical Reports Server (NTRS)

Lamar, J. E.; Gloss, B. B.

1975-01-01

Because the potential flow suction along the leading and side edges of a planform can be used to determine both leading- and side-edge vortex lift, the present investigation was undertaken to apply the vortex-lattice method to computing side-edge suction force for isolated or interacting planforms. Although there is a small effect of bound vortex sweep on the computation of the side-edge suction force, the results obtained for a number of different isolated planforms produced acceptable agreement with results obtained from a method employing continuous induced-velocity distributions. By using the method outlined, better agreement between theory and experiment was noted for a wing in the presence of a canard than was previously obtained.
Nonlocal Symmetry and Interaction Solutions of a Generalized Kadomtsev—Petviashvili Equation

NASA Astrophysics Data System (ADS)

Huang, Li-Li; Chen, Yong; Ma, Zheng-Yi

2016-08-01

A generalized Kadomtsev—Petviashvili equation is studied by nonlocal symmetry method and consistent Riccati expansion (CRE) method in this paper. Applying the truncated Painlevé analysis to the generalized Kadomtsev—Petviashvili equation, some Bäcklund transformations (BTs) including auto-BT and non-auto-BT are obtained. The auto-BT leads to a nonlocal symmetry which corresponds to the residual of the truncated Painlevé expansion. Then the nonlocal symmetry is localized to the corresponding nonlocal group by introducing two new variables. Further, by applying the Lie point symmetry method to the prolonged system, a new type of finite symmetry transformation is derived. In addition, the generalized Kadomtsev—Petviashvili equation is proved consistent Riccati expansion (CRE) solvable. As a result, the soliton-cnoidal wave interaction solutions of the equation are explicitly given, which are difficult to be found by other traditional methods. Moreover, figures are given out to show the properties of the explicit analytic interaction solutions. Supported by the Global Change Research Program of China under Grant No. 2015CB953904, National Natural Science Foundation of under Grant Nos. 11275072 and 11435005, Doctoral Program of Higher Education of China under Grant No. 20120076110024, the Network Information Physics Calculation of Basic Research Innovation Research Group of China under Grant No. 61321064, and Shanghai Collaborative Innovation Center of Trustworthy Software for Internet of Things under Grant No. ZF1213, and Zhejiang Provincial Natural Science Foundation of China under Grant No. LY14A010005
Resonating group method as applied to the spectroscopy of α-transfer reactions

NASA Astrophysics Data System (ADS)

Subbotin, V. B.; Semjonov, V. M.; Gridnev, K. A.; Hefter, E. F.

1983-10-01

In the conventional approach to α-transfer reactions the finite- and/or zero-range distorted-wave Born approximation is used in liaison with a macroscopic description of the captured α particle in the residual nucleus. Here the specific example of 16O(6Li,d)20Ne reactions at different projectile energies is taken to present a microscopic resonating group method analysis of the α particle in the final nucleus (for the reaction part the simple zero-range distorted-wave Born approximation is employed). In the discussion of suitable nucleon-nucleon interactions, force number one of the effective interactions presented by Volkov is shown to be most appropriate for the system considered. Application of the continuous analog of Newton's method to the evaluation of the resonating group method equations yields an increased accuracy with respect to traditional methods. The resonating group method description induces only minor changes in the structures of the angular distributions, but it does serve its purpose in yielding reliable and consistent spectroscopic information. NUCLEAR STRUCTURE 16O(6Li,d)20Ne; E=20 to 32 MeV; calculated B(E2); reduced widths, dσdΩ extracted α-spectroscopic factors. ZRDWBA with microscope RGM description of residual α particle in 20Ne; application of continuous analog of Newton's method; tested and applied Volkov force No. 1; direct mechanism.
Study of the interaction of 6-mercaptopurine with protein by microdialysis coupled with LC and electrochemical detection based on functionalized multi-wall carbon nanotubes modified electrode.

PubMed

Cao, Xu-Ni; Lin, Li; Zhou, Yu-Yan; Zhang, Wen; Shi, Guo-Yue; Yamamoto, Katsunobu; Jin, Li-Tong

2003-07-14

Microdialysis sampling coupled with liquid chromatography and electrochemical detection (LC-ECD) was developed and applied to study the interaction of 6-Mercaptopurine (6-MP) with bovine serum albumin (BSA). In the LC-ECD, the multi-wall carbon nanotubes fuctionalized with carboxylic groups modified electrode (MWNT-COOH CME) was used as the working electrode for the determination of 6-MP. The results indicated that this chemically modified electrode (CME) exhibited efficiently electrocatalytic oxidation for 6-MP with relatively high sensitivity, stability and long-life. The peak currents of 6-MP were linear to its concentrations ranging from 4.0 x 10(-7) to 1.0 x 10(-4) mol l(-1) with the calculated detection limit (S/N = 3) of 2.0 x 10(-7) mol l(-1). The method had been successfully applied to assess the association constant (K) and the number of the binding sites (n) on a BSA molecular, which calculated by Scatchard equation, were 3.97 x 10(3) mol(-1) l and 1.51, respectively. This method provided a fast, sensible and simple technique for the study of drug-protein interactions.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Pederson, Mark R.; Baruah, Tunna; Basurto, Luis

We have applied a recently developed method to incorporate the self-interaction correction through Fermi orbitals to Mg-porphyrin, C{sub 60}, and pentacene molecules. The Fermi-Löwdin orbitals are localized and unitarily invariant to the Kohn-Sham orbitals from which they are constructed. The self-interaction-corrected energy is obtained variationally leading to an optimum set of Fermi-Löwdin orbitals (orthonormalized Fermi orbitals) that gives the minimum energy. A Fermi orbital, by definition, is dependent on a certain point which is referred to as the descriptor position. The degree to which the initial choice of descriptor positions influences the variational approach to the minimum and the complexitymore » of the energy landscape as a function of Fermi-orbital descriptors is examined in detail for Mg-porphyrin. The applications presented here also demonstrate that the method can be applied to larger molecular systems containing a few hundred electrons. The atomization energy of the C{sub 60} molecule within the Fermi-Löwdin-orbital self-interaction-correction approach is significantly improved compared to local density approximation in the Perdew-Wang 92 functional and generalized gradient approximation of Perdew-Burke-Ernzerhof functionals. The eigenvalues of the highest occupied molecular orbitals show qualitative improvement.« less
Hierarchical equations of motion method applied to nonequilibrium heat transport in model molecular junctions: Transient heat current and high-order moments of the current operator

NASA Astrophysics Data System (ADS)

Song, Linze; Shi, Qiang

2017-02-01

We present a theoretical approach to study nonequilibrium quantum heat transport in molecular junctions described by a spin-boson type model. Based on the Feynman-Vernon path integral influence functional formalism, expressions for the average value and high-order moments of the heat current operators are derived, which are further obtained directly from the auxiliary density operators (ADOs) in the hierarchical equations of motion (HEOM) method. Distribution of the heat current is then derived from the high-order moments. As the HEOM method is nonperturbative and capable of treating non-Markovian system-environment interactions, the method can be applied to various problems of nonequilibrium quantum heat transport beyond the weak coupling regime.
Computational methods and traveling wave solutions for the fourth-order nonlinear Ablowitz-Kaup-Newell-Segur water wave dynamical equation via two methods and its applications

NASA Astrophysics Data System (ADS)

Ali, Asghar; Seadawy, Aly R.; Lu, Dianchen

2018-05-01

The aim of this article is to construct some new traveling wave solutions and investigate localized structures for fourth-order nonlinear Ablowitz-Kaup-Newell-Segur (AKNS) water wave dynamical equation. The simple equation method (SEM) and the modified simple equation method (MSEM) are applied in this paper to construct the analytical traveling wave solutions of AKNS equation. The different waves solutions are derived by assigning special values to the parameters. The obtained results have their importance in the field of physics and other areas of applied sciences. All the solutions are also graphically represented. The constructed results are often helpful for studying several new localized structures and the waves interaction in the high-dimensional models.
Artificial intelligence applied to the automatic analysis of absorption spectra. Objective measurement of the fine structure constant

NASA Astrophysics Data System (ADS)

Bainbridge, Matthew B.; Webb, John K.

2017-06-01

A new and automated method is presented for the analysis of high-resolution absorption spectra. Three established numerical methods are unified into one `artificial intelligence' process: a genetic algorithm (Genetic Voigt Profile FIT, gvpfit); non-linear least-squares with parameter constraints (vpfit); and Bayesian model averaging (BMA). The method has broad application but here we apply it specifically to the problem of measuring the fine structure constant at high redshift. For this we need objectivity and reproducibility. gvpfit is also motivated by the importance of obtaining a large statistical sample of measurements of Δα/α. Interactive analyses are both time consuming and complex and automation makes obtaining a large sample feasible. In contrast to previous methodologies, we use BMA to derive results using a large set of models and show that this procedure is more robust than a human picking a single preferred model since BMA avoids the systematic uncertainties associated with model choice. Numerical simulations provide stringent tests of the whole process and we show using both real and simulated spectra that the unified automated fitting procedure out-performs a human interactive analysis. The method should be invaluable in the context of future instrumentation like ESPRESSO on the VLT and indeed future ELTs. We apply the method to the zabs = 1.8389 absorber towards the zem = 2.145 quasar J110325-264515. The derived constraint of Δα/α = 3.3 ± 2.9 × 10-6 is consistent with no variation and also consistent with the tentative spatial variation reported in Webb et al. and King et al.
Applying Quantum Monte Carlo to the Electronic Structure Problem

NASA Astrophysics Data System (ADS)

Powell, Andrew D.; Dawes, Richard

2016-06-01

Two distinct types of Quantum Monte Carlo (QMC) calculations are applied to electronic structure problems such as calculating potential energy curves and producing benchmark values for reaction barriers. First, Variational and Diffusion Monte Carlo (VMC and DMC) methods using a trial wavefunction subject to the fixed node approximation were tested using the CASINO code.[1] Next, Full Configuration Interaction Quantum Monte Carlo (FCIQMC), along with its initiator extension (i-FCIQMC) were tested using the NECI code.[2] FCIQMC seeks the FCI energy for a specific basis set. At a reduced cost, the efficient i-FCIQMC method can be applied to systems in which the standard FCIQMC approach proves to be too costly. Since all of these methods are statistical approaches, uncertainties (error-bars) are introduced for each calculated energy. This study tests the performance of the methods relative to traditional quantum chemistry for some benchmark systems. References: [1] R. J. Needs et al., J. Phys.: Condensed Matter 22, 023201 (2010). [2] G. H. Booth et al., J. Chem. Phys. 131, 054106 (2009).
Archaeology Through Computational Linguistics: Inscription Statistics Predict Excavation Sites of Indus Valley Artifacts.

PubMed

Recchia, Gabriel L; Louwerse, Max M

2016-11-01

Computational techniques comparing co-occurrences of city names in texts allow the relative longitudes and latitudes of cities to be estimated algorithmically. However, these techniques have not been applied to estimate the provenance of artifacts with unknown origins. Here, we estimate the geographic origin of artifacts from the Indus Valley Civilization, applying methods commonly used in cognitive science to the Indus script. We show that these methods can accurately predict the relative locations of archeological sites on the basis of artifacts of known provenance, and we further apply these techniques to determine the most probable excavation sites of four sealings of unknown provenance. These findings suggest that inscription statistics reflect historical interactions among locations in the Indus Valley region, and they illustrate how computational methods can help localize inscribed archeological artifacts of unknown origin. The success of this method offers opportunities for the cognitive sciences in general and for computational anthropology specifically. Copyright © 2015 Cognitive Science Society, Inc.

A systems biology model of the regulatory network in Populus leaves reveals interacting regulators and conserved regulation

PubMed Central

2011-01-01

Background Green plant leaves have always fascinated biologists as hosts for photosynthesis and providers of basic energy to many food webs. Today, comprehensive databases of gene expression data enable us to apply increasingly more advanced computational methods for reverse-engineering the regulatory network of leaves, and to begin to understand the gene interactions underlying complex emergent properties related to stress-response and development. These new systems biology methods are now also being applied to organisms such as Populus, a woody perennial tree, in order to understand the specific characteristics of these species. Results We present a systems biology model of the regulatory network of Populus leaves. The network is reverse-engineered from promoter information and expression profiles of leaf-specific genes measured over a large set of conditions related to stress and developmental. The network model incorporates interactions between regulators, such as synergistic and competitive relationships, by evaluating increasingly more complex regulatory mechanisms, and is therefore able to identify new regulators of leaf development not found by traditional genomics methods based on pair-wise expression similarity. The approach is shown to explain available gene function information and to provide robust prediction of expression levels in new data. We also use the predictive capability of the model to identify condition-specific regulation as well as conserved regulation between Populus and Arabidopsis. Conclusions We outline a computationally inferred model of the regulatory network of Populus leaves, and show how treating genes as interacting, rather than individual, entities identifies new regulators compared to traditional genomics analysis. Although systems biology models should be used with care considering the complexity of regulatory programs and the limitations of current genomics data, methods describing interactions can provide hypotheses about the underlying cause of emergent properties and are needed if we are to identify target genes other than those constituting the "low hanging fruit" of genomic analysis. PMID:21232107
Energy of adhesion of human T cells to adsorption layers of monoclonal antibodies measured by a film trapping technique.

PubMed Central

Ivanov, I B; Hadjiiski, A; Denkov, N D; Gurkov, T D; Kralchevsky, P A; Koyasu, S

1998-01-01

A novel method for studying the interaction of biological cells with interfaces (e.g., adsorption monolayers of antibodies) is developed. The method is called the film trapping technique because the cell is trapped within an aqueous film of equilibrium thickness smaller than the cell diameter. A liquid film of uneven thickness is formed around the trapped cell. When observed in reflected monochromatic light, this film exhibits an interference pattern of concentric bright and dark fringes. From the radii of the fringes one can restore the shape of interfaces and the cell. Furthermore, one can calculate the adhesive energy between the cell membrane and the aqueous film surface (which is covered by a layer of adsorbed proteins and/or specific ligands), as well as the disjoining pressure, representing the force of interaction per unit area of the latter film. The method is applied to two human T cell lines: Jurkat and its T cell receptor negative (TCR-) derivative. The interaction of these cells with monolayers of three different monoclonal antibodies adsorbed at a water-air interface is studied. The results show that the adhesive energy is considerable (above 0.5 mJ/m2) when the adsorption monolayer contains antibodies acting as specific ligands for the receptors expressed on the cell surface. In contrast, the adhesive energy is close to zero in the absence of such a specific ligand-receptor interaction. In principle, the method can be applied to the study of the interaction of a variety of biological cells (B cells, natural killer cells, red blood cells, etc.) with adsorption monolayers of various biologically active molecules. In particular, film trapping provides a tool for the gentle micromanipulation of cells and for monitoring of processes (say the activation of a T lymphocyte) occurring at the single-cell level. PMID:9649417
Bayesian GGE biplot models applied to maize multi-environments trials.

PubMed

de Oliveira, L A; da Silva, C P; Nuvunga, J J; da Silva, A Q; Balestre, M

2016-06-17

The additive main effects and multiplicative interaction (AMMI) and the genotype main effects and genotype x environment interaction (GGE) models stand out among the linear-bilinear models used in genotype x environment interaction studies. Despite the advantages of their use to describe genotype x environment (AMMI) or genotype and genotype x environment (GGE) interactions, these methods have known limitations that are inherent to fixed effects models, including difficulty in treating variance heterogeneity and missing data. Traditional biplots include no measure of uncertainty regarding the principal components. The present study aimed to apply the Bayesian approach to GGE biplot models and assess the implications for selecting stable and adapted genotypes. Our results demonstrated that the Bayesian approach applied to GGE models with non-informative priors was consistent with the traditional GGE biplot analysis, although the credible region incorporated into the biplot enabled distinguishing, based on probability, the performance of genotypes, and their relationships with the environments in the biplot. Those regions also enabled the identification of groups of genotypes and environments with similar effects in terms of adaptability and stability. The relative position of genotypes and environments in biplots is highly affected by the experimental accuracy. Thus, incorporation of uncertainty in biplots is a key tool for breeders to make decisions regarding stability selection and adaptability and the definition of mega-environments.
Cognitive engineering and health informatics: Applications and intersections.

PubMed

Hettinger, A Zachary; Roth, Emilie M; Bisantz, Ann M

2017-03-01

Cognitive engineering is an applied field with roots in both cognitive science and engineering that has been used to support design of information displays, decision support, human-automation interaction, and training in numerous high risk domains ranging from nuclear power plant control to transportation and defense systems. Cognitive engineering provides a set of structured, analytic methods for data collection and analysis that intersect with and complement methods of Cognitive Informatics. These methods support discovery of aspects of the work that make performance challenging, as well as the knowledge, skills, and strategies that experts use to meet those challenges. Importantly, cognitive engineering methods provide novel representations that highlight the inherent complexities of the work domain and traceable links between the results of cognitive analyses and actionable design requirements. This article provides an overview of relevant cognitive engineering methods, and illustrates how they have been applied to the design of health information technology (HIT) systems. Additionally, although cognitive engineering methods have been applied in the design of user-centered informatics systems, methods drawn from informatics are not typically incorporated into a cognitive engineering analysis. This article presents a discussion regarding ways in which data-rich methods can inform cognitive engineering. Copyright © 2017 Elsevier Inc. All rights reserved.
Approximate solution of coupled cluster equations: application to the coupled cluster doubles method and non-covalent interacting systems.

PubMed

Smiga, Szymon; Fabiano, Eduardo

2017-11-15

We have developed a simplified coupled cluster (SCC) methodology, using the basic idea of scaled MP2 methods. The scheme has been applied to the coupled cluster double equations and implemented in three different non-iterative variants. This new method (especially the SCCD[3] variant, which utilizes a spin-resolved formalism) has been found to be very efficient and to yield an accurate approximation of the reference CCD results for both total and interaction energies of different atoms and molecules. Furthermore, we demonstrate that the equations determining the scaling coefficients for the SCCD[3] approach can generate non-empirical SCS-MP2 scaling coefficients which are in good agreement with previous theoretical investigations.
A virtual computer lab for distance biomedical technology education.

PubMed

Locatis, Craig; Vega, Anibal; Bhagwat, Medha; Liu, Wei-Li; Conde, Jose

2008-03-13

The National Library of Medicine's National Center for Biotechnology Information offers mini-courses which entail applying concepts in biochemistry and genetics to search genomics databases and other information sources. They are highly interactive and involve use of 3D molecular visualization software that can be computationally taxing. Methods were devised to offer the courses at a distance so as to provide as much functionality of a computer lab as possible, the venue where they are normally taught. The methods, which can be employed with varied videoconferencing technology and desktop sharing software, were used to deliver mini-courses at a distance in pilot applications where students could see demonstrations by the instructor and the instructor could observe and interact with students working at their remote desktops. Student ratings of the learning experience and comments to open ended questions were similar to those when the courses are offered face to face. The real time interaction and the instructor's ability to access student desktops from a distance in order to provide individual assistance and feedback were considered invaluable. The technologies and methods mimic much of the functionality of computer labs and may be usefully applied in any context where content changes frequently, training needs to be offered on complex computer applications at a distance in real time, and where it is necessary for the instructor to monitor students as they work.
The Interaction between Heterotrophic Bacteria and Coliform, Fecal Coliform, Fecal Streptococci Bacteria in the Water Supply Networks.

PubMed

Amanidaz, Nazak; Zafarzadeh, Ali; Mahvi, Amir Hossein

2015-12-01

This study investigated the interaction between heterotrophic bacteria and coliform, fecal coliforms, fecal streptococci bacteria in water supply networks. This study was conducted during 2013 on water supply distribution network in Aq Qala City, Golestan Province, Northern Iran and standard methods were applied for microbiological analysis. The surface method was applied to test the heterotrophic bacteria and MPN method was used for coliform, fecal coliform and fecal streptococci bacteria measurements. In 114 samples, heterotrophic bacteria count were over 500 CFU/ml, which the amount of fecal coliform, coliform, and fecal streptococci were 8, 32, and 20 CFU/100 ml, respectively. However, in the other 242 samples, with heterotrophic bacteria count being less than 500 CFU/ml, the amount of fecal coliform, coliform, and fecal streptococci was 7, 23, and 11 CFU/100ml, respectively. The relationship between heterotrophic bacteria, coliforms and fecal streptococci was highly significant (P<0.05). We observed the concentration of coliforms, fecal streptococci bacteria being high, whenever the concentration of heterotrophic bacteria in the water network systems was high. Interaction between heterotrophic bacteria and coliform, fecal coliforms, fecal streptococci bacteria in the Aq Qala City water supply networks was not notable. It can be due to high concentrations of organic carbon, bio-films and nutrients, which are necessary for growth, and survival of all microorganisms.
Improving Depth, Energy and Timing Estimation in PET Detectors with Deconvolution and Maximum Likelihood Pulse Shape Discrimination

PubMed Central

Berg, Eric; Roncali, Emilie; Hutchcroft, Will; Qi, Jinyi; Cherry, Simon R.

2016-01-01

In a scintillation detector, the light generated in the scintillator by a gamma interaction is converted to photoelectrons by a photodetector and produces a time-dependent waveform, the shape of which depends on the scintillator properties and the photodetector response. Several depth-of-interaction (DOI) encoding strategies have been developed that manipulate the scintillator’s temporal response along the crystal length and therefore require pulse shape discrimination techniques to differentiate waveform shapes. In this work, we demonstrate how maximum likelihood (ML) estimation methods can be applied to pulse shape discrimination to better estimate deposited energy, DOI and interaction time (for time-of-flight (TOF) PET) of a gamma ray in a scintillation detector. We developed likelihood models based on either the estimated detection times of individual photoelectrons or the number of photoelectrons in discrete time bins, and applied to two phosphor-coated crystals (LFS and LYSO) used in a previously developed TOF-DOI detector concept. Compared with conventional analytical methods, ML pulse shape discrimination improved DOI encoding by 27% for both crystals. Using the ML DOI estimate, we were able to counter depth-dependent changes in light collection inherent to long scintillator crystals and recover the energy resolution measured with fixed depth irradiation (~11.5% for both crystals). Lastly, we demonstrated how the Richardson-Lucy algorithm, an iterative, ML-based deconvolution technique, can be applied to the digitized waveforms to deconvolve the photodetector’s single photoelectron response and produce waveforms with a faster rising edge. After deconvolution and applying DOI and time-walk corrections, we demonstrated a 13% improvement in coincidence timing resolution (from 290 to 254 ps) with the LFS crystal and an 8% improvement (323 to 297 ps) with the LYSO crystal. PMID:27295658
Improving Depth, Energy and Timing Estimation in PET Detectors with Deconvolution and Maximum Likelihood Pulse Shape Discrimination.

PubMed

Berg, Eric; Roncali, Emilie; Hutchcroft, Will; Qi, Jinyi; Cherry, Simon R

2016-11-01

In a scintillation detector, the light generated in the scintillator by a gamma interaction is converted to photoelectrons by a photodetector and produces a time-dependent waveform, the shape of which depends on the scintillator properties and the photodetector response. Several depth-of-interaction (DOI) encoding strategies have been developed that manipulate the scintillator's temporal response along the crystal length and therefore require pulse shape discrimination techniques to differentiate waveform shapes. In this work, we demonstrate how maximum likelihood (ML) estimation methods can be applied to pulse shape discrimination to better estimate deposited energy, DOI and interaction time (for time-of-flight (TOF) PET) of a gamma ray in a scintillation detector. We developed likelihood models based on either the estimated detection times of individual photoelectrons or the number of photoelectrons in discrete time bins, and applied to two phosphor-coated crystals (LFS and LYSO) used in a previously developed TOF-DOI detector concept. Compared with conventional analytical methods, ML pulse shape discrimination improved DOI encoding by 27% for both crystals. Using the ML DOI estimate, we were able to counter depth-dependent changes in light collection inherent to long scintillator crystals and recover the energy resolution measured with fixed depth irradiation (~11.5% for both crystals). Lastly, we demonstrated how the Richardson-Lucy algorithm, an iterative, ML-based deconvolution technique, can be applied to the digitized waveforms to deconvolve the photodetector's single photoelectron response and produce waveforms with a faster rising edge. After deconvolution and applying DOI and time-walk corrections, we demonstrated a 13% improvement in coincidence timing resolution (from 290 to 254 ps) with the LFS crystal and an 8% improvement (323 to 297 ps) with the LYSO crystal.
Allelic-based gene-gene interaction associated with quantitative traits.

PubMed

Jung, Jeesun; Sun, Bin; Kwon, Deukwoo; Koller, Daniel L; Foroud, Tatiana M

2009-05-01

Recent studies have shown that quantitative phenotypes may be influenced not only by multiple single nucleotide polymorphisms (SNPs) within a gene but also by the interaction between SNPs at unlinked genes. We propose a new statistical approach that can detect gene-gene interactions at the allelic level which contribute to the phenotypic variation in a quantitative trait. By testing for the association of allelic combinations at multiple unlinked loci with a quantitative trait, we can detect the SNP allelic interaction whether or not it can be detected as a main effect. Our proposed method assigns a score to unrelated subjects according to their allelic combination inferred from observed genotypes at two or more unlinked SNPs, and then tests for the association of the allelic score with a quantitative trait. To investigate the statistical properties of the proposed method, we performed a simulation study to estimate type I error rates and power and demonstrated that this allelic approach achieves greater power than the more commonly used genotypic approach to test for gene-gene interaction. As an example, the proposed method was applied to data obtained as part of a candidate gene study of sodium retention by the kidney. We found that this method detects an interaction between the calcium-sensing receptor gene (CaSR), the chloride channel gene (CLCNKB) and the Na, K, 2Cl cotransporter gene (CLC12A1) that contributes to variation in diastolic blood pressure.
Symbolic Interaction and Applied Social Research

PubMed Central

Kotarba, Joseph A.

2014-01-01

In symbolic interaction, a traditional yet unfortunate and unnecessary distinction has been made between basic and applied research. The argument has been made that basic research is intended to generate new knowledge, whereas applied research is intended to apply knowledge to the solution of practical (social and organizational) problems. I will argue that the distinction between basic and applied research in symbolic interaction is outdated and dysfunctional. The masters of symbolic interactionist thought have left us a proud legacy of shaping their scholarly thinking and inquiry in response to and in light of practical issues of the day (e.g., Znaniecki, and Blumer). Current interactionist work continues this tradition in topical areas such as social justice studies. Applied research, especially in term of evaluation and needs assessment studies, can be designed to serve both basic and applied goals. Symbolic interaction provides three great resources to do this. The first is its orientation to dynamic sensitizing concepts that direct research and ask questions instead of supplying a priori and often impractical answers. The second is its orientation to qualitative methods, and appreciation for the logic of grounded theory. The third is interactionism’s overall holistic approach to interfacing with the everyday life world. The primary illustrative case here is the qualitative component of the evaluation of an NIH-funded, translational medical research program. The qualitative component has provided interactionist-inspired insights into translational research, such as examining cultural change in medical research in terms of changes in the form and content of formal and informal discourse among scientists; delineating the impact of significant symbols such as "my lab" on the social organization of science; and appreciating the essence of the self-concept "scientist" on the increasingly bureaucratic and administrative identities of medical researchers. This component has also contributed to the basic social scientific literature on complex organizations and the self. PMID:25221375
Symbolic Interaction and Applied Social Research: A FOCUS ON TRANSLATIONAL SCIENCE RESEARCH1.

PubMed

Kotarba, Joseph A

2014-08-01

In symbolic interaction, a traditional yet unfortunate and unnecessary distinction has been made between basic and applied research. The argument has been made that basic research is intended to generate new knowledge, whereas applied research is intended to apply knowledge to the solution of practical (social and organizational) problems. I will argue that the distinction between basic and applied research in symbolic interaction is outdated and dysfunctional. The masters of symbolic interactionist thought have left us a proud legacy of shaping their scholarly thinking and inquiry in response to and in light of practical issues of the day (e.g., Znaniecki, and Blumer). Current interactionist work continues this tradition in topical areas such as social justice studies. Applied research, especially in term of evaluation and needs assessment studies, can be designed to serve both basic and applied goals. Symbolic interaction provides three great resources to do this. The first is its orientation to dynamic sensitizing concepts that direct research and ask questions instead of supplying a priori and often impractical answers. The second is its orientation to qualitative methods, and appreciation for the logic of grounded theory. The third is interactionism's overall holistic approach to interfacing with the everyday life world. The primary illustrative case here is the qualitative component of the evaluation of an NIH-funded, translational medical research program. The qualitative component has provided interactionist-inspired insights into translational research, such as examining cultural change in medical research in terms of changes in the form and content of formal and informal discourse among scientists; delineating the impact of significant symbols such as "my lab" on the social organization of science; and appreciating the essence of the self-concept "scientist" on the increasingly bureaucratic and administrative identities of medical researchers. This component has also contributed to the basic social scientific literature on complex organizations and the self.
Theoretical study of optical activity of 1:1 hydrogen bond complexes of water with S-warfarin

NASA Astrophysics Data System (ADS)

Dadsetani, Mehrdad; Abdolmaleki, Ahmad; Zabardasti, Abedin

2016-11-01

The molecular interaction between S-warfarin (SW) and a single water molecule was investigated using the B3LYP method at 6-311 ++G(d,p) basis set. The vibrational spectra of the optimized complexes have been investigated for stabilization checking. Quantum theories of atoms in molecules, natural bond orbitals, molecular electrostatic potentials and energy decomposition analysis methods have been applied to analyze the intermolecular interactions. The intermolecular charge transfer in the most stable complex is in the opposite direction from those in the other complexes. The optical spectra and the hyperpolarizabilities of SW-water hydrogen bond complexes have been computed.
Protein annotation from protein interaction networks and Gene Ontology.

PubMed

Nguyen, Cao D; Gardiner, Katheleen J; Cios, Krzysztof J

2011-10-01

We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precision and 60% recall versus 45% and 26% for Majority and 24% and 61% for χ²-statistics, respectively. Copyright © 2011 Elsevier Inc. All rights reserved.
Procedure for short-lived particle detection in the OPERA experiment and its application to charm decays

NASA Astrophysics Data System (ADS)

Agafonova, N.; Aleksandrov, A.; Anokhina, A.; Aoki, S.; Ariga, A.; Ariga, T.; Bender, D.; Bertolin, A.; Bozza, C.; Brugnera, R.; Buonaura, A.; Buontempo, S.; Büttner, B.; Chernyavsky, M.; Chukanov, A.; Consiglio, L.; D'Ambrosio, N.; De Lellis, G.; De Serio, M.; Del Amo Sanchez, P.; Di Crescenzo, A.; Di Ferdinando, D.; Di Marco, N.; Dmitrievski, S.; Dracos, M.; Duchesneau, D.; Dusini, S.; Dzhatdoev, T.; Ebert, J.; Ereditato, A.; Fini, R. A.; Fukuda, T.; Galati, G.; Garfagnini, A.; Giacomelli, G.; Göllnitz, C.; Goldberg, J.; Gornushkin, Y.; Grella, G.; Guler, M.; Gustavino, C.; Hagner, C.; Hara, T.; Hollnagel, A.; Hosseini, B.; Ishida, H.; Ishiguro, K.; Jakovcic, K.; Jollet, C.; Kamiscioglu, C.; Kamiscioglu, M.; Kawada, J.; Kim, J. H.; Kim, S. H.; Kitagawa, N.; Klicek, B.; Kodama, K.; Komatsu, M.; Kose, U.; Kreslo, I.; Lauria, A.; Lenkeit, J.; Ljubicic, A.; Longhin, A.; Loverre, P.; Malgin, A.; Malenica, M.; Mandrioli, G.; Matsuo, T.; Matveev, V.; Mauri, N.; Medinaceli, E.; Meregaglia, A.; Mikado, S.; Monacelli, P.; Montesi, M. C.; Morishima, K.; Muciaccia, M. T.; Naganawa, N.; Naka, T.; Nakamura, M.; Nakano, T.; Nakatsuka, Y.; Niwa, K.; Ogawa, S.; Okateva, N.; Olshevsky, A.; Omura, T.; Ozaki, K.; Paoloni, A.; Park, B. D.; Park, I. G.; Pasqualini, L.; Pastore, A.; Patrizii, L.; Pessard, H.; Pistillo, C.; Podgrudkov, D.; Polukhina, N.; Pozzato, M.; Pupilli, F.; Roda, M.; Rokujo, H.; Roganova, T.; Rosa, G.; Ryazhskaya, O.; Sato, O.; Schembri, A.; Shakiryanova, I.; Shchedrina, T.; Sheshukov, A.; Shibuya, H.; Shiraishi, T.; Shoziyoev, G.; Simone, S.; Sioli, M.; Sirignano, C.; Sirri, G.; Spinetti, M.; Stanco, L.; Starkov, N.; Stellacci, S. M.; Stipcevic, M.; Strauss, T.; Strolin, P.; Takahashi, S.; Tenti, M.; Terranova, F.; Tioukov, V.; Tufanli, S.; Vilain, P.; Vladimirov, M.; Votano, L.; Vuilleumier, J. L.; Wilquet, G.; Wonsak, B.; Yoon, C. S.; Zemskova, S.; Zghiche, A.

2014-08-01

The OPERA experiment, designed to perform the first observation of oscillations in appearance mode through the detection of the leptons produced in charged current interactions, has collected data from 2008 to 2012. In the present paper, the procedure developed to detect particle decays, occurring over distances of the order of from the neutrino interaction point, is described in detail and applied to the search for charmed hadrons, showing similar decay topologies as the lepton. In the analysed sample, 50 charm decay candidate events are observed while are expected, proving that the detector performance and the analysis chain applied to neutrino events are well reproduced by the OPERA simulation and thus validating the methods for appearance detection.
A kernel machine method for detecting effects of interaction between multidimensional variable sets: an imaging genetics application.

PubMed

Ge, Tian; Nichols, Thomas E; Ghosh, Debashis; Mormino, Elizabeth C; Smoller, Jordan W; Sabuncu, Mert R

2015-04-01

Measurements derived from neuroimaging data can serve as markers of disease and/or healthy development, are largely heritable, and have been increasingly utilized as (intermediate) phenotypes in genetic association studies. To date, imaging genetic studies have mostly focused on discovering isolated genetic effects, typically ignoring potential interactions with non-genetic variables such as disease risk factors, environmental exposures, and epigenetic markers. However, identifying significant interaction effects is critical for revealing the true relationship between genetic and phenotypic variables, and shedding light on disease mechanisms. In this paper, we present a general kernel machine based method for detecting effects of the interaction between multidimensional variable sets. This method can model the joint and epistatic effect of a collection of single nucleotide polymorphisms (SNPs), accommodate multiple factors that potentially moderate genetic influences, and test for nonlinear interactions between sets of variables in a flexible framework. As a demonstration of application, we applied the method to the data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to detect the effects of the interactions between candidate Alzheimer's disease (AD) risk genes and a collection of cardiovascular disease (CVD) risk factors, on hippocampal volume measurements derived from structural brain magnetic resonance imaging (MRI) scans. Our method identified that two genes, CR1 and EPHA1, demonstrate significant interactions with CVD risk factors on hippocampal volume, suggesting that CR1 and EPHA1 may play a role in influencing AD-related neurodegeneration in the presence of CVD risks. Copyright © 2015 Elsevier Inc. All rights reserved.
Modeling quantum fluid dynamics at nonzero temperatures

PubMed Central

Berloff, Natalia G.; Brachet, Marc; Proukakis, Nick P.

2014-01-01

The detailed understanding of the intricate dynamics of quantum fluids, in particular in the rapidly growing subfield of quantum turbulence which elucidates the evolution of a vortex tangle in a superfluid, requires an in-depth understanding of the role of finite temperature in such systems. The Landau two-fluid model is the most successful hydrodynamical theory of superfluid helium, but by the nature of the scale separations it cannot give an adequate description of the processes involving vortex dynamics and interactions. In our contribution we introduce a framework based on a nonlinear classical-field equation that is mathematically identical to the Landau model and provides a mechanism for severing and coalescence of vortex lines, so that the questions related to the behavior of quantized vortices can be addressed self-consistently. The correct equation of state as well as nonlocality of interactions that leads to the existence of the roton minimum can also be introduced in such description. We review and apply the ideas developed for finite-temperature description of weakly interacting Bose gases as possible extensions and numerical refinements of the proposed method. We apply this method to elucidate the behavior of the vortices during expansion and contraction following the change in applied pressure. We show that at low temperatures, during the contraction of the vortex core as the negative pressure grows back to positive values, the vortex line density grows through a mechanism of vortex multiplication. This mechanism is suppressed at high temperatures. PMID:24704874
Density-Difference-Driven Optimized Embedding Potential Method To Study the Spectroscopy of Br₂ in Water Clusters.

PubMed

Roncero, Octavio; Aguado, Alfredo; Batista-Romero, Fidel A; Bernal-Uruchurtu, Margarita I; Hernández-Lamoneda, Ramón

2015-03-10

A variant of the density difference driven optimized embedding potential (DDD-OEP) method, proposed by Roncero et al. (J. Chem. Phys. 2009, 131, 234110), has been applied to the calculation of excited states of Br2 within small water clusters. It is found that the strong interaction of Br2 with the lone electronic pair of the water molecules makes necessary to optimize specific embedding potentials for ground and excited electronic states, separately and using the corresponding densities. Diagnosis and convergence studies are presented with the aim of providing methods to be applied for the study of chromophores in solution. Also, some preliminary results obtained for the study of electronic states of Br2 in clathrate cages are presented.
Linking sediment-charcoal records and ecological modeling to understand causes of fire-regime change in boreal forests

Treesearch

Linda B. Brubaker; Philip E. Higuera; T. Scott Rupp; Mark A. Olson; Patricia M. Anderson; Feng Sheng. Hu

2009-01-01

Interactions between vegetation and fire have the potential to overshadow direct effects of climate change on fire regimes in boreal forests of North America. We develop methods to compare sediment-charcoal records with fire regimes simulated by an ecological model, ALFRESCO (Alaskan Frame-based Ecosystem Code) and apply these methods to evaluate potential causes of a...
Investigating Patterns of Interaction in Networked Learning and Computer-Supported Collaborative Learning: A Role for Social Network Analysis

ERIC Educational Resources Information Center

de Laat, Maarten; Lally, Vic; Lipponen, Lasse; Simons, Robert-Jan

2007-01-01

The focus of this study is to explore the advances that Social Network Analysis (SNA) can bring, in combination with other methods, when studying Networked Learning/Computer-Supported Collaborative Learning (NL/CSCL). We present a general overview of how SNA is applied in NL/CSCL research; we then go on to illustrate how this research method can…

Numerical simulation of the interaction between a flowfield and chemical reaction on premixed pulsed jet combustion

NASA Astrophysics Data System (ADS)

Hishida, Manabu; Hayashi, A. Koichi

1992-12-01

Pulsed Jet Combustion (PJC) is numerically simulated using time-dependent, axisymmetric, full Navier-Stokes equations with the mass, momentum, energy, and species conservation equations for a hydrogen-air mixture. A hydrogen-air reaction mechanism is modeled by nine species and nineteen elementary forward and backward reactions to evaluate the effect of the chemical reactions accurately. A point implicit method with the Harten and Yee's non-MUSCL (Monotone Upstream-centerd Schemes for Conservation Laws) modified-flux type TVD (Total Variation Diminishing) scheme is applied to deal with the stiff partial differential equations. Furthermore, a zonal method making use of the Fortified Solution Algorithm (FSA) is applied to simulate the phenomena in the complicated shape of the sub-chamber. The numerical result shows that flames propagating in the sub-chamber interact with pressure waves and are deformed to be wrinkled like a 'tulip' flame and a jet passed through the orifice changes its mass flux quasi-periodically.
Nucleon-nucleon interactions from dispersion relations: Elastic partial waves

NASA Astrophysics Data System (ADS)

Albaladejo, M.; Oller, J. A.

2011-11-01

We consider nucleon-nucleon (NN) interactions from chiral effective field theory. In this work we restrict ourselves to the elastic NN scattering. We apply the N/D method to calculate the NN partial waves taking as input the one-pion exchange discontinuity along the left-hand cut. This discontinuity is amenable to a chiral power counting as discussed by Lacour, Oller, and Meißner [Ann. Phys. (NY)APNYA60003-491610.1016/j.aop.2010.06.012 326, 241 (2011)], with one-pion exchange as its leading order contribution. The resulting linear integral equation for a partial wave with orbital angular momentum ℓ≥2 is solved in the presence of ℓ-1 constraints, so as to guarantee the right behavior of the D- and higher partial waves near threshold. The calculated NN partial waves are based on dispersion relations and are independent of regulator. This method can also be applied to higher orders in the calculation of the discontinuity along the left-hand cut and extended to triplet coupled partial waves.
On the Scattering of the Electron off the Hydrogen Atom and the Helium Ion Below and Above the Ionization Threshold: Temkin-Poet Model

NASA Astrophysics Data System (ADS)

Yarevsky, E.; Yakovlev, S. L.; Elander, N.; Volkov, M. V.

2014-08-01

We generalize here the splitting approach to the long range (Coulomb) interaction for the three body scattering problem. With this approach, the exterior complex rotation technique can be applied for systems with asymptotic Coulomb interaction. We illustrate the method with calculations of the electron scattering on the hydrogen atom and positive helium ion in the frame of the Temkin-Poet model.
International Symposium on Solute-Solute-Solvent Interactions (7th) Held at Reading, United Kingdom on 15-19 July 1985.

DTIC Science & Technology

1985-07-19

analytical, integral equation methods can be applied to the problem of elucidating the detailed structural properties of strongly interacting molecu- lar...curve. r. I equation -)f sate to calculate phase diagrams and critical irv,: for polar-non polar systems is described. Measurements with the .- r...FRANCE The fundamentai] equations of the Onsager approach of transport properties in linear response are summarized. From a reformula- tion of the
Optical method for the characterization of laterally-patterned samples in integrated circuits

DOEpatents

Maris, Humphrey J.

2001-01-01

Disclosed is a method for characterizing a sample having a structure disposed on or within the sample, comprising the steps of applying a first pulse of light to a surface of the sample for creating a propagating strain pulse in the sample, applying a second pulse of light to the surface so that the second pulse of light interacts with the propagating strain pulse in the sample, sensing from a reflection of the second pulse a change in optical response of the sample, and relating a time of occurrence of the change in optical response to at least one dimension of the structure.
Optical method and system for the characterization of laterally-patterned samples in integrated circuits

DOEpatents

Maris, Humphrey J.

2008-03-04

Disclosed is a method for characterizing a sample having a structure disposed on or within the sample, comprising the steps of applying a first pulse of light to a surface of the sample for creating a propagating strain pulse in the sample, applying a second pulse of light to the surface so that the second pulse of light interacts with the propagating strain pulse in the sample, sensing from a reflection of the second pulse a change in optical response of the sample, and relating a time of occurrence of the change in optical response to at least one dimension of the structure.
Optical method for the characterization of laterally-patterned samples in integrated circuits

DOEpatents

Maris, Humphrey J.

2010-08-24

Disclosed is a method for characterizing a sample having a structure disposed on or within the sample, comprising the steps of applying a first pulse of light to a surface of the sample for creating a propagating strain pulse in the sample, applying a second pulse of light to the surface so that the second pulse of light interacts with the propagating strain pulse in the sample, sensing from a reflection of the second pulse a change in optical response of the sample, and relating a time of occurrence of the change in optical response to at least one dimension of the structure.
Optical method for the characterization of laterally patterned samples in integrated circuits

DOEpatents

Maris, Humphrey J [Barrington, RI

2009-03-17

Disclosed is a method for characterizing a sample having a structure disposed on or within the sample, comprising the steps of applying a first pulse of light to a surface of the sample for creating a propagating strain pulse in the sample, applying a second pulse of light to the surface so that the second pulse of light interacts with the propagating strain pulse in the sample, sensing from a reflection of the second pulse a change in optical response of the sample, and relating a time of occurrence of the change in optical response to at least one dimension of the structure.
Optical method and system for the characterization of laterally-patterned samples in integrated circuits

DOEpatents

Maris, Humphrey J [Barrington, RI

2011-02-22

Disclosed is a method for characterizing a sample having a structure disposed on or within the sample, comprising the steps of applying a first pulse of light to a surface of the sample for creating a propagating strain pulse in the sample, applying a second pulse of light to the surface so that the second pulse of light interacts with the propagating strain pulse in the sample, sensing from a reflection of the second pulse a change in optical response of the sample, and relating a time of occurrence of the change in optical response to at least one dimension of the structure.
Evolution of statistical averages: An interdisciplinary proposal using the Chapman-Enskog method

NASA Astrophysics Data System (ADS)

Mariscal-Sanchez, A.; Sandoval-Villalbazo, A.

2017-08-01

This work examines the idea of applying the Chapman-Enskog (CE) method for approximating the solution of the Boltzmann equation beyond the realm of physics, using an information theory approach. Equations describing the evolution of averages and their fluctuations in a generalized phase space are established up to first-order in the Knudsen parameter which is defined as the ratio of the time between interactions (mean free time) and a characteristic macroscopic time. Although the general equations here obtained may be applied in a wide range of disciplines, in this paper, only a particular case related to the evolution of averages in speculative markets is examined.
Application of advanced multidisciplinary analysis and optimization methods to vehicle design synthesis

NASA Technical Reports Server (NTRS)

Consoli, Robert David; Sobieszczanski-Sobieski, Jaroslaw

1990-01-01

Advanced multidisciplinary analysis and optimization methods, namely system sensitivity analysis and non-hierarchical system decomposition, are applied to reduce the cost and improve the visibility of an automated vehicle design synthesis process. This process is inherently complex due to the large number of functional disciplines and associated interdisciplinary couplings. Recent developments in system sensitivity analysis as applied to complex non-hierarchic multidisciplinary design optimization problems enable the decomposition of these complex interactions into sub-processes that can be evaluated in parallel. The application of these techniques results in significant cost, accuracy, and visibility benefits for the entire design synthesis process.
Computational prediction of host-pathogen protein-protein interactions.

PubMed

Dyer, Matthew D; Murali, T M; Sobral, Bruno W

2007-07-01

Infectious diseases such as malaria result in millions of deaths each year. An important aspect of any host-pathogen system is the mechanism by which a pathogen can infect its host. One method of infection is via protein-protein interactions (PPIs) where pathogen proteins target host proteins. Developing computational methods that identify which PPIs enable a pathogen to infect a host has great implications in identifying potential targets for therapeutics. We present a method that integrates known intra-species PPIs with protein-domain profiles to predict PPIs between host and pathogen proteins. Given a set of intra-species PPIs, we identify the functional domains in each of the interacting proteins. For every pair of functional domains, we use Bayesian statistics to assess the probability that two proteins with that pair of domains will interact. We apply our method to the Homo sapiens-Plasmodium falciparum host-pathogen system. Our system predicts 516 PPIs between proteins from these two organisms. We show that pairs of human proteins we predict to interact with the same Plasmodium protein are close to each other in the human PPI network and that Plasmodium pairs predicted to interact with same human protein are co-expressed in DNA microarray datasets measured during various stages of the Plasmodium life cycle. Finally, we identify functionally enriched sub-networks spanned by the predicted interactions and discuss the plausibility of our predictions. Supplementary data are available at http://staff.vbi.vt.edu/dyermd/publications/dyer2007a.html. Supplementary data are available at Bioinformatics online.
A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine.

PubMed

Jain, Dharm Skandh; Gupte, Sanket Rajan; Aduri, Raviprasad

2018-06-22

RNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these methods has been the accuracy and confidence of the predictions, and our in-house experiments show that they fail to accurately predict RPI involving short RNA sequences such as TERRA RNA. Here, we present a data-driven model for RPI prediction using a gradient boosting classifier. Amino acids and nucleotides are classified based on the high-resolution structural data of RNA protein complexes. The minimum structural unit consisting of five residues is used as the descriptor. Comparative analysis of existing methods shows the consistently higher performance of our method irrespective of the length of RNA present in the RPI. The method has been successfully applied to map RPI networks involving both long noncoding RNA as well as TERRA RNA. The method is also shown to successfully predict RNA and protein hubs present in RPI networks of four different organisms. The robustness of this method will provide a way for predicting RPI networks of yet unknown interactions for both long noncoding RNA and microRNA.
A method for generating reliable atomistic models of amorphous polymers based on a random search of energy minima

NASA Astrophysics Data System (ADS)

Curcó, David; Casanovas, Jordi; Roca, Marc; Alemán, Carlos

2005-07-01

A method for generating atomistic models of dense amorphous polymers is presented. The method is organized in a two-steps procedure. First, structures are generated using an algorithm that minimizes the torsional strain. After this, a relaxation algorithm is applied to minimize the non-bonding interactions. Two alternative relaxation methods, which are based simple minimization and Concerted Rotation techniques, have been implemented. The performance of the method has been checked by simulating polyethylene, polypropylene, nylon 6, poly(L,D-lactic acid) and polyglycolic acid.
Deep-Learning-Based Drug-Target Interaction Prediction.

PubMed

Wen, Ming; Zhang, Zhimin; Niu, Shaoyu; Sha, Haozhi; Yang, Ruihan; Yun, Yonghuan; Lu, Hongmei

2017-04-07

Identifying interactions between known drugs and targets is a major challenge in drug repositioning. In silico prediction of drug-target interaction (DTI) can speed up the expensive and time-consuming experimental work by providing the most potent DTIs. In silico prediction of DTI can also provide insights about the potential drug-drug interaction and promote the exploration of drug side effects. Traditionally, the performance of DTI prediction depends heavily on the descriptors used to represent the drugs and the target proteins. In this paper, to accurately predict new DTIs between approved drugs and targets without separating the targets into different classes, we developed a deep-learning-based algorithmic framework named DeepDTIs. It first abstracts representations from raw input descriptors using unsupervised pretraining and then applies known label pairs of interaction to build a classification model. Compared with other methods, it is found that DeepDTIs reaches or outperforms other state-of-the-art methods. The DeepDTIs can be further used to predict whether a new drug targets to some existing targets or whether a new target interacts with some existing drugs.
OncoBinder facilitates interpretation of proteomic interaction data by capturing coactivation pairs in cancer.

PubMed

Van Coillie, Samya; Liang, Lunxi; Zhang, Yao; Wang, Huanbin; Fang, Jing-Yuan; Xu, Jie

2016-04-05

High-throughput methods such as co-immunoprecipitationmass spectrometry (coIP-MS) and yeast 2 hybridization (Y2H) have suggested a broad range of unannotated protein-protein interactions (PPIs), and interpretation of these PPIs remains a challenging task. The advancements in cancer genomic researches allow for the inference of "coactivation pairs" in cancer, which may facilitate the identification of PPIs involved in cancer. Here we present OncoBinder as a tool for the assessment of proteomic interaction data based on the functional synergy of oncoproteins in cancer. This decision tree-based method combines gene mutation, copy number and mRNA expression information to infer the functional status of protein-coding genes. We applied OncoBinder to evaluate the potential binders of EGFR and ERK2 proteins based on the gastric cancer dataset of The Cancer Genome Atlas (TCGA). As a result, OncoBinder identified high confidence interactions (annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) or validated by low-throughput assays) more efficiently than co-expression based method. Taken together, our results suggest that evaluation of gene functional synergy in cancer may facilitate the interpretation of proteomic interaction data. The OncoBinder toolbox for Matlab is freely accessible online.
Playing cards on asthma management: A new interactive method for knowledge transfer to primary care physicians

PubMed Central

Boulet, Louis-Philippe; Borduas, Francine; Bouchard, Jacques; Blais, Johanne; Hargreave, Frederick E; Rouleau, Michel

2007-01-01

OBJECTIVES: To describe an interactive playing card workshop in the communication of asthma guidelines recommendations, and to assess the initial evaluation of this educational tool by family physicians. DESIGN: Family physicians were invited to participate in the workshop by advertisements or personal contacts. Each physician completed a standardized questionnaire on his or her perception of the rules, content and properties of the card game. SETTING: A university-based continuing medical education initiative. PARTICIPANTS: Primary care physicians. MAIN OUTCOME MEASURES: Physicians’ evaluation of the rules, content and usefulness of the program. RESULTS: The game allowed the communication of relevant asthma-related content, as well as experimentation with a different learning format. It also stimulated interaction in a climate of friendly competition. Participating physicians considered the method to be an innovative tool that facilitated reflection, interaction and learning. It generated relevant discussions on how to apply guideline recommendations to current asthma care. CONCLUSIONS: This new, interactive, educational intervention, integrating play and scientific components, was well received by participants. This method may be of value to help integrate current guidelines into current practice, thus facilitating knowledge transfer to caregivers. PMID:18060093
Gene-Based Testing of Interactions in Association Studies of Quantitative Traits

PubMed Central

Ma, Li; Clark, Andrew G.; Keinan, Alon

2013-01-01

Various methods have been developed for identifying gene–gene interactions in genome-wide association studies (GWAS). However, most methods focus on individual markers as the testing unit, and the large number of such tests drastically erodes statistical power. In this study, we propose novel interaction tests of quantitative traits that are gene-based and that confer advantage in both statistical power and biological interpretation. The framework of gene-based gene–gene interaction (GGG) tests combine marker-based interaction tests between all pairs of markers in two genes to produce a gene-level test for interaction between the two. The tests are based on an analytical formula we derive for the correlation between marker-based interaction tests due to linkage disequilibrium. We propose four GGG tests that extend the following P value combining methods: minimum P value, extended Simes procedure, truncated tail strength, and truncated P value product. Extensive simulations point to correct type I error rates of all tests and show that the two truncated tests are more powerful than the other tests in cases of markers involved in the underlying interaction not being directly genotyped and in cases of multiple underlying interactions. We applied our tests to pairs of genes that exhibit a protein–protein interaction to test for gene-level interactions underlying lipid levels using genotype data from the Atherosclerosis Risk in Communities study. We identified five novel interactions that are not evident from marker-based interaction testing and successfully replicated one of these interactions, between SMAD3 and NEDD9, in an independent sample from the Multi-Ethnic Study of Atherosclerosis. We conclude that our GGG tests show improved power to identify gene-level interactions in existing, as well as emerging, association studies. PMID:23468652
Disentangling the co-structure of multilayer interaction networks: degree distribution and module composition in two-layer bipartite networks.

PubMed

Astegiano, Julia; Altermatt, Florian; Massol, François

2017-11-13

Species establish different interactions (e.g. antagonistic, mutualistic) with multiple species, forming multilayer ecological networks. Disentangling network co-structure in multilayer networks is crucial to predict how biodiversity loss may affect the persistence of multispecies assemblages. Existing methods to analyse multilayer networks often fail to consider network co-structure. We present a new method to evaluate the modular co-structure of multilayer networks through the assessment of species degree co-distribution and network module composition. We focus on modular structure because of its high prevalence among ecological networks. We apply our method to two Lepidoptera-plant networks, one describing caterpillar-plant herbivory interactions and one representing adult Lepidoptera nectaring on flowers, thereby possibly pollinating them. More than 50% of the species established either herbivory or visitation interactions, but not both. These species were over-represented among plants and lepidopterans, and were present in most modules in both networks. Similarity in module composition between networks was high but not different from random expectations. Our method clearly delineates the importance of interpreting multilayer module composition similarity in the light of the constraints imposed by network structure to predict the potential indirect effects of species loss through interconnected modular networks.
Fast algorithms for evaluating the stress field of dislocation lines in anisotropic elastic media

NASA Astrophysics Data System (ADS)

Chen, C.; Aubry, S.; Oppelstrup, T.; Arsenlis, A.; Darve, E.

2018-06-01

In dislocation dynamics (DD) simulations, the most computationally intensive step is the evaluation of the elastic interaction forces among dislocation ensembles. Because the pair-wise interaction between dislocations is long-range, this force calculation step can be significantly accelerated by the fast multipole method (FMM). We implemented and compared four different methods in isotropic and anisotropic elastic media: one based on the Taylor series expansion (Taylor FMM), one based on the spherical harmonics expansion (Spherical FMM), one kernel-independent method based on the Chebyshev interpolation (Chebyshev FMM), and a new kernel-independent method that we call the Lagrange FMM. The Taylor FMM is an existing method, used in ParaDiS, one of the most popular DD simulation softwares. The Spherical FMM employs a more compact multipole representation than the Taylor FMM does and is thus more efficient. However, both the Taylor FMM and the Spherical FMM are difficult to derive in anisotropic elastic media because the interaction force is complex and has no closed analytical formula. The Chebyshev FMM requires only being able to evaluate the interaction between dislocations and thus can be applied easily in anisotropic elastic media. But it has a relatively large memory footprint, which limits its usage. The Lagrange FMM was designed to be a memory-efficient black-box method. Various numerical experiments are presented to demonstrate the convergence and the scalability of the four methods.

Flow Cytometric Analysis of Bimolecular Fluorescence Complementation: A High Throughput Quantitative Method to Study Protein-protein Interaction

PubMed Central

Wang, Li; Carnegie, Graeme K.

2013-01-01

Among methods to study protein-protein interaction inside cells, Bimolecular Fluorescence Complementation (BiFC) is relatively simple and sensitive. BiFC is based on the production of fluorescence using two non-fluorescent fragments of a fluorescent protein (Venus, a Yellow Fluorescent Protein variant, is used here). Non-fluorescent Venus fragments (VN and VC) are fused to two interacting proteins (in this case, AKAP-Lbc and PDE4D3), yielding fluorescence due to VN-AKAP-Lbc-VC-PDE4D3 interaction and the formation of a functional fluorescent protein inside cells. BiFC provides information on the subcellular localization of protein complexes and the strength of protein interactions based on fluorescence intensity. However, BiFC analysis using microscopy to quantify the strength of protein-protein interaction is time-consuming and somewhat subjective due to heterogeneity in protein expression and interaction. By coupling flow cytometric analysis with BiFC methodology, the fluorescent BiFC protein-protein interaction signal can be accurately measured for a large quantity of cells in a short time. Here, we demonstrate an application of this methodology to map regions in PDE4D3 that are required for the interaction with AKAP-Lbc. This high throughput methodology can be applied to screening factors that regulate protein-protein interaction. PMID:23979513
Flow cytometric analysis of bimolecular fluorescence complementation: a high throughput quantitative method to study protein-protein interaction.

PubMed

Wang, Li; Carnegie, Graeme K

2013-08-15

Among methods to study protein-protein interaction inside cells, Bimolecular Fluorescence Complementation (BiFC) is relatively simple and sensitive. BiFC is based on the production of fluorescence using two non-fluorescent fragments of a fluorescent protein (Venus, a Yellow Fluorescent Protein variant, is used here). Non-fluorescent Venus fragments (VN and VC) are fused to two interacting proteins (in this case, AKAP-Lbc and PDE4D3), yielding fluorescence due to VN-AKAP-Lbc-VC-PDE4D3 interaction and the formation of a functional fluorescent protein inside cells. BiFC provides information on the subcellular localization of protein complexes and the strength of protein interactions based on fluorescence intensity. However, BiFC analysis using microscopy to quantify the strength of protein-protein interaction is time-consuming and somewhat subjective due to heterogeneity in protein expression and interaction. By coupling flow cytometric analysis with BiFC methodology, the fluorescent BiFC protein-protein interaction signal can be accurately measured for a large quantity of cells in a short time. Here, we demonstrate an application of this methodology to map regions in PDE4D3 that are required for the interaction with AKAP-Lbc. This high throughput methodology can be applied to screening factors that regulate protein-protein interaction.
Modelling and simulation of particle-particle interaction in a magnetophoretic bio-separation chip

NASA Astrophysics Data System (ADS)

Alam, Manjurul; Golozar, Matin; Darabi, Jeff

2018-04-01

A Lagrangian particle trajectory model is developed to predict the interaction between cell-bead particle complexes and to track their trajectories in a magnetophoretic bio-separation chip. Magnetic flux gradients are simulated in the OpenFOAM CFD software and imported into MATLAB to obtain the trapping lengths and trajectories of the particles. A connector vector is introduced to calculate the interaction force between cell-bead complexes as they flow through a microfluidic device. The interaction force calculations are performed for cases where the connector vector is parallel, perpendicular, and at an angle of 45° with the applied magnetic field. The trajectories of the particles are simulated by solving a system of eight ordinary differential equations using a fourth order Runge-Kutta method. The model is then used to study the effects of geometric positions and angles of the connector vector between the particles as well as the cell size, number of beads per cell, and flow rate on the interaction force and trajectories of the particles. The results show that the interaction forces may be attractive or repulsive, depending on the orientation of the connector vector distance between the particle complexes and the applied magnetic field. When the interaction force is attractive, the particles are observed to merge and trap sooner than a single particle, whereas a repulsive interaction force has little or no effect on the trapping length.
Interaction entropy for protein-protein binding.

PubMed

Sun, Zhaoxi; Yan, Yu N; Yang, Maoyou; Zhang, John Z H

2017-03-28

Protein-protein interactions are at the heart of signal transduction and are central to the function of protein machine in biology. The highly specific protein-protein binding is quantitatively characterized by the binding free energy whose accurate calculation from the first principle is a grand challenge in computational biology. In this paper, we show how the interactionentropy approach, which was recently proposed for protein-ligand binding free energy calculation, can be applied to computing the entropic contribution to the protein-protein binding free energy. Explicit theoretical derivation of the interactionentropy approach for protein-protein interaction system is given in detail from the basic definition. Extensive computational studies for a dozen realistic protein-protein interaction systems are carried out using the present approach and comparisons of the results for these protein-protein systems with those from the standard normal mode method are presented. Analysis of the present method for application in protein-protein binding as well as the limitation of the method in numerical computation is discussed. Our study and analysis of the results provided useful information for extracting correct entropic contribution in protein-protein binding from molecular dynamics simulations.
Investigation of laser-tissue interaction in medicine by means of laser spectroscopic measurements

NASA Astrophysics Data System (ADS)

Lademann, Juergen; Weigmann, Hans-Juergen

1995-01-01

Toxic and carcinogenic substances were produced during laser application in medicine for the cutting and evaporation of tissue. The laser smoke presents a danger potential for the medical staff and the patients. The laser tissue interaction process was investigated by means of laser spectroscopic measurements which give the possibility of measuring metastable molecular states directly as a prerequisite to understand and to influence fundamental laser tissue interaction processes in order to reduce the amount of harmful chemicals. Highly excited atomic and molecular states and free radicals (CN, OH, C2, CH, CH2) have been detected applying spontaneous and laser induced fluorescence methods. It was found that the formation of harmful substances in the laser plumes can be reduced significantly by optimization of the surrounding gas atmosphere. A high content of oxygen or water in the interaction zone has been found, in agreement with the results of classical and analytical methods, as a suitable way to decrease pollutant emission. The experimental methods and the principal results are applicable not only in laser medicine but in laser material treatment generally.
Estimating and testing interactions when explanatory variables are subject to non-classical measurement error.

PubMed

Murad, Havi; Kipnis, Victor; Freedman, Laurence S

2016-10-01

Assessing interactions in linear regression models when covariates have measurement error (ME) is complex.We previously described regression calibration (RC) methods that yield consistent estimators and standard errors for interaction coefficients of normally distributed covariates having classical ME. Here we extend normal based RC (NBRC) and linear RC (LRC) methods to a non-classical ME model, and describe more efficient versions that combine estimates from the main study and internal sub-study. We apply these methods to data from the Observing Protein and Energy Nutrition (OPEN) study. Using simulations we show that (i) for normally distributed covariates efficient NBRC and LRC were nearly unbiased and performed well with sub-study size ≥200; (ii) efficient NBRC had lower MSE than efficient LRC; (iii) the naïve test for a single interaction had type I error probability close to the nominal significance level, whereas efficient NBRC and LRC were slightly anti-conservative but more powerful; (iv) for markedly non-normal covariates, efficient LRC yielded less biased estimators with smaller variance than efficient NBRC. Our simulations suggest that it is preferable to use: (i) efficient NBRC for estimating and testing interaction effects of normally distributed covariates and (ii) efficient LRC for estimating and testing interactions for markedly non-normal covariates. © The Author(s) 2013.
Assessing the impact of natural policy experiments on socioeconomic inequalities in health: how to apply commonly used quantitative analytical methods?

PubMed

Hu, Yannan; van Lenthe, Frank J; Hoffmann, Rasmus; van Hedel, Karen; Mackenbach, Johan P

2017-04-20

The scientific evidence-base for policies to tackle health inequalities is limited. Natural policy experiments (NPE) have drawn increasing attention as a means to evaluating the effects of policies on health. Several analytical methods can be used to evaluate the outcomes of NPEs in terms of average population health, but it is unclear whether they can also be used to assess the outcomes of NPEs in terms of health inequalities. The aim of this study therefore was to assess whether, and to demonstrate how, a number of commonly used analytical methods for the evaluation of NPEs can be applied to quantify the effect of policies on health inequalities. We identified seven quantitative analytical methods for the evaluation of NPEs: regression adjustment, propensity score matching, difference-in-differences analysis, fixed effects analysis, instrumental variable analysis, regression discontinuity and interrupted time-series. We assessed whether these methods can be used to quantify the effect of policies on the magnitude of health inequalities either by conducting a stratified analysis or by including an interaction term, and illustrated both approaches in a fictitious numerical example. All seven methods can be used to quantify the equity impact of policies on absolute and relative inequalities in health by conducting an analysis stratified by socioeconomic position, and all but one (propensity score matching) can be used to quantify equity impacts by inclusion of an interaction term between socioeconomic position and policy exposure. Methods commonly used in economics and econometrics for the evaluation of NPEs can also be applied to assess the equity impact of policies, and our illustrations provide guidance on how to do this appropriately. The low external validity of results from instrumental variable analysis and regression discontinuity makes these methods less desirable for assessing policy effects on population-level health inequalities. Increased use of the methods in social epidemiology will help to build an evidence base to support policy making in the area of health inequalities.
Improving semi-automated segmentation by integrating learning with active sampling

NASA Astrophysics Data System (ADS)

Huo, Jing; Okada, Kazunori; Brown, Matthew

2012-02-01

Interactive segmentation algorithms such as GrowCut usually require quite a few user interactions to perform well, and have poor repeatability. In this study, we developed a novel technique to boost the performance of the interactive segmentation method GrowCut involving: 1) a novel "focused sampling" approach for supervised learning, as opposed to conventional random sampling; 2) boosting GrowCut using the machine learned results. We applied the proposed technique to the glioblastoma multiforme (GBM) brain tumor segmentation, and evaluated on a dataset of ten cases from a multiple center pharmaceutical drug trial. The results showed that the proposed system has the potential to reduce user interaction while maintaining similar segmentation accuracy.
NASA EOSDIS: Enabling Science by Improving User Knowledge

NASA Technical Reports Server (NTRS)

Lindsay, Francis; Brennan, Jennifer; Blumenfeld, Joshua

2016-01-01

Lessons learned and impacts of applying these newer methods are explained and include several examples from our current efforts such as the interactive, on-line webinars focusing on data discovery and access including tool usage, informal and informative data chats with data experts across our EOSDIS community, data user profile interviews with scientists actively using EOSDIS data in their research, and improved conference and meeting interactions via EOSDIS data interactively used during hyper-wall talks and Worldview application. The suite of internet-based, interactive capabilities and technologies has allowed our project to expand our user community by making the data and applications from numerous Earth science missions more engaging, approachable and meaningful.
Interaction of albumins and heparinoids investigated by affinity capillary electrophoresis and free flow electrophoresis.

PubMed

Mozafari, Mona; El Deeb, Sami; Krull, Friederike; Wildgruber, Robert; Weber, Gerhard; Reiter, Christian G; Wätzig, Hermann

2018-02-01

A fast and precise affinity capillary electrophoresis (ACE) method has been applied to investigate the interactions between two serum albumins (HSA and BSA) and heparinoids. Furthermore, different free flow electrophoresis methods were developed to separate the species which appears owing to interaction of albumins with pentosan polysulfate sodium (PPS) under different experimental conditions. For ACE experiments, the normalized mobility ratios (∆R/R f ), which provided information about the binding strength and the overall charge of the protein-ligand complex, were used to evaluate the binding affinities. ACE experiments were performed at two different temperatures (23 and 37°C). Both BSA and HSA interact more strongly with PPS than with unfractionated and low molecular weight heparins. For PPS, the interactions can already be observed at low mg/L concentrations (3 mg/L), and saturation is already obtained at approximately 20 mg/L. Unfractionated heparin showed almost no interactions with BSA at 23°C, but weak interactions at 37°C at higher heparin concentrations. The additional signals also appeared at higher concentrations at 37°C. Nevertheless, in most cases the binding data were similar at both temperatures. Furthermore, HSA showed a characteristic splitting in two peaks especially after interacting with PPS, which is probably attributable to the formation of two species or conformational change of HSA after interacting with PPS. The free flow electrophoresis methods have confirmed and completed the ACE experiments. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Determination of nonlinear genetic architecture using compressed sensing.

PubMed

Ho, Chiu Man; Hsu, Stephen D H

2015-01-01

One of the fundamental problems of modern genomics is to extract the genetic architecture of a complex trait from a data set of individual genotypes and trait values. Establishing this important connection between genotype and phenotype is complicated by the large number of candidate genes, the potentially large number of causal loci, and the likely presence of some nonlinear interactions between different genes. Compressed Sensing methods obtain solutions to under-constrained systems of linear equations. These methods can be applied to the problem of determining the best model relating genotype to phenotype, and generally deliver better performance than simply regressing the phenotype against each genetic variant, one at a time. We introduce a Compressed Sensing method that can reconstruct nonlinear genetic models (i.e., including epistasis, or gene-gene interactions) from phenotype-genotype (GWAS) data. Our method uses L1-penalized regression applied to nonlinear functions of the sensing matrix. The computational and data resource requirements for our method are similar to those necessary for reconstruction of linear genetic models (or identification of gene-trait associations), assuming a condition of generalized sparsity, which limits the total number of gene-gene interactions. An example of a sparse nonlinear model is one in which a typical locus interacts with several or even many others, but only a small subset of all possible interactions exist. It seems plausible that most genetic architectures fall in this category. We give theoretical arguments suggesting that the method is nearly optimal in performance, and demonstrate its effectiveness on broad classes of nonlinear genetic models using simulated human genomes and the small amount of currently available real data. A phase transition (i.e., dramatic and qualitative change) in the behavior of the algorithm indicates when sufficient data is available for its successful application. Our results indicate that predictive models for many complex traits, including a variety of human disease susceptibilities (e.g., with additive heritability h (2)∼0.5), can be extracted from data sets comprised of n ⋆∼100s individuals, where s is the number of distinct causal variants influencing the trait. For example, given a trait controlled by ∼10 k loci, roughly a million individuals would be sufficient for application of the method.
Genes involved in host-parasite interactions can be revealed by their correlated expression.

PubMed

Reid, Adam James; Berriman, Matthew

2013-02-01

Molecular interactions between a parasite and its host are key to the ability of the parasite to enter the host and persist. Our understanding of the genes and proteins involved in these interactions is limited. To better understand these processes it would be advantageous to have a range of methods to predict pairs of genes involved in such interactions. Correlated gene expression profiles can be used to identify molecular interactions within a species. Here we have extended the concept to different species, showing that genes with correlated expression are more likely to encode proteins, which directly or indirectly participate in host-parasite interaction. We go on to examine our predictions of molecular interactions between the malaria parasite and both its mammalian host and insect vector. Our approach could be applied to study any interaction between species, for example, between a host and its parasites or pathogens, but also symbiotic and commensal pairings.
Verification, Validation, and Solution Quality in Computational Physics: CFD Methods Applied to Ice Sheet Physics

NASA Technical Reports Server (NTRS)

Thompson, David E.

2005-01-01

Procedures and methods for veri.cation of coding algebra and for validations of models and calculations used in the aerospace computational fluid dynamics (CFD) community would be ef.cacious if used by the glacier dynamics modeling community. This paper presents some of those methods, and how they might be applied to uncertainty management supporting code veri.cation and model validation for glacier dynamics. The similarities and differences between their use in CFD analysis and the proposed application of these methods to glacier modeling are discussed. After establishing sources of uncertainty and methods for code veri.cation, the paper looks at a representative sampling of veri.cation and validation efforts that are underway in the glacier modeling community, and establishes a context for these within an overall solution quality assessment. Finally, a vision of a new information architecture and interactive scienti.c interface is introduced and advocated.
A computational method for the coupled solution of reaction-diffusion equations on evolving domains and manifolds: Application to a model of cell migration and chemotaxis.

PubMed

MacDonald, G; Mackenzie, J A; Nolan, M; Insall, R H

2016-03-15

In this paper, we devise a moving mesh finite element method for the approximate solution of coupled bulk-surface reaction-diffusion equations on an evolving two dimensional domain. Fundamental to the success of the method is the robust generation of bulk and surface meshes. For this purpose, we use a novel moving mesh partial differential equation (MMPDE) approach. The developed method is applied to model problems with known analytical solutions; these experiments indicate second-order spatial and temporal accuracy. Coupled bulk-surface problems occur frequently in many areas; in particular, in the modelling of eukaryotic cell migration and chemotaxis. We apply the method to a model of the two-way interaction of a migrating cell in a chemotactic field, where the bulk region corresponds to the extracellular region and the surface to the cell membrane.
A fictitious domain method for fluid/solid interaction applied to the plate folding over the 660 Km depth boundary.

NASA Astrophysics Data System (ADS)

Cerpa, Nestor; Hassani, Riad; Gerbault, Muriel

2014-05-01

A large variety of geodynamical problems involve a mechanical system where a competent body is embedded in a more deformable medium, and hence they can be viewed as belonging to the field of solid/fluid interaction.The lithosphere/asthenosphere interaction in subduction zones is among those kind of problems which are generally difficult to tackle numerically since the immersed (solid) body can be geometrically complex and the surrounding (fluid) medium can thus undergo large deformation. Our work presents a new numerical approach for the study of subduction zones. The lithosphere is modeled as a Maxwell viscoelastic body sinking in the viscous asthenosphere. Both domains are discretized by the Finite Element Method (FEM) and we use a staggered coupling method. The interaction is provided by a non-matching interface method called the Fictitious Domain Method (FDM). We have validated this method with some 2-D benchmarks and examples. Through this numerical coupling method we aim at studying the effect of mantle viscosity on the cyclicity of slab folding on the 660 km depth discontinuity approximated as an impenetrable barrier. Depending on the kinematics condition imposed to the overriding and subducting plates, analog and numerical models have previously shown that cyclicity occurs. The viscosity of the asthenosphere (taken as an isoviscous or a double viscosity-layer fluid) impacts on folding cyclicity and consequently on the slab's dip as well as the stress regime of the overriding plate. In particular, applying far-field plate velocities corresponding to those of the South-American and Nazca plates at present, (4.3 cm/yr and 2.9 cm/yr respectively), we obtain periodic slab folding which is consistent with magmatism and sedimentalogical records. These data report cycles in orogenic growth of the order of 30-40 Myrs, a period that we reproduce when the mantle viscosity ranges in between 3 and 5 x 1020 Pa.s. Moreover, we reproduce episodic development of horizontal subduction induced by cyclic folding and, hence, propose a new explanation for episodes of flat subduction under the South-American plate. We show also preliminary results of 3-D subduction.
MPQ-cytometry: a magnetism-based method for quantification of nanoparticle-cell interactions

NASA Astrophysics Data System (ADS)

Shipunova, V. O.; Nikitin, M. P.; Nikitin, P. I.; Deyev, S. M.

2016-06-01

Precise quantification of interactions between nanoparticles and living cells is among the imperative tasks for research in nanobiotechnology, nanotoxicology and biomedicine. To meet the challenge, a rapid method called MPQ-cytometry is developed, which measures the integral non-linear response produced by magnetically labeled nanoparticles in a cell sample with an original magnetic particle quantification (MPQ) technique. MPQ-cytometry provides a sensitivity limit 0.33 ng of nanoparticles and is devoid of a background signal present in many label-based assays. Each measurement takes only a few seconds, and no complicated sample preparation or data processing is required. The capabilities of the method have been demonstrated by quantification of interactions of iron oxide nanoparticles with eukaryotic cells. The total amount of targeted nanoparticles that specifically recognized the HER2/neu oncomarker on the human cancer cell surface was successfully measured, the specificity of interaction permitting the detection of HER2/neu positive cells in a cell mixture. Moreover, it has been shown that MPQ-cytometry analysis of a HER2/neu-specific iron oxide nanoparticle interaction with six cell lines of different tissue origins quantitatively reflects the HER2/neu status of the cells. High correlation of MPQ-cytometry data with those obtained by three other commonly used in molecular and cell biology methods supports consideration of this method as a prospective alternative for both quantifying cell-bound nanoparticles and estimating the expression level of cell surface antigens. The proposed method does not require expensive sophisticated equipment or highly skilled personnel and it can be easily applied for rapid diagnostics, especially under field conditions.Precise quantification of interactions between nanoparticles and living cells is among the imperative tasks for research in nanobiotechnology, nanotoxicology and biomedicine. To meet the challenge, a rapid method called MPQ-cytometry is developed, which measures the integral non-linear response produced by magnetically labeled nanoparticles in a cell sample with an original magnetic particle quantification (MPQ) technique. MPQ-cytometry provides a sensitivity limit 0.33 ng of nanoparticles and is devoid of a background signal present in many label-based assays. Each measurement takes only a few seconds, and no complicated sample preparation or data processing is required. The capabilities of the method have been demonstrated by quantification of interactions of iron oxide nanoparticles with eukaryotic cells. The total amount of targeted nanoparticles that specifically recognized the HER2/neu oncomarker on the human cancer cell surface was successfully measured, the specificity of interaction permitting the detection of HER2/neu positive cells in a cell mixture. Moreover, it has been shown that MPQ-cytometry analysis of a HER2/neu-specific iron oxide nanoparticle interaction with six cell lines of different tissue origins quantitatively reflects the HER2/neu status of the cells. High correlation of MPQ-cytometry data with those obtained by three other commonly used in molecular and cell biology methods supports consideration of this method as a prospective alternative for both quantifying cell-bound nanoparticles and estimating the expression level of cell surface antigens. The proposed method does not require expensive sophisticated equipment or highly skilled personnel and it can be easily applied for rapid diagnostics, especially under field conditions. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr03507h
Symmetric Epistasis Estimation (SEE) and its application to dissecting interaction map of Plasmodium falciparum.

PubMed

Huang, Yang; Siwo, Geoffrey; Wuchty, Stefan; Ferdig, Michael T; Przytycka, Teresa M

2012-04-01

It is being increasingly recognized that many important phenotypic traits, including various diseases, are governed by a combination of weak genetic effects and their interactions. While the detection of epistatic interactions that involve a non-additive effect of two loci on a quantitative trait is particularly challenging, this interaction type is fundamental for the understanding of genome organization and gene regulation. However, current methods that detect epistatic interactions typically rely on the existence of a strong primary effect, considerably limiting the sensitivity of the search. To fill this gap, we developed a new method, SEE (Symmetric Epistasis Estimation), allowing the genome-wide detection of epistatic interactions without the need for a strong primary effect. We applied our approach to progeny crosses of the human malaria parasite P. falciparum and S. cerevisiae. We found an abundance of epistatic interactions in the parasite and a much smaller number of such interactions in yeast. The genome of P. falciparum also harboured several epistatic interaction hotspots that putatively play a role in drug resistance mechanisms. The abundance of observed epistatic interactions might suggest a mechanism of compensation for the extremely limited repertoire of transcription factors. Interestingly, epistatic interaction hotspots were associated with elevated levels of linkage disequilibrium, an observation that suggests selection pressure acting on P. falciparum, potentially reflecting host-pathogen interactions or drug-induced selection.
Predicting Protein Function by Genomic Context: Quantitative Evaluation and Qualitative Inferences

PubMed Central

Huynen, Martijn; Snel, Berend; Lathe, Warren; Bork, Peer

2000-01-01

Various new methods have been proposed to predict functional interactions between proteins based on the genomic context of their genes. The types of genomic context that they use are Type I: the fusion of genes; Type II: the conservation of gene-order or co-occurrence of genes in potential operons; and Type III: the co-occurrence of genes across genomes (phylogenetic profiles). Here we compare these types for their coverage, their correlations with various types of functional interaction, and their overlap with homology-based function assignment. We apply the methods to Mycoplasma genitalium, the standard benchmarking genome in computational and experimental genomics. Quantitatively, conservation of gene order is the technique with the highest coverage, applying to 37% of the genes. By combining gene order conservation with gene fusion (6%), the co-occurrence of genes in operons in absence of gene order conservation (8%), and the co-occurrence of genes across genomes (11%), significant context information can be obtained for 50% of the genes (the categories overlap). Qualitatively, we observe that the functional interactions between genes are stronger as the requirements for physical neighborhood on the genome are more stringent, while the fraction of potential false positives decreases. Moreover, only in cases in which gene order is conserved in a substantial fraction of the genomes, in this case six out of twenty-five, does a single type of functional interaction (physical interaction) clearly dominate (>80%). In other cases, complementary function information from homology searches, which is available for most of the genes with significant genomic context, is essential to predict the type of interaction. Using a combination of genomic context and homology searches, new functional features can be predicted for 10% of M. genitalium genes. PMID:10958638
Measurement of Vehicle-Bridge-Interaction force using dynamic tire pressure monitoring

NASA Astrophysics Data System (ADS)

Chen, Zhao; Xie, Zhipeng; Zhang, Jian

2018-05-01

The Vehicle-Bridge-Interaction (VBI) force, i.e., the normal contact force of a tire, is a key component in the VBI mechanism. The VBI force measurement can facilitate experimental studies of the VBI as well as input-output bridge structural identification. This paper introduces an innovative method for calculating the interaction force by using dynamic tire pressure monitoring. The core idea of the proposed method combines the ideal gas law and a basic force model to build a relationship between the tire pressure and the VBI force. Then, unknown model parameters are identified by the Extended Kalman Filter using calibration data. A signal filter based on the wavelet analysis is applied to preprocess the effect that the tire rotation has on the pressure data. Two laboratory tests were conducted to check the proposed method's validity. The effects of different road irregularities, loads and forward velocities were studied. Under the current experiment setting, the proposed method was robust to different road irregularities, and the increase in load and velocity benefited the performance of the proposed method. A high-speed test further supported the use of this method in rapid bridge tests. Limitations of the derived theories and experiment were also discussed.
Prediction of the interaction between a simple moving vehicle and an infinite periodically supported rail - Green's functions approach

NASA Astrophysics Data System (ADS)

Mazilu, Traian

2010-09-01

This paper herein describes the interaction between a simple moving vehicle and an infinite periodically supported rail, in order to signalise the basic features of the vehicle/track vibration behaviour in general, and wheel/rail vibration, in particular. The rail is modelled as an infinite Timoshenko beam resting on semi-sleepers via three-directional rail pads and ballast. The time-domain analysis was performed applying Green's matrix of the track method. This method allows taking into account the nonlinearities of the wheel/rail contact and the Doppler effect. The numerical analysis is dedicated to the wheel/rail response due to two types of excitation: the steady-state interaction and rail irregularities. The study points out to certain aspects regarding the parametric resonance, the amplitude-modulated vibration due to corrugation and the Doppler effect.

Interactive Reference Point Procedure Based on the Conic Scalarizing Function

PubMed Central

2014-01-01

In multiobjective optimization methods, multiple conflicting objectives are typically converted into a single objective optimization problem with the help of scalarizing functions. The conic scalarizing function is a general characterization of Benson proper efficient solutions of non-convex multiobjective problems in terms of saddle points of scalar Lagrangian functions. This approach preserves convexity. The conic scalarizing function, as a part of a posteriori or a priori methods, has successfully been applied to several real-life problems. In this paper, we propose a conic scalarizing function based interactive reference point procedure where the decision maker actively takes part in the solution process and directs the search according to her or his preferences. An algorithmic framework for the interactive solution of multiple objective optimization problems is presented and is utilized for solving some illustrative examples. PMID:24723795
RPYFMM: Parallel adaptive fast multipole method for Rotne-Prager-Yamakawa tensor in biomolecular hydrodynamics simulations

NASA Astrophysics Data System (ADS)

Guan, W.; Cheng, X.; Huang, J.; Huber, G.; Li, W.; McCammon, J. A.; Zhang, B.

2018-06-01

RPYFMM is a software package for the efficient evaluation of the potential field governed by the Rotne-Prager-Yamakawa (RPY) tensor interactions in biomolecular hydrodynamics simulations. In our algorithm, the RPY tensor is decomposed as a linear combination of four Laplace interactions, each of which is evaluated using the adaptive fast multipole method (FMM) (Greengard and Rokhlin, 1997) where the exponential expansions are applied to diagonalize the multipole-to-local translation operators. RPYFMM offers a unified execution on both shared and distributed memory computers by leveraging the DASHMM library (DeBuhr et al., 2016, 2018). Preliminary numerical results show that the interactions for a molecular system of 15 million particles (beads) can be computed within one second on a Cray XC30 cluster using 12,288 cores, while achieving approximately 54% strong-scaling efficiency.
Model Checking for Verification of Interactive Health IT Systems

PubMed Central

Butler, Keith A.; Mercer, Eric; Bahrami, Ali; Tao, Cui

2015-01-01

Rigorous methods for design and verification of health IT systems have lagged far behind their proliferation. The inherent technical complexity of healthcare, combined with the added complexity of health information technology makes their resulting behavior unpredictable and introduces serious risk. We propose to mitigate this risk by formalizing the relationship between HIT and the conceptual work that increasingly typifies modern care. We introduce new techniques for modeling clinical workflows and the conceptual products within them that allow established, powerful modeling checking technology to be applied to interactive health IT systems. The new capability can evaluate the workflows of a new HIT system performed by clinicians and computers to improve safety and reliability. We demonstrate the method on a patient contact system to demonstrate model checking is effective for interactive systems and that much of it can be automated. PMID:26958166
Results of EAS characteristics calculations in the framework of the universal hadronic interaction model NEXUS

NASA Astrophysics Data System (ADS)

Kalmykov, N. N.; Ostapchenko, S. S.; Werner, K.

An extensive air shower (EAS) calculation scheme based on cascade equations and some EAS characteristics for energies 1014 -1017 eV are presented. The universal hadronic interaction model NEXUS is employed to provide the necessary data concerning hadron-air collisions. The influence of model assumptions on the longitudinal EAS development is discussed in the framework of the NEXUS and QGSJET models. Applied to EAS simulations, perspectives of combined Monte Carlo and numerical methods are considered.
Interaction Dynamics Between a Flexible Rotor and an Auxiliary Clearance Bearing

NASA Technical Reports Server (NTRS)

Lawen, James L., Jr.; Flowers, George T.

1996-01-01

This study investigates the application of synchronous interaction dynamics methodology to the design of auxiliary bearing systems. The technique is applied to a flexible rotor system and comparisons are made between the behavior predicted by this analysis method and the observed simulation response characteristics. Of particular interest is the influence of coupled shaft/bearing vibration modes on rotordynamical behavior. Experimental studies are also perFormed to validate the simulation results and provide insight into the expected behavior of such a system.
Activities report in nuclear physics and particle acceleration

NASA Astrophysics Data System (ADS)

Jansen, J. F. W.; Demeijer, R. J.

1984-04-01

Research on nuclear resonances; charge transfer; breakup of light and heavy ions; reaction mechanisms of heavy ion collisions; high-spin states; and fundamental symmetries in weak interactions are outlined. Group theoretical methods applied to supersymmetries; phenomenological description of rotation-vibration coupling; a microscopic theory of collective variables; the binding energy of hydrogen adsorbed on stepped platinium; and single electron capture are discussed. Isotopes for nuclear medicine, for off-line nuclear spectroscopy work, and for the study of hyperfine interactions were produced.
Multifactor dimensionality reduction reveals a three-locus epistatic interaction associated with susceptibility to pulmonary tuberculosis.

PubMed

Collins, Ryan L; Hu, Ting; Wejse, Christian; Sirugo, Giorgio; Williams, Scott M; Moore, Jason H

2013-02-18

Identifying high-order genetics associations with non-additive (i.e. epistatic) effects in population-based studies of common human diseases is a computational challenge. Multifactor dimensionality reduction (MDR) is a machine learning method that was designed specifically for this problem. The goal of the present study was to apply MDR to mining high-order epistatic interactions in a population-based genetic study of tuberculosis (TB). The study used a previously published data set consisting of 19 candidate single-nucleotide polymorphisms (SNPs) in 321 pulmonary TB cases and 347 healthy controls from Guniea-Bissau in Africa. The ReliefF algorithm was applied first to generate a smaller set of the five most informative SNPs. MDR with 10-fold cross-validation was then applied to look at all possible combinations of two, three, four and five SNPs. The MDR model with the best testing accuracy (TA) consisted of SNPs rs2305619, rs187084, and rs11465421 (TA = 0.588) in PTX3, TLR9 and DC-Sign, respectively. A general 1000-fold permutation test of the null hypothesis of no association confirmed the statistical significance of the model (p = 0.008). An additional 1000-fold permutation test designed specifically to test the linear null hypothesis that the association effects are only additive confirmed the presence of non-additive (i.e. nonlinear) or epistatic effects (p = 0.013). An independent information-gain measure corroborated these results with a third-order epistatic interaction that was stronger than any lower-order associations. We have identified statistically significant evidence for a three-way epistatic interaction that is associated with susceptibility to TB. This interaction is stronger than any previously described one-way or two-way associations. This study highlights the importance of using machine learning methods that are designed to embrace, rather than ignore, the complexity of common diseases such as TB. We recommend future studies of the genetics of TB take into account the possibility that high-order epistatic interactions might play an important role in disease susceptibility.
Remote sensing applied to agriculture: Basic principles, methodology, and applications

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Mendonca, F. J.

1981-01-01

The general principles of remote sensing techniques as applied to agriculture and the methods of data analysis are described. the theoretical spectral responses of crops; reflectance, transmittance, and absorbtance of plants; interactions of plants and soils with reflectance energy; leaf morphology; and factors which affect the reflectance of vegetation cover are dicussed. The methodologies of visual and computer-aided analyses of LANDSAT data are presented. Finally, a case study wherein infrared film was used to detect crop anomalies and other data applications are described.
Semi-discrete Galerkin solution of the compressible boundary-layer equations with viscous-inviscid interaction

NASA Technical Reports Server (NTRS)

Day, Brad A.; Meade, Andrew J., Jr.

1993-01-01

A semi-discrete Galerkin (SDG) method is under development to model attached, turbulent, and compressible boundary layers for transonic airfoil analysis problems. For the boundary-layer formulation the method models the spatial variable normal to the surface with linear finite elements and the time-like variable with finite differences. A Dorodnitsyn transformed system of equations is used to bound the infinite spatial domain thereby providing high resolution near the wall and permitting the use of a uniform finite element grid which automatically follows boundary-layer growth. The second-order accurate Crank-Nicholson scheme is applied along with a linearization method to take advantage of the parabolic nature of the boundary-layer equations and generate a non-iterative marching routine. The SDG code can be applied to any smoothly-connected airfoil shape without modification and can be coupled to any inviscid flow solver. In this analysis, a direct viscous-inviscid interaction is accomplished between the Euler and boundary-layer codes through the application of a transpiration velocity boundary condition. Results are presented for compressible turbulent flow past RAE 2822 and NACA 0012 airfoils at various freestream Mach numbers, Reynolds numbers, and angles of attack.
Application of factorial designs to study factors involved in the determination of aldehydes present in beer by on-fiber derivatization in combination with gas chromatography and mass spectrometry.

PubMed

Carrillo, Génesis; Bravo, Adriana; Zufall, Carsten

2011-05-11

With the aim of studying the factors involved in on-fiber derivatization of Strecker aldehydes, furfural, and (E)-2-nonenal with O-(2,3,4,5,6-pentafluorobenzyl)hydroxylamine in beer, factorial designs were applied. The effect of the temperature, time, and NaCl addition on the analytes' derivatization/extraction efficiency was studied through a factorial 2(3) randomized-block design; all of the factors and their interactions were significant at the 95% confidence level for most of the analytes. The effect of temperature and its interactions separated the analytes in two groups. However, a single sampling condition was selected that optimized response for most aldehydes. The resulting method, combining on-fiber derivatization with gas chromatography-mass spectrometry, was validated. Limits of detections were between 0.015 and 1.60 μg/L, and relative standard deviations were between 1.1 and 12.2%. The efficacy of the internal standardization method was confirmed by recovery percentage (73-117%). The method was applied to the determination of aldehydes in fresh beer and after storage at 28 °C.
Functional connectivity analysis of the neural bases of emotion regulation: A comparison of independent component method with density-based k-means clustering method.

PubMed

Zou, Ling; Guo, Qian; Xu, Yi; Yang, Biao; Jiao, Zhuqing; Xiang, Jianbo

2016-04-29

Functional magnetic resonance imaging (fMRI) is an important tool in neuroscience for assessing connectivity and interactions between distant areas of the brain. To find and characterize the coherent patterns of brain activity as a means of identifying brain systems for the cognitive reappraisal of the emotion task, both density-based k-means clustering and independent component analysis (ICA) methods can be applied to characterize the interactions between brain regions involved in cognitive reappraisal of emotion. Our results reveal that compared with the ICA method, the density-based k-means clustering method provides a higher sensitivity of polymerization. In addition, it is more sensitive to those relatively weak functional connection regions. Thus, the study concludes that in the process of receiving emotional stimuli, the relatively obvious activation areas are mainly distributed in the frontal lobe, cingulum and near the hypothalamus. Furthermore, density-based k-means clustering method creates a more reliable method for follow-up studies of brain functional connectivity.
Dynamical Symmetry Breaking in Models of Spinor Fields with Quartic Interactions in (1+1) Dimensions

NASA Astrophysics Data System (ADS)

Wang, Rhung-tai; Ni, Guang-jiong

1982-07-01

A nonperturbative method, namely, variational method together with canonical transformations, is developed to study dynamical symmetry breaking. This method has been applied in the models of two dimensional massless fermion fields with quartic interactions. The results imply that the mechanism of dynamical symmetry breaking bears some analogy to the phenomenon of superconductivity. The new vacuum \\mid \\tilde{0}> is just a relativistic BCS groundstate, In this vacuum \\mid ^≈0>, we can observe a quasi-particle with mass "MF" Furthermore, correlative vacuum \\mid ^≈0> exists and the mesons emerge with masses "O" and "2MF". It is also shown that dynamical symmetry breaking always occurs in the models with infrared slavery and asymptotic freedom, while it is meaningless to discuss dynamical symmetry breaking in infrared stable theory.
A multilevel control system for the large space telescope. [numerical analysis/optimal control

NASA Technical Reports Server (NTRS)

Siljak, D. D.; Sundareshan, S. K.; Vukcevic, M. B.

1975-01-01

A multilevel scheme was proposed for control of Large Space Telescope (LST) modeled by a three-axis-six-order nonlinear equation. Local controllers were used on the subsystem level to stabilize motions corresponding to the three axes. Global controllers were applied to reduce (and sometimes nullify) the interactions among the subsystems. A multilevel optimization method was developed whereby local quadratic optimizations were performed on the subsystem level, and global control was again used to reduce (nullify) the effect of interactions. The multilevel stabilization and optimization methods are presented as general tools for design and then used in the design of the LST Control System. The methods are entirely computerized, so that they can accommodate higher order LST models with both conceptual and numerical advantages over standard straightforward design techniques.
The Mindful School: How To Assess Thoughtful Outcomes. K-College.

ERIC Educational Resources Information Center

Burke, Kay

Authentic assessment, as referred to in this book, encompasses meaningful tasks, positive interaction between teachers and students, methods that emphasize higher-order thinking skills, and strategies that allow students to plan, monitor, and evaluate their own learning. Most important, authentic assessment means helping students to apply and…
Learning to See the (W)holes

ERIC Educational Resources Information Center

Burns, Barbara A.; Jordan, Thomas M.

2006-01-01

Business managers are faced with complex decisions involving a wide range of issues--technical, social, environmental, and financial--and their interaction. Our education system focuses heavily on presenting structured problems and teaching students to apply a set of tools or methods to solve these problems. Yet the most difficult thing to teach…
Development Research of a Teachers' Educational Performance Support System: The Practices of Design, Development, and Evaluation

ERIC Educational Resources Information Center

Hung, Wei-Chen; Smith, Thomas J.; Harris, Marian S.; Lockard, James

2010-01-01

This study adopted design and development research methodology (Richey & Klein, "Design and development research: Methods, strategies, and issues," 2007) to systematically investigate the process of applying instructional design principles, human-computer interaction, and software engineering to a performance support system (PSS) for behavior…
Eyetracking Methodology in SCMC: A Tool for Empowering Learning and Teaching

ERIC Educational Resources Information Center

Stickler, Ursula; Shi, Lijing

2017-01-01

Computer-assisted language learning, or CALL, is an interdisciplinary area of research, positioned between science and social science, computing and education, linguistics and applied linguistics. This paper argues that by appropriating methods originating in some areas of CALL-related research, for example human-computer interaction (HCI) or…
Learning by Doing: Using an Online Simulation Game in an International Relations Course

ERIC Educational Resources Information Center

Epley, Jennifer

2016-01-01

Integrating interactive learning activities into undergraduate courses is one method for increasing student interest, engagement, and skills development. Online simulation games in particular offer students the unique applied opportunity to "learn by doing" in a virtual space to further their overall knowledge base and critical thinking…
Mimicking multivalent protein-carbohydrate interactions for monitoring the glucosamine level in biological fluids and pharmaceutical tablets.

PubMed

Dey, Nilanjan; Bhattacharya, Santanu

2017-05-11

An easily synthesizable probe has been employed for dual mode sensing of glucosamine in pure water. The method was also applied for glucosamine estimation in blood serum samples and pharmaceutical tablets. Further, selective detection of glucosamine was also achieved using portable color strips.
Meta-analysis identifies gene-by-environment interactions as demonstrated in a study of 4,965 mice.

PubMed

Kang, Eun Yong; Han, Buhm; Furlotte, Nicholas; Joo, Jong Wha J; Shih, Diana; Davis, Richard C; Lusis, Aldons J; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study.

Meta-Analysis Identifies Gene-by-Environment Interactions as Demonstrated in a Study of 4,965 Mice

PubMed Central

Joo, Jong Wha J.; Shih, Diana; Davis, Richard C.; Lusis, Aldons J.; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study. PMID:24415945
Assessing the performance of dispersionless and dispersion-accounting methods: helium interaction with cluster models of the TiO2(110) surface.

PubMed

de Lara-Castells, María Pilar; Stoll, Hermann; Mitrushchenkov, Alexander O

2014-08-21

As a prototypical dispersion-dominated physisorption problem, we analyze here the performance of dispersionless and dispersion-accounting methodologies on the helium interaction with cluster models of the TiO2(110) surface. A special focus has been given to the dispersionless density functional dlDF and the dlDF+Das construction for the total interaction energy (K. Pernal, R. Podeswa, K. Patkowski, and K. Szalewicz, Phys. Rev. Lett. 2009, 109, 263201), where Das is an effective interatomic pairwise functional form for the dispersion. Likewise, the performance of symmetry-adapted perturbation theory (SAPT) method is evaluated, where the interacting monomers are described by density functional theory (DFT) with the dlDF, PBE, and PBE0 functionals. Our benchmarks include CCSD(T)-F12b calculations and comparative analysis on the nuclear bound states supported by the He-cluster potentials. Moreover, intra- and intermonomer correlation contributions to the physisorption interaction are analyzed through the method of increments (H. Stoll, J. Chem. Phys. 1992, 97, 8449) at the CCSD(T) level of theory. This method is further applied in conjunction with a partitioning of the Hartree-Fock interaction energy to estimate individual interaction energy components, comparing them with those obtained using the different SAPT(DFT) approaches. The cluster size evolution of dispersionless and dispersion-accounting energy components is then discussed, revealing the reduced role of the dispersionless interaction and intramonomer correlation when the extended nature of the surface is better accounted for. On the contrary, both post-Hartree-Fock and SAPT(DFT) results clearly demonstrate the high-transferability character of the effective pairwise dispersion interaction whatever the cluster model is. Our contribution also illustrates how the method of increments can be used as a valuable tool not only to achieve the accuracy of CCSD(T) calculations using large cluster models but also to evaluate the performance of SAPT(DFT) methods for the physically well-defined contributions to the total interaction energy. Overall, our work indicates the excellent performance of a dlDF+Das approach in which the parameters are optimized using the smallest cluster model of the target surface to treat van der Waals adsorbate-surface interactions.
Yoink: An interaction-based partitioning API.

PubMed

Zheng, Min; Waller, Mark P

2018-05-15

Herein, we describe the implementation details of our interaction-based partitioning API (application programming interface) called Yoink for QM/MM modeling and fragment-based quantum chemistry studies. Interactions are detected by computing density descriptors such as reduced density gradient, density overlap regions indicator, and single exponential decay detector. Only molecules having an interaction with a user-definable QM core are added to the QM region of a hybrid QM/MM calculation. Moreover, a set of molecule pairs having density-based interactions within a molecular system can be computed in Yoink, and an interaction graph can then be constructed. Standard graph clustering methods can then be applied to construct fragments for further quantum chemical calculations. The Yoink API is licensed under Apache 2.0 and can be accessed via yoink.wallerlab.org. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.
Interactive Sonification Exploring Emergent Behavior Applying Models for Biological Information and Listening

PubMed Central

Choi, Insook

2018-01-01

Sonification is an open-ended design task to construct sound informing a listener of data. Understanding application context is critical for shaping design requirements for data translation into sound. Sonification requires methodology to maintain reproducibility when data sources exhibit non-linear properties of self-organization and emergent behavior. This research formalizes interactive sonification in an extensible model to support reproducibility when data exhibits emergent behavior. In the absence of sonification theory, extensibility demonstrates relevant methods across case studies. The interactive sonification framework foregrounds three factors: reproducible system implementation for generating sonification; interactive mechanisms enhancing a listener's multisensory observations; and reproducible data from models that characterize emergent behavior. Supramodal attention research suggests interactive exploration with auditory feedback can generate context for recognizing irregular patterns and transient dynamics. The sonification framework provides circular causality as a signal pathway for modeling a listener interacting with emergent behavior. The extensible sonification model adopts a data acquisition pathway to formalize functional symmetry across three subsystems: Experimental Data Source, Sound Generation, and Guided Exploration. To differentiate time criticality and dimensionality of emerging dynamics, tuning functions are applied between subsystems to maintain scale and symmetry of concurrent processes and temporal dynamics. Tuning functions accommodate sonification design strategies that yield order parameter values to render emerging patterns discoverable as well as rehearsable, to reproduce desired instances for clinical listeners. Case studies are implemented with two computational models, Chua's circuit and Swarm Chemistry social agent simulation, generating data in real-time that exhibits emergent behavior. Heuristic Listening is introduced as an informal model of a listener's clinical attention to data sonification through multisensory interaction in a context of structured inquiry. Three methods are introduced to assess the proposed sonification framework: Listening Scenario classification, data flow Attunement, and Sonification Design Patterns to classify sound control. Case study implementations are assessed against these methods comparing levels of abstraction between experimental data and sound generation. Outcomes demonstrate the framework performance as a reference model for representing experimental implementations, also for identifying common sonification structures having different experimental implementations, identifying common functions implemented in different subsystems, and comparing impact of affordances across multiple implementations of listening scenarios. PMID:29755311
Extended maximum likelihood halo-independent analysis of dark matter direct detection data

DOE PAGES

Gelmini, Graciela B.; Georgescu, Andreea; Gondolo, Paolo; ...

2015-11-24

We extend and correct a recently proposed maximum-likelihood halo-independent method to analyze unbinned direct dark matter detection data. Instead of the recoil energy as independent variable we use the minimum speed a dark matter particle must have to impart a given recoil energy to a nucleus. This has the advantage of allowing us to apply the method to any type of target composition and interaction, e.g. with general momentum and velocity dependence, and with elastic or inelastic scattering. We prove the method and provide a rigorous statistical interpretation of the results. As first applications, we find that for dark mattermore » particles with elastic spin-independent interactions and neutron to proton coupling ratio f n/f p=-0.7, the WIMP interpretation of the signal observed by CDMS-II-Si is compatible with the constraints imposed by all other experiments with null results. We also find a similar compatibility for exothermic inelastic spin-independent interactions with f n/f p=-0.8.« less
An improved viscid/inviscid interaction procedure for transonic flow over airfoils

NASA Technical Reports Server (NTRS)

Melnik, R. E.; Chow, R. R.; Mead, H. R.; Jameson, A.

1985-01-01

A new interacting boundary layer approach for computing the viscous transonic flow over airfoils is described. The theory includes a complete treatment of viscous interaction effects induced by the wake and accounts for normal pressure gradient effects across the boundary layer near trailing edges. The method is based on systematic expansions of the full Reynolds equation of turbulent flow in the limit of Reynolds numbers, Reynolds infinity. Procedures are developed for incorporating the local trailing edge solution into the numerical solution of the coupled full potential and integral boundary layer equations. Although the theory is strictly applicable to airfoils with cusped or nearly cusped trailing edges and to turbulent boundary layers that remain fully attached to the airfoil surface, the method was successfully applied to more general airfoils and to flows with small separation zones. Comparisons of theoretical solutions with wind tunnel data indicate the present method can accurately predict the section characteristics of airfoils including the absolute levels of drag.
Dissipative time-dependent quantum transport theory.

PubMed

Zhang, Yu; Yam, Chi Yung; Chen, GuanHua

2013-04-28

A dissipative time-dependent quantum transport theory is developed to treat the transient current through molecular or nanoscopic devices in presence of electron-phonon interaction. The dissipation via phonon is taken into account by introducing a self-energy for the electron-phonon coupling in addition to the self-energy caused by the electrodes. Based on this, a numerical method is proposed. For practical implementation, the lowest order expansion is employed for the weak electron-phonon coupling case and the wide-band limit approximation is adopted for device and electrodes coupling. The corresponding hierarchical equation of motion is derived, which leads to an efficient and accurate time-dependent treatment of inelastic effect on transport for the weak electron-phonon interaction. The resulting method is applied to a one-level model system and a gold wire described by tight-binding model to demonstrate its validity and the importance of electron-phonon interaction for the quantum transport. As it is based on the effective single-electron model, the method can be readily extended to time-dependent density functional theory.
Gauge invariance of excitonic linear and nonlinear optical response

NASA Astrophysics Data System (ADS)

Taghizadeh, Alireza; Pedersen, T. G.

2018-05-01

We study the equivalence of four different approaches to calculate the excitonic linear and nonlinear optical response of multiband semiconductors. These four methods derive from two choices of gauge, i.e., length and velocity gauges, and two ways of computing the current density, i.e., direct evaluation and evaluation via the time-derivative of the polarization density. The linear and quadratic response functions are obtained for all methods by employing a perturbative density-matrix approach within the mean-field approximation. The equivalence of all four methods is shown rigorously, when a correct interaction Hamiltonian is employed for the velocity gauge approaches. The correct interaction is written as a series of commutators containing the unperturbed Hamiltonian and position operators, which becomes equivalent to the conventional velocity gauge interaction in the limit of infinite Coulomb screening and infinitely many bands. As a case study, the theory is applied to hexagonal boron nitride monolayers, and the linear and nonlinear optical response found in different approaches are compared.
High-Throughput, Data-Rich Cellular RNA Device Engineering

PubMed Central

Townshend, Brent; Kennedy, Andrew B.; Xiang, Joy S.; Smolke, Christina D.

2015-01-01

Methods for rapidly assessing sequence-structure-function landscapes and developing conditional gene-regulatory devices are critical to our ability to manipulate and interface with biology. We describe a framework for engineering RNA devices from preexisting aptamers that exhibit ligand-responsive ribozyme tertiary interactions. Our methodology utilizes cell sorting, high-throughput sequencing, and statistical data analyses to enable parallel measurements of the activities of hundreds of thousands of sequences from RNA device libraries in the absence and presence of ligands. Our tertiary interaction RNA devices exhibit improved performance in terms of gene silencing, activation ratio, and ligand sensitivity as compared to optimized RNA devices that rely on secondary structure changes. We apply our method to building biosensors for diverse ligands and determine consensus sequences that enable ligand-responsive tertiary interactions. These methods advance our ability to develop broadly applicable genetic tools and to elucidate understanding of the underlying sequence-structure-function relationships that empower rational design of complex biomolecules. PMID:26258292
Re-Sonification of Objects, Events, and Environments

NASA Astrophysics Data System (ADS)

Fink, Alex M.

Digital sound synthesis allows the creation of a great variety of sounds. Focusing on interesting or ecologically valid sounds for music, simulation, aesthetics, or other purposes limits the otherwise vast digital audio palette. Tools for creating such sounds vary from arbitrary methods of altering recordings to precise simulations of vibrating objects. In this work, methods of sound synthesis by re-sonification are considered. Re-sonification, herein, refers to the general process of analyzing, possibly transforming, and resynthesizing or reusing recorded sounds in meaningful ways, to convey information. Applied to soundscapes, re-sonification is presented as a means of conveying activity within an environment. Applied to the sounds of objects, this work examines modeling the perception of objects as well as their physical properties and the ability to simulate interactive events with such objects. To create soundscapes to re-sonify geographic environments, a method of automated soundscape design is presented. Using recorded sounds that are classified based on acoustic, social, semantic, and geographic information, this method produces stochastically generated soundscapes to re-sonify selected geographic areas. Drawing on prior knowledge, local sounds and those deemed similar comprise a locale's soundscape. In the context of re-sonifying events, this work examines processes for modeling and estimating the excitations of sounding objects. These include plucking, striking, rubbing, and any interaction that imparts energy into a system, affecting the resultant sound. A method of estimating a linear system's input, constrained to a signal-subspace, is presented and applied toward improving the estimation of percussive excitations for re-sonification. To work toward robust recording-based modeling and re-sonification of objects, new implementations of banded waveguide (BWG) models are proposed for object modeling and sound synthesis. Previous implementations of BWGs use arbitrary model parameters and may produce a range of simulations that do not match digital waveguide or modal models of the same design. Subject to linear excitations, some models proposed here behave identically to other equivalently designed physical models. Under nonlinear interactions, such as bowing, many of the proposed implementations exhibit improvements in the attack characteristics of synthesized sounds.
Application of Analytical Quality by Design concept for bilastine and its degradation impurities determination by hydrophilic interaction liquid chromatographic method.

PubMed

Terzić, Jelena; Popović, Igor; Stajić, Ana; Tumpa, Anja; Jančić-Stojanović, Biljana

2016-06-05

This paper deals with the development of hydrophilic interaction liquid chromatographic (HILIC) method for the analysis of bilastine and its degradation impurities following Analytical Quality by Design approach. It is the first time that the method for bilastine and its impurities is proposed. The main objective was to identify the conditions where an adequate separation in minimal analysis duration could be achieved within a robust region. Critical process parameters which have the most influence on method performance were defined as acetonitrile content in the mobile phase, pH of the aqueous phase and ammonium acetate concentration in the aqueous phase. Box-Behnken design was applied for establishing a relationship between critical process parameters and critical quality attributes. The defined mathematical models and Monte Carlo simulations were used to identify the design space. Fractional factorial design was applied for experimental robustness testing and the method is validated to verify the adequacy of selected optimal conditions: the analytical column Luna(®) HILIC (100mm×4.6mm, 5μm particle size); mobile phase consisted of acetonitrile-aqueous phase (50mM ammonium acetate, pH adjusted to 5.3 with glacial acetic acid) (90.5:9.5, v/v); column temperature 30°C, mobile phase flow rate 1mLmin(-1), wavelength of detection 275nm. Copyright © 2016 Elsevier B.V. All rights reserved.
A High-Throughput Screening Method for Small-Molecule Inhibitors of the Aberrant Mutant SOD1 and Dynein Complex Interaction

PubMed Central

Tang, Xiaohu; Seyb, Kathleen I.; Huang, Mickey; Schuman, Eli R.; Shi, Ping; Zhu, Haining; Glicksman, Marcie A.

2013-01-01

Aberrant protein-protein interactions are attractive drug targets in a variety of neurodegenerative diseases due to the common pathology of accumulation of protein aggregates. In amyotrophic lateral sclerosis, mutations in SOD1 cause the formation of aggregates and inclusions that may sequester other proteins and disrupt cellular processes. It has been demonstrated that mutant SOD1, but not wild-type SOD1, interacts with the axonal transport motor dynein and that this interaction contributes to motor neuron cell death, suggesting that disrupting this interaction may be a potential therapeutic target. However, it can be challenging to configure a high-throughput screening (HTS)–compatible assay to detect inhibitors of a protein-protein interaction. Here we describe the development and challenges of an HTS for small-molecule inhibitors of the mutant SOD1-dynein interaction. We demonstrate that the interaction can be formed by coexpressing the A4V mutant SOD1 and dynein intermediate complex in cells and that this interaction can be disrupted by compounds added to the cell lysates. Finally, we show that some of the compounds identified from a pilot screen to inhibit the protein-protein interaction with this method specifically disrupt the interaction between the dynein complex and mtSOD1 but not the dynein complex itself when applied to live cells. PMID:22140121
Symmetry-adapted perturbation theory interaction energy decomposition for some noble gas complexes

NASA Astrophysics Data System (ADS)

Cukras, Janusz; Sadlej, Joanna

2008-06-01

This Letter contains a study of the interaction energy in HArF⋯N 2 and HArF⋯P 2 complexes. Symmetry-adapted perturbation theory (SAPT) has been applied to analyze the electrostatic, induction, dispersion and exchange contributions to the total interaction energy. The interaction energy has also been obtained by supermolecular method at the MP2, MP4, CCSD, CCSD(T) levels. The interaction energy for the studied complexes results from a partial cancelation of large attractive electrostatic, induction, dispersion terms by a strong repulsive exchange contribution. The induction and dispersion effects proved to be crucial in establishing the preference for the colinear HArF⋯N 2 and HArF⋯P 2 structures and shift direction of νHAr stretching vibrations.
Improved numerical methods for infinite spin chains with long-range interactions

NASA Astrophysics Data System (ADS)

Nebendahl, V.; Dür, W.

2013-02-01

We present several improvements of the infinite matrix product state (iMPS) algorithm for finding ground states of one-dimensional quantum systems with long-range interactions. As a main ingredient, we introduce the superposed multioptimization method, which allows an efficient optimization of exponentially many MPS of different lengths at different sites all in one step. Here, the algorithm becomes protected against position-dependent effects as caused by spontaneously broken translational invariance. So far, these have been a major obstacle to convergence for the iMPS algorithm if no prior knowledge of the system's translational symmetry was accessible. Further, we investigate some more general methods to speed up calculations and improve convergence, which might be partially interesting in a much broader context, too. As a more special problem, we also look into translational invariant states close to an invariance-breaking phase transition and show how to avoid convergence into wrong local minima for such systems. Finally, we apply these methods to polar bosons with long-range interactions. We calculate several detailed Devil's staircases with the corresponding phase diagrams and investigate some supersolid properties.
Scale transition using dislocation dynamics and the nudged elastic band method

DOE PAGES

Sobie, Cameron; Capolungo, Laurent; McDowell, David L.; ...

2017-08-01

Microstructural features such as precipitates or irradiation-induced defects impede dislocation motion and directly influence macroscopic mechanical properties such as yield point and ductility. In dislocation-defect interactions both atomic scale and long range elastic interactions are involved. Thermally assisted dislocation bypass of obstacles occurs when thermal fluctuations and driving stresses contribute sufficient energy to overcome the energy barrier. The Nudged Elastic Band (NEB) method is typically used in the context of atomistic simulations to quantify the activation barriers for a given reaction. In this work, the NEB method is generalized to coarse-grain continuum representations of evolving microstructure states beyond the discretemore » particle descriptions of first principles and atomistics. The method we employed enables the calculation of activation energies for a View the MathML source glide dislocation bypassing a [001] self-interstitial atom loop of size in the range of 4-10 nm with a spacing larger than 150nm in α-iron for a range of applied stresses and interaction geometries. This study is complemented by a comparison between atomistic and continuum based prediction of barriers.« less
Computational revelation of binding mechanisms of inhibitors to endocellular protein tyrosine phosphatase 1B using molecular dynamics simulations.

PubMed

Yan, Fangfang; Liu, Xinguo; Zhang, Shaolong; Su, Jing; Zhang, Qinggang; Chen, Jianzhong

2017-11-06

Endocellular protein tyrosine phosphatase 1B (PTP1B) is one of the most promising target for designing and developing drugs to cure type-II diabetes and obesity. Molecular dynamics (MD) simulations combined with molecular mechanics generalized Born surface area (MM-GBSA) and solvated interaction energy methods were applied to study binding differences of three inhibitors (ID: 901, 941, and 968) to PTP1B, the calculated results show that the inhibitor 901 has the strongest binding ability to PTP1B among the current inhibitors. Principal component (PC) analysis was also carried out to investigate the conformational change of PTP1B, and the results indicate that the associations of inhibitors with PTP1B generate a significant effect on the motion of the WPD-loop. Free energy decomposition method was applied to study the contributions of individual residues to inhibitor bindings, it is found that three inhibitors can generate hydrogen bonding interactions and hydrophobic interactions with different residues of PTP1B, which provide important forces for associations of inhibitors with PTP1B. This research is expected to give a meaningfully theoretical guidance to design and develop of effective drugs curing type-II diabetes and obesity.
Predicting Protein-protein Association Rates using Coarse-grained Simulation and Machine Learning

NASA Astrophysics Data System (ADS)

Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao

2017-04-01

Protein-protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins. After applying a machine learning algorithm with input variables that accounted for both the conformational flexibility and the energetic factor of binding, we successfully identified most of the protein complexes with overestimated association rates and improved our final prediction by using a cross-validation test. This method was then applied to a new independent test set and resulted in a similar prediction accuracy to that obtained using the training set. It has been thought that diffusion-limited protein association is dominated by long-range interactions. Our results provide strong evidence that the conformational flexibility also plays an important role in regulating protein association. Our studies provide new insights into the mechanism of protein association and offer a computationally efficient tool for predicting its rate.
Predicting Protein–protein Association Rates using Coarse-grained Simulation and Machine Learning

PubMed Central

Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao

2017-01-01

Protein–protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins. After applying a machine learning algorithm with input variables that accounted for both the conformational flexibility and the energetic factor of binding, we successfully identified most of the protein complexes with overestimated association rates and improved our final prediction by using a cross-validation test. This method was then applied to a new independent test set and resulted in a similar prediction accuracy to that obtained using the training set. It has been thought that diffusion-limited protein association is dominated by long-range interactions. Our results provide strong evidence that the conformational flexibility also plays an important role in regulating protein association. Our studies provide new insights into the mechanism of protein association and offer a computationally efficient tool for predicting its rate. PMID:28418043
Predicting Protein-protein Association Rates using Coarse-grained Simulation and Machine Learning.

PubMed

Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao

2017-04-18

Protein-protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins. After applying a machine learning algorithm with input variables that accounted for both the conformational flexibility and the energetic factor of binding, we successfully identified most of the protein complexes with overestimated association rates and improved our final prediction by using a cross-validation test. This method was then applied to a new independent test set and resulted in a similar prediction accuracy to that obtained using the training set. It has been thought that diffusion-limited protein association is dominated by long-range interactions. Our results provide strong evidence that the conformational flexibility also plays an important role in regulating protein association. Our studies provide new insights into the mechanism of protein association and offer a computationally efficient tool for predicting its rate.
Applying pollen DNA metabarcoding to the study of plant–pollinator interactions1

PubMed Central

Bell, Karen L.; Fowler, Julie; Burgess, Kevin S.; Dobbs, Emily K.; Gruenewald, David; Lawley, Brice; Morozumi, Connor; Brosi, Berry J.

2017-01-01

Premise of the study: To study pollination networks in a changing environment, we need accurate, high-throughput methods. Previous studies have shown that more highly resolved networks can be constructed by studying pollen loads taken from bees, relative to field observations. DNA metabarcoding potentially allows for faster and finer-scale taxonomic resolution of pollen compared to traditional approaches (e.g., light microscopy), but has not been applied to pollination networks. Methods: We sampled pollen from 38 bee species collected in Florida from sites differing in forest management. We isolated DNA from pollen mixtures and sequenced rbcL and ITS2 gene regions from all mixtures in a single run on the Illumina MiSeq platform. We identified species from sequence data using comprehensive rbcL and ITS2 databases. Results: We successfully built a proof-of-concept quantitative pollination network using pollen metabarcoding. Discussion: Our work underscores that pollen metabarcoding is not quantitative but that quantitative networks can be constructed based on the number of interacting individuals. Due to the frequency of contamination and false positive reads, isolation and PCR negative controls should be used in every reaction. DNA metabarcoding has advantages in efficiency and resolution over microscopic identification of pollen, and we expect that it will have broad utility for future studies of plant–pollinator interactions. PMID:28690929

Computational Analysis of Molecular Interaction Networks Underlying Change of HIV-1 Resistance to Selected Reverse Transcriptase Inhibitors

PubMed Central

Kierczak, Marcin; Dramiński, Michał; Koronacki, Jacek; Komorowski, Jan

2010-01-01

Motivation Despite more than two decades of research, HIV resistance to drugs remains a serious obstacle in developing efficient AIDS treatments. Several computational methods have been developed to predict resistance level from the sequence of viral proteins such as reverse transcriptase (RT) or protease. These methods, while powerful and accurate, give very little insight into the molecular interactions that underly acquisition of drug resistance/hypersusceptibility. Here, we attempt at filling this gap by using our Monte Carlo feature selection and interdependency discovery method (MCFS-ID) to elucidate molecular interaction networks that characterize viral strains with altered drug resistance levels. Results We analyzed a number of HIV-1 RT sequences annotated with drug resistance level using the MCFS-ID method. This let us expound interdependency networks that characterize change of drug resistance to six selected RT inhibitors: Abacavir, Lamivudine, Stavudine, Zidovudine, Tenofovir and Nevirapine. The networks consider interdependencies at the level of physicochemical properties of mutating amino acids, eg,: polarity. We mapped each network on the 3D structure of RT in attempt to understand the molecular meaning of interacting pairs. The discovered interactions describe several known drug resistance mechanisms and, importantly, some previously unidentified ones. Our approach can be easily applied to a whole range of problems from the domain of protein engineering. Availability A portable Java implementation of our MCFS-ID method is freely available for academic users and can be obtained at: http://www.ipipan.eu/staff/m.draminski/software.htm. PMID:21234299
Computational Analysis of Molecular Interaction Networks Underlying Change of HIV-1 Resistance to Selected Reverse Transcriptase Inhibitors.

PubMed

Kierczak, Marcin; Dramiński, Michał; Koronacki, Jacek; Komorowski, Jan

2010-12-12

Despite more than two decades of research, HIV resistance to drugs remains a serious obstacle in developing efficient AIDS treatments. Several computational methods have been developed to predict resistance level from the sequence of viral proteins such as reverse transcriptase (RT) or protease. These methods, while powerful and accurate, give very little insight into the molecular interactions that underly acquisition of drug resistance/hypersusceptibility. Here, we attempt at filling this gap by using our Monte Carlo feature selection and interdependency discovery method (MCFS-ID) to elucidate molecular interaction networks that characterize viral strains with altered drug resistance levels. We analyzed a number of HIV-1 RT sequences annotated with drug resistance level using the MCFS-ID method. This let us expound interdependency networks that characterize change of drug resistance to six selected RT inhibitors: Abacavir, Lamivudine, Stavudine, Zidovudine, Tenofovir and Nevirapine. The networks consider interdependencies at the level of physicochemical properties of mutating amino acids, eg,: polarity. We mapped each network on the 3D structure of RT in attempt to understand the molecular meaning of interacting pairs. The discovered interactions describe several known drug resistance mechanisms and, importantly, some previously unidentified ones. Our approach can be easily applied to a whole range of problems from the domain of protein engineering. A portable Java implementation of our MCFS-ID method is freely available for academic users and can be obtained at: http://www.ipipan.eu/staff/m.draminski/software.htm.
Causal inference in nonlinear systems: Granger causality versus time-delayed mutual information

NASA Astrophysics Data System (ADS)

Li, Songting; Xiao, Yanyang; Zhou, Douglas; Cai, David

2018-05-01

The Granger causality (GC) analysis has been extensively applied to infer causal interactions in dynamical systems arising from economy and finance, physics, bioinformatics, neuroscience, social science, and many other fields. In the presence of potential nonlinearity in these systems, the validity of the GC analysis in general is questionable. To illustrate this, here we first construct minimal nonlinear systems and show that the GC analysis fails to infer causal relations in these systems—it gives rise to all types of incorrect causal directions. In contrast, we show that the time-delayed mutual information (TDMI) analysis is able to successfully identify the direction of interactions underlying these nonlinear systems. We then apply both methods to neuroscience data collected from experiments and demonstrate that the TDMI analysis but not the GC analysis can identify the direction of interactions among neuronal signals. Our work exemplifies inference hazards in the GC analysis in nonlinear systems and suggests that the TDMI analysis can be an appropriate tool in such a case.
A Framework for Modeling Human-Machine Interactions

NASA Technical Reports Server (NTRS)

Shafto, Michael G.; Rosekind, Mark R. (Technical Monitor)

1996-01-01

Modern automated flight-control systems employ a variety of different behaviors, or modes, for managing the flight. While developments in cockpit automation have resulted in workload reduction and economical advantages, they have also given rise to an ill-defined class of human-machine problems, sometimes referred to as 'automation surprises'. Our interest in applying formal methods for describing human-computer interaction stems from our ongoing research on cockpit automation. In this area of aeronautical human factors, there is much concern about how flight crews interact with automated flight-control systems, so that the likelihood of making errors, in particular mode-errors, is minimized and the consequences of such errors are contained. The goal of the ongoing research on formal methods in this context is: (1) to develop a framework for describing human interaction with control systems; (2) to formally categorize such automation surprises; and (3) to develop tests for identification of these categories early in the specification phase of a new human-machine system.
Predicting Pharmacodynamic Drug-Drug Interactions through Signaling Propagation Interference on Protein-Protein Interaction Networks.

PubMed

Park, Kyunghyun; Kim, Docyong; Ha, Suhyun; Lee, Doheon

2015-01-01

As pharmacodynamic drug-drug interactions (PD DDIs) could lead to severe adverse effects in patients, it is important to identify potential PD DDIs in drug development. The signaling starting from drug targets is propagated through protein-protein interaction (PPI) networks. PD DDIs could occur by close interference on the same targets or within the same pathways as well as distant interference through cross-talking pathways. However, most of the previous approaches have considered only close interference by measuring distances between drug targets or comparing target neighbors. We have applied a random walk with restart algorithm to simulate signaling propagation from drug targets in order to capture the possibility of their distant interference. Cross validation with DrugBank and Kyoto Encyclopedia of Genes and Genomes DRUG shows that the proposed method outperforms the previous methods significantly. We also provide a web service with which PD DDIs for drug pairs can be analyzed at http://biosoft.kaist.ac.kr/targetrw.
Next-generation sequencing coupled with a cell-free display technology for high-throughput production of reliable interactome data

PubMed Central

Fujimori, Shigeo; Hirai, Naoya; Ohashi, Hiroyuki; Masuoka, Kazuyo; Nishikimi, Akihiko; Fukui, Yoshinori; Washio, Takanori; Oshikubo, Tomohiro; Yamashita, Tatsuhiro; Miyamoto-Sato, Etsuko

2012-01-01

Next-generation sequencing (NGS) has been applied to various kinds of omics studies, resulting in many biological and medical discoveries. However, high-throughput protein-protein interactome datasets derived from detection by sequencing are scarce, because protein-protein interaction analysis requires many cell manipulations to examine the interactions. The low reliability of the high-throughput data is also a problem. Here, we describe a cell-free display technology combined with NGS that can improve both the coverage and reliability of interactome datasets. The completely cell-free method gives a high-throughput and a large detection space, testing the interactions without using clones. The quantitative information provided by NGS reduces the number of false positives. The method is suitable for the in vitro detection of proteins that interact not only with the bait protein, but also with DNA, RNA and chemical compounds. Thus, it could become a universal approach for exploring the large space of protein sequences and interactome networks. PMID:23056904
Collision-induced absorption with exchange effects and anisotropic interactions: theory and application to H2 - H2.

PubMed

Karman, Tijs; van der Avoird, Ad; Groenenboom, Gerrit C

2015-02-28

We discuss three quantum mechanical formalisms for calculating collision-induced absorption spectra. First, we revisit the established theory of collision-induced absorption, assuming distinguishable molecules which interact isotropically. Then, the theory is rederived incorporating exchange effects between indistinguishable molecules. It is shown that the spectrum can no longer be written as an incoherent sum of the contributions of the different spherical components of the dipole moment. Finally, we derive an efficient method to include the effects of anisotropic interactions in the computation of the absorption spectrum. This method calculates the dipole coupling on-the-fly, which allows for the uncoupled treatment of the initial and final states without the explicit reconstruction of the many-component wave functions. The three formalisms are applied to the collision-induced rotation-translation spectra of hydrogen molecules in the far-infrared. Good agreement with experimental data is obtained. Significant effects of anisotropic interactions are observed in the far wing.
Inference of RhoGAP/GTPase regulation using single-cell morphological data from a combinatorial RNAi screen.

PubMed

Nir, Oaz; Bakal, Chris; Perrimon, Norbert; Berger, Bonnie

2010-03-01

Biological networks are highly complex systems, consisting largely of enzymes that act as molecular switches to activate/inhibit downstream targets via post-translational modification. Computational techniques have been developed to perform signaling network inference using some high-throughput data sources, such as those generated from transcriptional and proteomic studies, but comparable methods have not been developed to use high-content morphological data, which are emerging principally from large-scale RNAi screens, to these ends. Here, we describe a systematic computational framework based on a classification model for identifying genetic interactions using high-dimensional single-cell morphological data from genetic screens, apply it to RhoGAP/GTPase regulation in Drosophila, and evaluate its efficacy. Augmented by knowledge of the basic structure of RhoGAP/GTPase signaling, namely, that GAPs act directly upstream of GTPases, we apply our framework for identifying genetic interactions to predict signaling relationships between these proteins. We find that our method makes mediocre predictions using only RhoGAP single-knockdown morphological data, yet achieves vastly improved accuracy by including original data from a double-knockdown RhoGAP genetic screen, which likely reflects the redundant network structure of RhoGAP/GTPase signaling. We consider other possible methods for inference and show that our primary model outperforms the alternatives. This work demonstrates the fundamental fact that high-throughput morphological data can be used in a systematic, successful fashion to identify genetic interactions and, using additional elementary knowledge of network structure, to infer signaling relations.
Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks

PubMed Central

Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E.; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A.; Kellis, Manolis

2012-01-01

Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein–protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level. PMID:22456606
A new open tubular capillary microextraction and sweeping for the analysis of super low concentration of hydrophobic compounds.

PubMed

Xia, Zhining; Gan, Tingting; Chen, Hua; Lv, Rui; Wei, Weili; Yang, Fengqing

2010-10-01

A sample pre-concentration method based on the in-line coupling of in-tube solid-phase microextraction and electrophoretic sweeping was developed for the analysis of hydrophobic compounds. The sample pre-concentration and electrophoretic separation processes were simply and sequentially carried out with a (35%-phenyl)-methylpolysiloxane-coated capillary. The developed method was validated and applied to enrich and separate several pharmaceuticals including loratadine, indomethacin, ibuprofen and doxazosin. Several parameters of microextration were investigated such as temperature, pH and eluant. And the concentration of microemulsion that influences separation efficiency and microextraction efficiency were also studied. Central composite design was applied for the optimization of sampling flow rate and sampling time that interact in a very complex way with each other. The precision, sensitivity and recovery of the method were investigated. Under the optimal conditions, the maximum enrichment factors for loratadine, indomethacin, ibuprofen and doxazosin in aqueous solutions are 1355, 571, 523 and 318, respectively. In addition, the developed method was applied to determine loratadine in rabbit blood sample.
An examination of the concept of driving point receptance

NASA Astrophysics Data System (ADS)

Sheng, X.; He, Y.; Zhong, T.

2018-04-01

In the field of vibration, driving point receptance is a well-established and widely applied concept. However, as demonstrated in this paper, when a driving point receptance is calculated using the finite element (FE) method with solid elements, it does not converge as the FE mesh becomes finer, suggesting that there is a singularity. Hence, the concept of driving point receptance deserves a rigorous examination. In this paper, it is firstly shown that, for a point harmonic force applied on the surface of an elastic half-space, the Boussinesq formula can be applied to calculate the displacement amplitude of the surface if the response point is sufficiently close to the load. Secondly, by applying the Betti reciprocal theorem, it is shown that the displacement of an elastic body near a point harmonic force can be decomposed into two parts, with the first one being the displacement of an elastic half-space. This decomposition is useful, since it provides a solid basis for the introduction of a contact spring between a wheel and a rail in interaction. However, according to the Boussinesq formula, this decomposition also leads to the conclusion that a driving point receptance is infinite (singular), and would be undefinable. Nevertheless, driving point receptances have been calculated using different methods. Since the singularity identified in this paper was not appreciated, no account was given to the singularity in these calculations. Thus, the validity of these calculation methods must be examined. This constructs the third part of the paper. As the final development of the paper, the above decomposition is utilised to define and determine driving point receptances required for dealing with wheel/rail interactions.
Evaluation of drug-carrier interactions in quaternary powder mixtures containing perindopril tert-butylamine and indapamide.

PubMed

Voelkel, Adam; Milczewska, Kasylda; Teżyk, Michał; Milanowski, Bartłomiej; Lulek, Janina

2016-04-30

Interactions occurring between components in the quaternary powder mixtures consisting of perindopril tert-butylamine, indapamide (active pharmaceutical ingredients), carrier substance and hydrophobic colloidal silica were examined. Two grades of lactose monohydrate: Spherolac(®) 100 and Granulac(®) 200 and two types of microcrystalline cellulose: M101D+ and Vivapur(®) 102 were used as carriers. We determined the size distribution (laser diffraction method), morphology (scanning electron microscopy) and a specific surface area of the powder particles (by nitrogen adsorption-desorption). For the determination of the surface energy of powder mixtures the method of inverse gas chromatography was applied. Investigated mixtures were characterized by surface parameters (dispersive component of surface energy, specific interactions parameters, specific surface area), work of adhesion and cohesion as well as Flory-Huggins parameter χ23('). Results obtained for all quaternary powder mixtures indicate existence of interactions between components. The strongest interactions occur for both blends with different types of microcrystalline cellulose (PM-1 and PM-4) while much weaker ones for powder mixtures with various types of lactose (PM-2 and PM-3). Published by Elsevier B.V.
Acute effect of Vagus nerve stimulation parameters on cardiac chronotropic, inotropic, and dromotropic responses

NASA Astrophysics Data System (ADS)

Ojeda, David; Le Rolle, Virginie; Romero-Ugalde, Hector M.; Gallet, Clément; Bonnet, Jean-Luc; Henry, Christine; Bel, Alain; Mabo, Philippe; Carrault, Guy; Hernández, Alfredo I.

2017-11-01

Vagus nerve stimulation (VNS) is an established therapy for drug-resistant epilepsy and depression, and is considered as a potential therapy for other pathologies, including Heart Failure (HF) or inflammatory diseases. In the case of HF, several experimental studies on animals have shown an improvement in the cardiac function and a reverse remodeling of the cardiac cavity when VNS is applied. However, recent clinical trials have not been able to reproduce the same response in humans. One of the hypothesis to explain this lack of response is related to the way in which stimulation parameters are defined. The combined effect of VNS parameters is still poorly-known, especially in the case of VNS synchronously delivered with cardiac activity. In this paper, we propose a methodology to analyze the acute cardiovascular effects of VNS parameters individually, as well as their interactive effects. A Latin hypercube sampling method was applied to design a uniform experimental plan. Data gathered from this experimental plan was used to produce a Gaussian process regression (GPR) model in order to estimate unobserved VNS sequences. Finally, a Morris screening sensitivity analysis method was applied to each obtained GPR model. Results highlight dominant effects of pulse current, pulse width and number of pulses over frequency and delay and, more importantly, the degree of interactions between these parameters on the most important acute cardiovascular responses. In particular, high interacting effects between current and pulse width were found. Similar sensitivity profiles were observed for chronotropic, dromotropic and inotropic effects. These findings are of primary importance for the future development of closed-loop, personalized neuromodulator technologies.
SIRIUS. An automated method for the analysis of the preferred packing arrangements between protein groups.

PubMed

Singh, J; Thornton, J M

1990-02-05

Automated methods have been developed to determine the preferred packing arrangement between interacting protein groups. A suite of FORTRAN programs, SIRIUS, is described for calculating and analysing the geometries of interacting protein groups using crystallographically derived atomic co-ordinates. The programs involved in calculating the geometries search for interacting pairs of protein groups using a distance criterion, and then calculate the spatial disposition and orientation of the pair. The second set of programs is devoted to analysis. This involves calculating the observed and expected distributions of the angles and assessing the statistical significance of the difference between the two. A database of the geometries of the 400 combinations of side-chain to side-chain interaction has been created. The approach used in analysing the geometrical information is illustrated here with specific examples of interactions between side-chains, peptide groups and particular types of atom. At the side-chain level, an analysis of aromatic-amino interactions, and the interactions of peptide carbonyl groups with arginine residues is presented. At the atomic level the analyses include the spatial disposition of oxygen atoms around tyrosine residues, and the frequency and type of contact between carbon, nitrogen and oxygen atoms. This information is currently being applied to the modelling of protein interactions.
Differential network analysis reveals the genome-wide landscape of estrogen receptor modulation in hormonal cancers

PubMed Central

Hsiao, Tzu-Hung; Chiu, Yu-Chiao; Hsu, Pei-Yin; Lu, Tzu-Pin; Lai, Liang-Chuan; Tsai, Mong-Hsun; Huang, Tim H.-M.; Chuang, Eric Y.; Chen, Yidong

2016-01-01

Several mutual information (MI)-based algorithms have been developed to identify dynamic gene-gene and function-function interactions governed by key modulators (genes, proteins, etc.). Due to intensive computation, however, these methods rely heavily on prior knowledge and are limited in genome-wide analysis. We present the modulated gene/gene set interaction (MAGIC) analysis to systematically identify genome-wide modulation of interaction networks. Based on a novel statistical test employing conjugate Fisher transformations of correlation coefficients, MAGIC features fast computation and adaption to variations of clinical cohorts. In simulated datasets MAGIC achieved greatly improved computation efficiency and overall superior performance than the MI-based method. We applied MAGIC to construct the estrogen receptor (ER) modulated gene and gene set (representing biological function) interaction networks in breast cancer. Several novel interaction hubs and functional interactions were discovered. ER+ dependent interaction between TGFβ and NFκB was further shown to be associated with patient survival. The findings were verified in independent datasets. Using MAGIC, we also assessed the essential roles of ER modulation in another hormonal cancer, ovarian cancer. Overall, MAGIC is a systematic framework for comprehensively identifying and constructing the modulated interaction networks in a whole-genome landscape. MATLAB implementation of MAGIC is available for academic uses at https://github.com/chiuyc/MAGIC. PMID:26972162
Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, Sang Hyun; Gao, Yaozong, E-mail: yzgao@cs.unc.edu; Shi, Yinghuan, E-mail: syh@nju.edu.cn

Purpose: Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correctmore » the segmentations from any type of automatic or interactive segmentation methods. Methods: The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. Results: The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to evaluate both the efficiency and the robustness. The automatic segmentation results with the original average Dice similarity coefficient of 0.78 were improved to 0.865–0.872 after conducting 55–59 interactions by using the proposed method, where each editing procedure took less than 3 s. In addition, the proposed method obtained the most consistent editing results with respect to different user interactions, compared to other methods. Conclusions: The proposed method obtains robust editing results with few interactions for various wrong segmentation cases, by selecting the location-adaptive features and further imposing the manifold regularization. The authors expect the proposed method to largely reduce the laborious burdens of manual editing, as well as both the intra- and interobserver variability across clinicians.« less
Physical and genetic-interaction density reveals functional organization and informs significance cutoffs in genome-wide screens

PubMed Central

Dittmar, John C.; Pierce, Steven; Rothstein, Rodney; Reid, Robert J. D.

2013-01-01

Genome-wide experiments often measure quantitative differences between treated and untreated cells to identify affected strains. For these studies, statistical models are typically used to determine significance cutoffs. We developed a method termed “CLIK” (Cutoff Linked to Interaction Knowledge) that overlays biological knowledge from the interactome on screen results to derive a cutoff. The method takes advantage of the fact that groups of functionally related interacting genes often respond similarly to experimental conditions and, thus, cluster in a ranked list of screen results. We applied CLIK analysis to five screens of the yeast gene disruption library and found that it defined a significance cutoff that differed from traditional statistics. Importantly, verification experiments revealed that the CLIK cutoff correlated with the position in the rank order where the rate of true positives drops off significantly. In addition, the gene sets defined by CLIK analysis often provide further biological perspectives. For example, applying CLIK analysis retrospectively to a screen for cisplatin sensitivity allowed us to identify the importance of the Hrq1 helicase in DNA crosslink repair. Furthermore, we demonstrate the utility of CLIK to determine optimal treatment conditions by analyzing genome-wide screens at multiple rapamycin concentrations. We show that CLIK is an extremely useful tool for evaluating screen quality, determining screen cutoffs, and comparing results between screens. Furthermore, because CLIK uses previously annotated interaction data to determine biologically informed cutoffs, it provides additional insights into screen results, which supplement traditional statistical approaches. PMID:23589890
Temporal information partitioning: Characterizing synergy, uniqueness, and redundancy in interacting environmental variables

NASA Astrophysics Data System (ADS)

Goodwell, Allison E.; Kumar, Praveen

2017-07-01

Information theoretic measures can be used to identify nonlinear interactions between source and target variables through reductions in uncertainty. In information partitioning, multivariate mutual information is decomposed into synergistic, unique, and redundant components. Synergy is information shared only when sources influence a target together, uniqueness is information only provided by one source, and redundancy is overlapping shared information from multiple sources. While this partitioning has been applied to provide insights into complex dependencies, several proposed partitioning methods overestimate redundant information and omit a component of unique information because they do not account for source dependencies. Additionally, information partitioning has only been applied to time-series data in a limited context, using basic pdf estimation techniques or a Gaussian assumption. We develop a Rescaled Redundancy measure (Rs) to solve the source dependency issue, and present Gaussian, autoregressive, and chaotic test cases to demonstrate its advantages over existing techniques in the presence of noise, various source correlations, and different types of interactions. This study constitutes the first rigorous application of information partitioning to environmental time-series data, and addresses how noise, pdf estimation technique, or source dependencies can influence detected measures. We illustrate how our techniques can unravel the complex nature of forcing and feedback within an ecohydrologic system with an application to 1 min environmental signals of air temperature, relative humidity, and windspeed. The methods presented here are applicable to the study of a broad range of complex systems composed of interacting variables.
Applications of IBSOM and ETEM for solving the nonlinear chains of atoms with long-range interactions

NASA Astrophysics Data System (ADS)

Foroutan, Mohammadreza; Zamanpour, Isa; Manafian, Jalil

2017-10-01

This paper presents a number of new solutions obtained for solving a complex nonlinear equation describing dynamics of nonlinear chains of atoms via the improved Bernoulli sub-ODE method (IBSOM) and the extended trial equation method (ETEM). The proposed solutions are kink solitons, anti-kink solitons, soliton solutions, hyperbolic solutions, trigonometric solutions, and bellshaped soliton solutions. Then our new results are compared with the well-known results. The methods used here are very simple and succinct and can be also applied to other nonlinear models. The balance number of these methods is not constant contrary to other methods. The proposed methods also allow us to establish many new types of exact solutions. By utilizing the Maple software package, we show that all obtained solutions satisfy the conditions of the studied model. More importantly, the solutions found in this work can have significant applications in Hamilton's equations and generalized momentum where solitons are used for long-range interactions.
Identification of New Genetic Susceptibility Loci for Breast Cancer Through Consideration of Gene-Environment Interactions

PubMed Central

Schoeps, Anja; Rudolph, Anja; Seibold, Petra; Dunning, Alison M.; Milne, Roger L.; Bojesen, Stig E.; Swerdlow, Anthony; Andrulis, Irene; Brenner, Hermann; Behrens, Sabine; Orr, Nicholas; Jones, Michael; Ashworth, Alan; Li, Jingmei; Cramp, Helen; Connley, Dan; Czene, Kamila; Darabi, Hatef; Chanock, Stephen J.; Lissowska, Jolanta; Figueroa, Jonine D.; Knight, Julia; Glendon, Gord; Mulligan, Anna M.; Dumont, Martine; Severi, Gianluca; Baglietto, Laura; Olson, Janet; Vachon, Celine; Purrington, Kristen; Moisse, Matthieu; Neven, Patrick; Wildiers, Hans; Spurdle, Amanda; Kosma, Veli-Matti; Kataja, Vesa; Hartikainen, Jaana M.; Hamann, Ute; Ko, Yon-Dschun; Dieffenbach, Aida K.; Arndt, Volker; Stegmaier, Christa; Malats, Núria; Arias Perez, JoséI.; Benítez, Javier; Flyger, Henrik; Nordestgaard, Børge G.; Truong, Théresè; Cordina-Duverger, Emilie; Menegaux, Florence; Silva, Isabel dos Santos; Fletcher, Olivia; Johnson, Nichola; Häberle, Lothar; Beckmann, Matthias W.; Ekici, Arif B.; Braaf, Linde; Atsma, Femke; van den Broek, Alexandra J.; Makalic, Enes; Schmidt, Daniel F.; Southey, Melissa C.; Cox, Angela; Simard, Jacques; Giles, Graham G.; Lambrechts, Diether; Mannermaa, Arto; Brauch, Hiltrud; Guénel, Pascal; Peto, Julian; Fasching, Peter A.; Hopper, John; Flesch-Janys, Dieter; Couch, Fergus; Chenevix-Trench, Georgia; Pharoah, Paul D. P.; Garcia-Closas, Montserrat; Schmidt, Marjanka K.; Hall, Per; Easton, Douglas F.; Chang-Claude, Jenny

2014-01-01

Genes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene-environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P-values = 3 × 10−07), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m2 (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m2 or higher (OR = 0.89, 95% CI 0.72–1.11, P for interaction = 3.2 × 10−05). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci. PMID:24248812

Reconstruction of metabolic pathways by combining probabilistic graphical model-based and knowledge-based methods

PubMed Central

2014-01-01

Automatic reconstruction of metabolic pathways for an organism from genomics and transcriptomics data has been a challenging and important problem in bioinformatics. Traditionally, known reference pathways can be mapped into an organism-specific ones based on its genome annotation and protein homology. However, this simple knowledge-based mapping method might produce incomplete pathways and generally cannot predict unknown new relations and reactions. In contrast, ab initio metabolic network construction methods can predict novel reactions and interactions, but its accuracy tends to be low leading to a lot of false positives. Here we combine existing pathway knowledge and a new ab initio Bayesian probabilistic graphical model together in a novel fashion to improve automatic reconstruction of metabolic networks. Specifically, we built a knowledge database containing known, individual gene / protein interactions and metabolic reactions extracted from existing reference pathways. Known reactions and interactions were then used as constraints for Bayesian network learning methods to predict metabolic pathways. Using individual reactions and interactions extracted from different pathways of many organisms to guide pathway construction is new and improves both the coverage and accuracy of metabolic pathway construction. We applied this probabilistic knowledge-based approach to construct the metabolic networks from yeast gene expression data and compared its results with 62 known metabolic networks in the KEGG database. The experiment showed that the method improved the coverage of metabolic network construction over the traditional reference pathway mapping method and was more accurate than pure ab initio methods. PMID:25374614
Ab initio O(N) elongation-counterpoise method for BSSE-corrected interaction energy analyses in biosystems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Orimoto, Yuuichi; Xie, Peng; Liu, Kai

2015-03-14

An Elongation-counterpoise (ELG-CP) method was developed for performing accurate and efficient interaction energy analysis and correcting the basis set superposition error (BSSE) in biosystems. The method was achieved by combining our developed ab initio O(N) elongation method with the conventional counterpoise method proposed for solving the BSSE problem. As a test, the ELG-CP method was applied to the analysis of the DNAs’ inter-strands interaction energies with respect to the alkylation-induced base pair mismatch phenomenon that causes a transition from G⋯C to A⋯T. It was found that the ELG-CP method showed high efficiency (nearly linear-scaling) and high accuracy with a negligiblymore » small energy error in the total energy calculations (in the order of 10{sup −7}–10{sup −8} hartree/atom) as compared with the conventional method during the counterpoise treatment. Furthermore, the magnitude of the BSSE was found to be ca. −290 kcal/mol for the calculation of a DNA model with 21 base pairs. This emphasizes the importance of BSSE correction when a limited size basis set is used to study the DNA models and compare small energy differences between them. In this work, we quantitatively estimated the inter-strands interaction energy for each possible step in the transition process from G⋯C to A⋯T by the ELG-CP method. It was found that the base pair replacement in the process only affects the interaction energy for a limited area around the mismatch position with a few adjacent base pairs. From the interaction energy point of view, our results showed that a base pair sliding mechanism possibly occurs after the alkylation of guanine to gain the maximum possible number of hydrogen bonds between the bases. In addition, the steps leading to the A⋯T replacement accompanied with replications were found to be unfavorable processes corresponding to ca. 10 kcal/mol loss in stabilization energy. The present study indicated that the ELG-CP method is promising for performing effective interaction energy analyses in biosystems.« less
A Type-2 fuzzy data fusion approach for building reliable weighted protein interaction networks with application in protein complex detection.

PubMed

Mehranfar, Adele; Ghadiri, Nasser; Kouhsar, Morteza; Golshani, Ashkan

2017-09-01

Detecting the protein complexes is an important task in analyzing the protein interaction networks. Although many algorithms predict protein complexes in different ways, surveys on the interaction networks indicate that about 50% of detected interactions are false positives. Consequently, the accuracy of existing methods needs to be improved. In this paper we propose a novel algorithm to detect the protein complexes in 'noisy' protein interaction data. First, we integrate several biological data sources to determine the reliability of each interaction and determine more accurate weights for the interactions. A data fusion component is used for this step, based on the interval type-2 fuzzy voter that provides an efficient combination of the information sources. This fusion component detects the errors and diminishes their effect on the detection protein complexes. So in the first step, the reliability scores have been assigned for every interaction in the network. In the second step, we have proposed a general protein complex detection algorithm by exploiting and adopting the strong points of other algorithms and existing hypotheses regarding real complexes. Finally, the proposed method has been applied for the yeast interaction datasets for predicting the interactions. The results show that our framework has a better performance regarding precision and F-measure than the existing approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.
Nonlinear Waves, Dynamical Systems and Other Applied Mathematics Programs

DTIC Science & Technology

1991-10-04

present a general scheme of perturbation method for perturbed soliton systems, based on the normal form theory and the method of multiple scales. By this...dimension, and discuss possible consequences of the interplay between wavefront- interactions and curvature in two dimensions. Thursday, October 19 All ... normal speed D parametrized by the local mean surface curvature x. Its solution provides a relation D = D(x) which determines the evolution of the front
Simulation of Vortex Structure in Supersonic Free Shear Layer Using Pse Method

NASA Astrophysics Data System (ADS)

Guo, Xin; Wang, Qiang

The method of parabolized stability equations (PSE) are applied in the analysis of nonlinear stability and the simulation of flow structure in supersonic free shear layer. High accuracy numerical techniques including self-similar basic flow, high order differential method, appropriate transformation and decomposition of nonlinear terms are adopted and developed to solve the PSE effectively for free shear layer. The spatial evolving unstable waves which dominate the flow structure are investigated through nonlinear coupling spatial marching methods. The nonlinear interactions between harmonic waves are further analyzed and instantaneous flow field are obtained by adding the harmonic waves into basic flow. Relevant data agree well with that of DNS. The results demonstrate that T-S wave does not keeping growing exponential as the linear evolution, the energy transfer to high order harmonic modes and finally all harmonic modes get saturation due to the nonlinear interaction; Mean flow distortion is produced by the nonlinear interaction between the harmonic and its conjugate harmonic, makes great change to the average flow and increases the thickness of shear layer; PSE methods can well capture the large scale nonlinear flow structure in the supersonic free shear layer such as vortex roll-up, vortex pairing and nonlinear saturation.
Using cluster ensemble and validation to identify subtypes of pervasive developmental disorders.

PubMed

Shen, Jess J; Lee, Phil-Hyoun; Holden, Jeanette J A; Shatkay, Hagit

2007-10-11

Pervasive Developmental Disorders (PDD) are neurodevelopmental disorders characterized by impairments in social interaction, communication and behavior. Given the diversity and varying severity of PDD, diagnostic tools attempt to identify homogeneous subtypes within PDD. Identifying subtypes can lead to targeted etiology studies and to effective type-specific intervention. Cluster analysis can suggest coherent subsets in data; however, different methods and assumptions lead to different results. Several previous studies applied clustering to PDD data, varying in number and characteristics of the produced subtypes. Most studies used a relatively small dataset (fewer than 150 subjects), and all applied only a single clustering method. Here we study a relatively large dataset (358 PDD patients), using an ensemble of three clustering methods. The results are evaluated using several validation methods, and consolidated through an integration step. Four clusters are identified, analyzed and compared to subtypes previously defined by the widely used diagnostic tool DSM-IV.
Using Cluster Ensemble and Validation to Identify Subtypes of Pervasive Developmental Disorders

PubMed Central

Shen, Jess J.; Lee, Phil Hyoun; Holden, Jeanette J.A.; Shatkay, Hagit

2007-01-01

Pervasive Developmental Disorders (PDD) are neurodevelopmental disorders characterized by impairments in social interaction, communication and behavior.1 Given the diversity and varying severity of PDD, diagnostic tools attempt to identify homogeneous subtypes within PDD. Identifying subtypes can lead to targeted etiology studies and to effective type-specific intervention. Cluster analysis can suggest coherent subsets in data; however, different methods and assumptions lead to different results. Several previous studies applied clustering to PDD data, varying in number and characteristics of the produced subtypes19. Most studies used a relatively small dataset (fewer than 150 subjects), and all applied only a single clustering method. Here we study a relatively large dataset (358 PDD patients), using an ensemble of three clustering methods. The results are evaluated using several validation methods, and consolidated through an integration step. Four clusters are identified, analyzed and compared to subtypes previously defined by the widely used diagnostic tool DSM-IV.2 PMID:18693920
A methodology for uncertainty quantification in quantitative technology valuation based on expert elicitation

NASA Astrophysics Data System (ADS)

Akram, Muhammad Farooq Bin

The management of technology portfolios is an important element of aerospace system design. New technologies are often applied to new product designs to ensure their competitiveness at the time they are introduced to market. The future performance of yet-to- be designed components is inherently uncertain, necessitating subject matter expert knowledge, statistical methods and financial forecasting. Estimates of the appropriate parameter settings often come from disciplinary experts, who may disagree with each other because of varying experience and background. Due to inherent uncertain nature of expert elicitation in technology valuation process, appropriate uncertainty quantification and propagation is very critical. The uncertainty in defining the impact of an input on performance parameters of a system makes it difficult to use traditional probability theory. Often the available information is not enough to assign the appropriate probability distributions to uncertain inputs. Another problem faced during technology elicitation pertains to technology interactions in a portfolio. When multiple technologies are applied simultaneously on a system, often their cumulative impact is non-linear. Current methods assume that technologies are either incompatible or linearly independent. It is observed that in case of lack of knowledge about the problem, epistemic uncertainty is the most suitable representation of the process. It reduces the number of assumptions during the elicitation process, when experts are forced to assign probability distributions to their opinions without sufficient knowledge. Epistemic uncertainty can be quantified by many techniques. In present research it is proposed that interval analysis and Dempster-Shafer theory of evidence are better suited for quantification of epistemic uncertainty in technology valuation process. Proposed technique seeks to offset some of the problems faced by using deterministic or traditional probabilistic approaches for uncertainty propagation. Non-linear behavior in technology interactions is captured through expert elicitation based technology synergy matrices (TSM). Proposed TSMs increase the fidelity of current technology forecasting methods by including higher order technology interactions. A test case for quantification of epistemic uncertainty on a large scale problem of combined cycle power generation system was selected. A detailed multidisciplinary modeling and simulation environment was adopted for this problem. Results have shown that evidence theory based technique provides more insight on the uncertainties arising from incomplete information or lack of knowledge as compared to deterministic or probability theory methods. Margin analysis was also carried out for both the techniques. A detailed description of TSMs and their usage in conjunction with technology impact matrices and technology compatibility matrices is discussed. Various combination methods are also proposed for higher order interactions, which can be applied according to the expert opinion or historical data. The introduction of technology synergy matrix enabled capturing the higher order technology interactions, and improvement in predicted system performance.
Minimum curvilinearity to enhance topological prediction of protein interactions by network embedding

PubMed Central

Cannistraci, Carlo Vittorio; Alanis-Lobato, Gregorio; Ravasi, Timothy

2013-01-01

Motivation: Most functions within the cell emerge thanks to protein–protein interactions (PPIs), yet experimental determination of PPIs is both expensive and time-consuming. PPI networks present significant levels of noise and incompleteness. Predicting interactions using only PPI-network topology (topological prediction) is difficult but essential when prior biological knowledge is absent or unreliable. Methods: Network embedding emphasizes the relations between network proteins embedded in a low-dimensional space, in which protein pairs that are closer to each other represent good candidate interactions. To achieve network denoising, which boosts prediction performance, we first applied minimum curvilinear embedding (MCE), and then adopted shortest path (SP) in the reduced space to assign likelihood scores to candidate interactions. Furthermore, we introduce (i) a new valid variation of MCE, named non-centred MCE (ncMCE); (ii) two automatic strategies for selecting the appropriate embedding dimension; and (iii) two new randomized procedures for evaluating predictions. Results: We compared our method against several unsupervised and supervisedly tuned embedding approaches and node neighbourhood techniques. Despite its computational simplicity, ncMCE-SP was the overall leader, outperforming the current methods in topological link prediction. Conclusion: Minimum curvilinearity is a valuable non-linear framework that we successfully applied to the embedding of protein networks for the unsupervised prediction of novel PPIs. The rationale for our approach is that biological and evolutionary information is imprinted in the non-linear patterns hidden behind the protein network topology, and can be exploited for predicting new protein links. The predicted PPIs represent good candidates for testing in high-throughput experiments or for exploitation in systems biology tools such as those used for network-based inference and prediction of disease-related functional modules. Availability: https://sites.google.com/site/carlovittoriocannistraci/home Contact: kalokagathos.agon@gmail.com or timothy.ravasi@kaust.edu.sa Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23812985
Multifactor-Dimensionality Reduction Reveals High-Order Interactions among Estrogen-Metabolism Genes in Sporadic Breast Cancer

PubMed Central

Ritchie, Marylyn D.; Hahn, Lance W.; Roodi, Nady; Bailey, L. Renee; Dupont, William D.; Parl, Fritz F.; Moore, Jason H.

2001-01-01

One of the greatest challenges facing human geneticists is the identification and characterization of susceptibility genes for common complex multifactorial human diseases. This challenge is partly due to the limitations of parametric-statistical methods for detection of gene effects that are dependent solely or partially on interactions with other genes and with environmental exposures. We introduce multifactor-dimensionality reduction (MDR) as a method for reducing the dimensionality of multilocus information, to improve the identification of polymorphism combinations associated with disease risk. The MDR method is nonparametric (i.e., no hypothesis about the value of a statistical parameter is made), is model-free (i.e., it assumes no particular inheritance model), and is directly applicable to case-control and discordant-sib-pair studies. Using simulated case-control data, we demonstrate that MDR has reasonable power to identify interactions among two or more loci in relatively small samples. When it was applied to a sporadic breast cancer case-control data set, in the absence of any statistically significant independent main effects, MDR identified a statistically significant high-order interaction among four polymorphisms from three different estrogen-metabolism genes. To our knowledge, this is the first report of a four-locus interaction associated with a common complex multifactorial disease. PMID:11404819
Detection of protein complex from protein-protein interaction network using Markov clustering

NASA Astrophysics Data System (ADS)

Ochieng, P. J.; Kusuma, W. A.; Haryanto, T.

2017-05-01

Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks.
Phase diagrams and free-energy landscapes for model spin-crossover materials with antiferromagnetic-like nearest-neighbor and ferromagnetic-like long-range interactions

NASA Astrophysics Data System (ADS)

Chan, C. H.; Brown, G.; Rikvold, P. A.

2017-11-01

We present phase diagrams, free-energy landscapes, and order-parameter distributions for a model spin-crossover material with a two-step transition between the high-spin and low-spin states (a square-lattice Ising model with antiferromagnetic-like nearest-neighbor and ferromagnetic-like long-range interactions) [P. A. Rikvold et al., Phys. Rev. B 93, 064109 (2016), 10.1103/PhysRevB.93.064109]. The results are obtained by a recently introduced, macroscopically constrained Wang-Landau Monte Carlo simulation method [Phys. Rev. E 95, 053302 (2017), 10.1103/PhysRevE.95.053302]. The method's computational efficiency enables calculation of thermodynamic quantities for a wide range of temperatures, applied fields, and long-range interaction strengths. For long-range interactions of intermediate strength, tricritical points in the phase diagrams are replaced by pairs of critical end points and mean-field critical points that give rise to horn-shaped regions of metastability. The corresponding free-energy landscapes offer insights into the nature of asymmetric, multiple hysteresis loops that have been experimentally observed in spin-crossover materials characterized by competing short-range interactions and long-range elastic interactions.
Hydration of Li+ -ion in atom-bond electronegativity equalization method-7P water: a molecular dynamics simulation study.

PubMed

Li, Xin; Yang, Zhong-Zhi

2005-02-22

We have carried out molecular dynamics simulations of a Li(+) ion in water over a wide range of temperature (from 248 to 368 K). The simulations make use of the atom-bond electronegativity equalization method-7P water model, a seven-site flexible model with fluctuating charges, which has accurately reproduced many bulk water properties. The recently constructed Li(+)-water interaction potential through fitting to the experimental and ab initio gas-phase binding energies and to the measured structures for Li(+)-water clusters is adopted in the simulations. ABEEM was proposed and developed in terms of partitioning the electron density into atom and bond regions and using the electronegativity equalization method (EEM) and the density functional theory (DFT). Based on a combination of the atom-bond electronegativity equalization method and molecular mechanics (ABEEM/MM), a new set of water-water and Li(+)-water potentials, successfully applied to ionic clusters Li(+)(H(2)O)(n)(n=1-6,8), are further investigated in an aqueous solution of Li(+) in the present paper. Two points must be emphasized in the simulations: first, the model allows for the charges on the interacting sites fluctuating as a function of time; second, the ABEEM-7P model has applied the parameter k(lp,H)(R(lp,H)) to explicitly describe the short-range interaction of hydrogen bond in the hydrogen bond interaction region, and has a new description for the hydrogen bond. The static, dynamic, and thermodynamic properties have been studied in detail. In addition, at different temperatures, the structural properties such as radial distribution functions, and the dynamical properties such as diffusion coefficients and residence times of the water molecules in the first hydration shell of Li(+), are also simulated well. These simulation results show that the ABEEM/MM-based water-water and Li(+)-water potentials appear to be robust giving the overall characteristic hydration properties in excellent agreement with experiments and other molecular dynamics simulations on similar system.
A new methodical approach in neuroscience: assessing inter-personal brain coupling using functional near-infrared imaging (fNIRI) hyperscanning.

PubMed

Scholkmann, Felix; Holper, Lisa; Wolf, Ursula; Wolf, Martin

2013-11-27

Since the first demonstration of how to simultaneously measure brain activity using functional magnetic resonance imaging (fMRI) on two subjects about 10 years ago, a new paradigm in neuroscience is emerging: measuring brain activity from two or more people simultaneously, termed "hyperscanning". The hyperscanning approach has the potential to reveal inter-personal brain mechanisms underlying interaction-mediated brain-to-brain coupling. These mechanisms are engaged during real social interactions, and cannot be captured using single-subject recordings. In particular, functional near-infrared imaging (fNIRI) hyperscanning is a promising new method, offering a cost-effective, easy to apply and reliable technology to measure inter-personal interactions in a natural context. In this short review we report on fNIRI hyperscanning studies published so far and summarize opportunities and challenges for future studies.
Content-specific network analysis of peer-to-peer communication in an online community for smoking cessation.

PubMed

Myneni, Sahiti; Cobb, Nathan K; Cohen, Trevor

2016-01-01

Analysis of user interactions in online communities could improve our understanding of health-related behaviors and inform the design of technological solutions that support behavior change. However, to achieve this we would need methods that provide granular perspective, yet are scalable. In this paper, we present a methodology for high-throughput semantic and network analysis of large social media datasets, combining semi-automated text categorization with social network analytics. We apply this method to derive content-specific network visualizations of 16,492 user interactions in an online community for smoking cessation. Performance of the categorization system was reasonable (average F-measure of 0.74, with system-rater reliability approaching rater-rater reliability). The resulting semantically specific network analysis of user interactions reveals content- and behavior-specific network topologies. Implications for socio-behavioral health and wellness platforms are also discussed.
Automated breast segmentation in ultrasound computer tomography SAFT images

NASA Astrophysics Data System (ADS)

Hopp, T.; You, W.; Zapf, M.; Tan, W. Y.; Gemmeke, H.; Ruiter, N. V.

2017-03-01

Ultrasound Computer Tomography (USCT) is a promising new imaging system for breast cancer diagnosis. An essential step before further processing is to remove the water background from the reconstructed images. In this paper we present a fully-automated image segmentation method based on three-dimensional active contours. The active contour method is extended by applying gradient vector flow and encoding the USCT aperture characteristics as additional weighting terms. A surface detection algorithm based on a ray model is developed to initialize the active contour, which is iteratively deformed to capture the breast outline in USCT reflection images. The evaluation with synthetic data showed that the method is able to cope with noisy images, and is not influenced by the position of the breast and the presence of scattering objects within the breast. The proposed method was applied to 14 in-vivo images resulting in an average surface deviation from a manual segmentation of 2.7 mm. We conclude that automated segmentation of USCT reflection images is feasible and produces results comparable to a manual segmentation. By applying the proposed method, reproducible segmentation results can be obtained without manual interaction by an expert.
Identification of genes related to proliferative diabetic retinopathy through RWR algorithm based on protein-protein interaction network.

PubMed

Zhang, Jian; Suo, Yan; Liu, Min; Xu, Xun

2018-06-01

Proliferative diabetic retinopathy (PDR) is one of the most common complications of diabetes and can lead to blindness. Proteomic studies have provided insight into the pathogenesis of PDR and a series of PDR-related genes has been identified but are far from fully characterized because the experimental methods are expensive and time consuming. In our previous study, we successfully identified 35 candidate PDR-related genes through the shortest-path algorithm. In the current study, we developed a computational method using the random walk with restart (RWR) algorithm and the protein-protein interaction (PPI) network to identify potential PDR-related genes. After some possible genes were obtained by the RWR algorithm, a three-stage filtration strategy, which includes the permutation test, interaction test and enrichment test, was applied to exclude potential false positives caused by the structure of PPI network, the poor interaction strength, and the limited similarity on gene ontology (GO) terms and biological pathways. As a result, 36 candidate genes were discovered by the method which was different from the 35 genes reported in our previous study. A literature review showed that 21 of these 36 genes are supported by previous experiments. These findings suggest the robustness and complementary effects of both our efforts using different computational methods, thus providing an alternative method to study PDR pathogenesis. Copyright © 2017 Elsevier B.V. All rights reserved.
Interactive, Learner-Centered Methods of Teaching Mathematics

ERIC Educational Resources Information Center

Alsardary, Salar; Blumberg, Phyllis

2009-01-01

We describe a learner-centered upper-level mathematics course where the students present the material to the class instead of the instructor, and the students make presentations on applied topics at the regional MAA meeting. After take-home examinations the students can discuss their answers one-on-one with the instructor. The students liked the…
Pedagogical Considerations for Effectively Teaching Qualitative Research to Students in an Online Environment

ERIC Educational Resources Information Center

Bender, Sara; Hill, Karlie

2016-01-01

Qualitative research aims to understand both individual meaning as well as complex systemic interactions as they apply to social problems or individual experiences. This method of research is both inductive and flexible, allowing for a holistic approach that facilitates a rich understanding of the content examined. Past research identifies a…
Development of Independence among Future Primary School Teachers by Applying Interactive Learning Methods

ERIC Educational Resources Information Center

Rotova, Natalia Alexandrovna

2018-01-01

The necessity to develop independence among future primary school teachers during the process of studying in higher education institutions is substantiated. The essentials of independence notion are disclosed as efforts of students aimed at reaching the goals single-handedly. The results of the ascertaining experiment on defining the level of…

Inquiry Practices in Malaysian Secondary Classroom and Model of Inquiry Teaching Based on Verbal Interaction

ERIC Educational Resources Information Center

Li, Winnie Sim Siew; Arshad, Mohammad Yusof

2015-01-01

Purpose: Inquiry teaching has been suggested as one of the important approaches in teaching chemistry. This study investigates the inquiry practices among chemistry teachers. Method: A combination of quantitative and qualitative study was applied in this study to provide detailed information about inquiry teaching practices. Questionnaires,…
Psychiatric Training Program Engagement with the Pharmaceutical Industry: An Educational Issue, Not Strictly an Ethical One

ERIC Educational Resources Information Center

Mohl, Paul C.

2005-01-01

OBJECTIVE: To analyze the educational and ethical issues involved in interactions between departments of psychiatry and the pharmaceutical industry. METHODS: The author analyzes the history of attitudes toward pharmaceutical companies, various conflicting ethical principles that apply, and areas of confluence and conflict of interest between…
A Bayesian Method for Evaluating Trainee Proficiency. Technical Paper 323.

ERIC Educational Resources Information Center

Epstein, Kenneth I.; Steinheiser, Frederick H., Jr.

A multiparameter, programmable model was developed to examine the interactive influence of certain parameters on the probability of deciding that an examinee had attained a specified degree of mastery. It was applied within the simulated context of performance testing of military trainees. These parameters included: (1) the number of assumed…
A Comparison of Four Approaches to Account for Method Effects in Latent State-Trait Analyses

ERIC Educational Resources Information Center

Geiser, Christian; Lockhart, Ginger

2012-01-01

Latent state-trait (LST) analysis is frequently applied in psychological research to determine the degree to which observed scores reflect stable person-specific effects, effects of situations and/or person-situation interactions, and random measurement error. Most LST applications use multiple repeatedly measured observed variables as indicators…
Virus immobilization on biomaterial scaffolds through biotin-avidin interaction for improving bone regeneration.

PubMed

Hu, Wei-Wen; Wang, Zhuo; Krebsbach, Paul H

2016-02-01

To spatially control therapeutic gene delivery for potential tissue engineering applications, a biotin-avidin interaction strategy was applied to immobilize viral vectors on biomaterial scaffolds. Both adenoviral vectors and gelatin sponges were biotinylated and avidin was applied to link them in a virus-biotin-avidin-biotin-material (VBABM) arrangement. The tethered viral particles were stably maintained within scaffolds and SEM images illustrated that viral particles were evenly distributed in three-dimensional (3D) gelatin sponges. An in vivo study demonstrated that transgene expression was restricted to the implant sites only and transduction efficiency was improved using this conjugation method. For an orthotopic bone regeneration model, adenovirus encoding BMP-2 (AdBMP2) was immobilized to gelatin sponges before implanting into critical-sized bone defects in rat calvaria. Compared to gelatin sponges with AdBMP2 loaded in a freely suspended form, the VBABM method enhanced gene transfer and bone regeneration was significantly improved. These results suggest that biotin-avidin immobilization of viral vectors to biomaterial scaffolds may be an effective strategy to facilitate tissue regeneration. Copyright © 2013 John Wiley & Sons, Ltd.
Anharmonic phonon-phonon scattering modeling of three-dimensional atomistic transport: An efficient quantum treatment

NASA Astrophysics Data System (ADS)

Lee, Y.; Bescond, M.; Logoteta, D.; Cavassilas, N.; Lannoo, M.; Luisier, M.

2018-05-01

We propose an efficient method to quantum mechanically treat anharmonic interactions in the atomistic nonequilibrium Green's function simulation of phonon transport. We demonstrate that the so-called lowest-order approximation, implemented through a rescaling technique and analytically continued by means of the Padé approximants, can be used to accurately model third-order anharmonic effects. Although the paper focuses on a specific self-energy, the method is applicable to a very wide class of physical interactions. We apply this approach to the simulation of anharmonic phonon transport in realistic Si and Ge nanowires with uniform or discontinuous cross sections. The effect of increasing the temperature above 300 K is also investigated. In all the considered cases, we are able to obtain a good agreement with the routinely adopted self-consistent Born approximation, at a remarkably lower computational cost. In the more complicated case of high temperatures (≫300 K), we find that the first-order Richardson extrapolation applied to the sequence of the Padé approximants N -1 /N results in a significant acceleration of the convergence.
Interaction between moving tandem wheels and an infinite rail with periodic supports - Green's matrices of the track method in stationary reference frame

NASA Astrophysics Data System (ADS)

Mazilu, Traian

2017-08-01

This paper approaches the issue of the interaction between moving tandem wheels and an infinite periodically supported rail and points out at the basic characteristics in the steady-state interaction behaviour and in the interaction in the presence of the rail random irregularity. The rail is modelled as an infinite Timoshenko beam resting on supports which are discretely modelling the inertia of the sleepers and ballast and also the viscoelastic features of the rail pads, the ballast and the subgrade. Green‧s matrices of the track method in stationary reference frame were applied so as to conduct the time-domain analysis. This method allows to consider the nonlinearities of the wheel/rail contact and the Doppler effect. The study highlights certain aspects regarding the influence of the wheel base on the wheels/rail contact forces, particularly at the parametric resonance, due to the coincidence between the wheel/rail natural frequency and the passing frequency and also when the rail surface exhibits random irregularity. It has been shown that the wheel/rail dynamic behaviour is less intense when the wheel base equals integer multiple of the sleeper bay.
Fast Electron Correlation Methods for Molecular Clusters without Basis Set Superposition Errors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kamiya, Muneaki; Hirata, So; Valiev, Marat

2008-02-19

Two critical extensions to our fast, accurate, and easy-to-implement binary or ternary interaction method for weakly-interacting molecular clusters [Hirata et al. Mol. Phys. 103, 2255 (2005)] have been proposed, implemented, and applied to water hexamers, hydrogen fluoride chains and rings, and neutral and zwitterionic glycine–water clusters with an excellent result for an initial performance assessment. Our original method included up to two- or three-body Coulomb, exchange, and correlation energies exactly and higher-order Coulomb energies in the dipole–dipole approximation. In this work, the dipole moments are replaced by atom-centered point charges determined so that they reproduce the electrostatic potentials of themore » cluster subunits as closely as possible and also self-consistently with one another in the cluster environment. They have been shown to lead to dramatic improvement in the description of short-range electrostatic potentials not only of large, charge-separated subunits like zwitterionic glycine but also of small subunits. Furthermore, basis set superposition errors (BSSE) known to plague direct evaluation of weak interactions have been eliminated by com-bining the Valiron–Mayer function counterpoise (VMFC) correction with our binary or ternary interaction method in an economical fashion (quadratic scaling n2 with respect to the number of subunits n when n is small and linear scaling when n is large). A new variant of VMFC has also been proposed in which three-body and all higher-order Coulomb effects on BSSE are estimated approximately. The BSSE-corrected ternary interaction method with atom-centered point charges reproduces the VMFC-corrected results of conventional electron correlation calculations within 0.1 kcal/mol. The proposed method is significantly more accurate and also efficient than conventional correlation methods uncorrected of BSSE.« less
Elastic interactions of a fatigue crack with a micro-defect by the mixed boundary integral equation method

NASA Technical Reports Server (NTRS)

Lua, Yuan J.; Liu, Wing K.; Belytschko, Ted

1993-01-01

In this paper, the mixed boundary integral equation method is developed to study the elastic interactions of a fatigue crack and a micro-defect such as a void, a rigid inclusion or a transformation inclusion. The method of pseudo-tractions is employed to study the effect of a transformation inclusion. An enriched element which incorporates the mixed-mode stress intensity factors is applied to characterize the singularity at a moving crack tip. In order to evaluate the accuracy of the numerical procedure, the analysis of a crack emanating from a circular hole in a finite plate is performed and the results are compared with the available numerical solution. The effects of various micro-defects on the crack path and fatigue life are investigated. The results agree with the experimental observations.
Two complementary reversed-phase separations for comprehensive coverage of the semipolar and nonpolar metabolome.

PubMed

Naser, Fuad J; Mahieu, Nathaniel G; Wang, Lingjue; Spalding, Jonathan L; Johnson, Stephen L; Patti, Gary J

2018-02-01

Although it is common in untargeted metabolomics to apply reversed-phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC) methods that have been systematically optimized for lipids and central carbon metabolites, here we show that these established protocols provide poor coverage of semipolar metabolites because of inadequate retention. Our objective was to develop an RPLC approach that improved detection of these metabolites without sacrificing lipid coverage. We initially evaluated columns recently released by Waters under the CORTECS line by analyzing 47 small-molecule standards that evenly span the nonpolar and semipolar ranges. An RPLC method commonly used in untargeted metabolomics was considered a benchmarking reference. We found that highly nonpolar and semipolar metabolites cannot be reliably profiled with any single method because of retention and solubility limitations of the injection solvent. Instead, we optimized a multiplexed approach using the CORTECS T3 column to analyze semipolar compounds and the CORTECS C 8 column to analyze lipids. Strikingly, we determined that combining these methods allowed detection of 41 of the total 47 standards, whereas our reference RPLC method detected only 10 of the 47 standards. We then applied credentialing to compare method performance at the comprehensive scale. The tandem method showed more than a fivefold increase in credentialing coverage relative to our RPLC benchmark. Our results demonstrate that comprehensive coverage of metabolites amenable to reversed-phase separation necessitates two reconstitution solvents and chromatographic methods. Thus, we suggest complementing HILIC methods with a dual T3 and C 8 RPLC approach to increase coverage of semipolar metabolites and lipids for untargeted metabolomics. Graphical abstract Analysis of semipolar and nonpolar metabolites necessitates two reversed-phase chromatography (RPLC) methods, which extend metabolome coverage more than fivefold for untargeted profiling. HILIC hydrophilic interaction liquid chromatography.
The penalty immersed boundary method and its application to aerodynamics

NASA Astrophysics Data System (ADS)

Kim, Yongsam

The Immersed Boundary (IB) method has been widely applied to problems involving a moving elastic boundary that is immersed in fluid and interacting with it. But most applications of the IB method have involved a massless elastic boundary. Extending the method to cover the case of a massive boundary has required spreading the boundary mass out onto the fluid grid and then solving the Navier-Stokes equations with a variable mass density. The variable mass density makes Fourier transform methods inapplicable, and requires a multigrid solver. Here we propose a new and simple way to give mass to the elastic boundary. The key idea of the method is to introduce two representations of each boundary: one is a massive boundary which does not interact with the fluid, and the other is messless and plays the same role as the boundary of the IB method with the massless assumption. Although they are almost the same, we allow these two representations of the boundary to be different as long as the gap between them is small. This can be ensured by connecting them with a stiff spring with a zero rest length which generates force acting on both boundaries and pulling them together. We call this the 'Penalty IB method'. It does not spread mass to the fluid grid, retains the use of Fourier transform methodology, and is easy to implement in the context of an existing IB method code for the massless case. This thesis introduces the Penalty IB method and applies it to several problems in which the mass of the boundary is important. These problems are filaments in a flowing soap film, flows past a cylinder, windsocks, flags, and parachutes.
Changing learning with new interactive and media-rich instruction environments: virtual labs case study report.

PubMed

Huang, Camillan

2003-01-01

Technology has created a new dimension for visual teaching and learning with web-delivered interactive media. The Virtual Labs Project has embraced this technology with instructional design and evaluation methodologies behind the simPHYSIO suite of simulation-based, online interactive teaching modules in physiology for the Stanford students. In addition, simPHYSIO provides the convenience of anytime web-access and a modular structure that allows for personalization and customization of the learning material. This innovative tool provides a solid delivery and pedagogical backbone that can be applied to developing an interactive simulation-based training tool for the use and management of the Picture Archiving and Communication System (PACS) image information system. The disparity in the knowledge between health and IT professionals can be bridged by providing convenient modular teaching tools to fill the gaps in knowledge. An innovative teaching method in the whole PACS is deemed necessary for its successful implementation and operation since it has become widely distributed with many interfaces, components, and customizations. This paper will discuss the techniques for developing an interactive-based teaching tool, a case study of its implementation, and a perspective for applying this approach to an online PACS training tool. Copyright 2002 Elsevier Science Ltd.
Using affinity capillary electrophoresis and computational models for binding studies of heparinoids with p-selectin and other proteins.

PubMed

Mozafari, Mona; Balasupramaniam, Shantheya; Preu, Lutz; El Deeb, Sami; Reiter, Christian G; Wätzig, Hermann

2017-06-01

A fast and precise affinity capillary electrophoresis (ACE) method has been developed and applied for the investigation of the binding interactions between P-selectin and heparinoids as potential P-selectin inhibitors in the presence and absence of calcium ions. Furthermore, model proteins and vitronectin were used to appraise the binding behavior of P-selectin. The normalized mobility ratios (∆R/R f ), which provided information about the binding strength and the overall charge of the protein-ligand complex, were used to evaluate the binding affinities. It was found that P-selectin interacts more strongly with heparinoids in the presence of calcium ions. P-selectin was affected by heparinoids at the concentration of 3 mg/L. In addition, the results of the ACE experiments showed that among other investigated proteins, albumins and vitronectin exhibited strong interactions with heparinoids. Especially with P-selectin and vitronectin, the interaction may additionally induce conformational changes. Subsequently, computational models were applied to interpret the ACE experiments. Docking experiments explained that the binding of heparinoids on P-selectin is promoted by calcium ions. These docking models proved to be particularly well suited to investigate the interaction of charged compounds, and are therefore complementary to ACE experiments. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Deconvolving molecular signatures of interactions between microbial colonies

PubMed Central

Harn, Y.-C.; Powers, M. J.; Shank, E. A.; Jojic, V.

2015-01-01

Motivation: The interactions between microbial colonies through chemical signaling are not well understood. A microbial colony can use different molecules to inhibit or accelerate the growth of other colonies. A better understanding of the molecules involved in these interactions could lead to advancements in health and medicine. Imaging mass spectrometry (IMS) applied to co-cultured microbial communities aims to capture the spatial characteristics of the colonies’ molecular fingerprints. These data are high-dimensional and require computational analysis methods to interpret. Results: Here, we present a dictionary learning method that deconvolves spectra of different molecules from IMS data. We call this method MOLecular Dictionary Learning (MOLDL). Unlike standard dictionary learning methods which assume Gaussian-distributed data, our method uses the Poisson distribution to capture the count nature of the mass spectrometry data. Also, our method incorporates universally applicable information on common ion types of molecules in MALDI mass spectrometry. This greatly reduces model parameterization and increases deconvolution accuracy by eliminating spurious solutions. Moreover, our method leverages the spatial nature of IMS data by assuming that nearby locations share similar abundances, thus avoiding overfitting to noise. Tests on simulated datasets show that this method has good performance in recovering molecule dictionaries. We also tested our method on real data measured on a microbial community composed of two species. We confirmed through follow-up validation experiments that our method recovered true and complete signatures of molecules. These results indicate that our method can discover molecules in IMS data reliably, and hence can help advance the study of interaction of microbial colonies. Availability and implementation: The code used in this paper is available at: https://github.com/frizfealer/IMS_project. Contact: vjojic@cs.unc.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26072476
A design automation framework for computational bioenergetics in biological networks.

PubMed

Angione, Claudio; Costanza, Jole; Carapezza, Giovanni; Lió, Pietro; Nicosia, Giuseppe

2013-10-01

The bioenergetic activity of mitochondria can be thoroughly investigated by using computational methods. In particular, in our work we focus on ATP and NADH, namely the metabolites representing the production of energy in the cell. We develop a computational framework to perform an exhaustive investigation at the level of species, reactions, genes and metabolic pathways. The framework integrates several methods implementing the state-of-the-art algorithms for many-objective optimization, sensitivity, and identifiability analysis applied to biological systems. We use this computational framework to analyze three case studies related to the human mitochondria and the algal metabolism of Chlamydomonas reinhardtii, formally described with algebraic differential equations or flux balance analysis. Integrating the results of our framework applied to interacting organelles would provide a general-purpose method for assessing the production of energy in a biological network.
Probing dynamical symmetry breaking using quantum-entangled photons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Hao; Piryatinski, Andrei; Jerke, Jonathan

Here, we present an input/output analysis of photon-correlation experiments whereby a quantum mechanically entangled bi-photon state interacts with a material sample placed in one arm of a Hong–Ou–Mandel apparatus. We show that the output signal contains detailed information about subsequent entanglement with the microscopic quantum states in the sample. In particular, we apply the method to an ensemble of emitters interacting with a common photon mode within the open-system Dicke model. Our results indicate considerable dynamical information concerning spontaneous symmetry breaking can be revealed with such an experimental system.
Immunoassay for Visualization of Protein-Protein Interactions on Ni-Nitrilotriacetate Support: Example of a Laboratory Exercise with Recombinant Heterotrimeric G[alpha][subscript i2][beta][subscript 1[gamma]2] Tagged by Hexahistidine from sf9 Cells

ERIC Educational Resources Information Center

Bavec, Aljosa

2004-01-01

We have developed an "in vitro assay" for following the interaction between the [alpha][subscript i2] subunit and [beta][subscript 1[gamma]2] dimer from sf9 cells. This method is suitable for education purposes because it is easy, reliable, nonexpensive, can be applied for a big class of 20 students, and avoid the commonly used kinetic approach,…
Probing dynamical symmetry breaking using quantum-entangled photons

DOE PAGES

Li, Hao; Piryatinski, Andrei; Jerke, Jonathan; ...

2017-11-15

Here, we present an input/output analysis of photon-correlation experiments whereby a quantum mechanically entangled bi-photon state interacts with a material sample placed in one arm of a Hong–Ou–Mandel apparatus. We show that the output signal contains detailed information about subsequent entanglement with the microscopic quantum states in the sample. In particular, we apply the method to an ensemble of emitters interacting with a common photon mode within the open-system Dicke model. Our results indicate considerable dynamical information concerning spontaneous symmetry breaking can be revealed with such an experimental system.
Hot-spot analysis for drug discovery targeting protein-protein interactions.

PubMed

Rosell, Mireia; Fernández-Recio, Juan

2018-04-01

Protein-protein interactions are important for biological processes and pathological situations, and are attractive targets for drug discovery. However, rational drug design targeting protein-protein interactions is still highly challenging. Hot-spot residues are seen as the best option to target such interactions, but their identification requires detailed structural and energetic characterization, which is only available for a tiny fraction of protein interactions. Areas covered: In this review, the authors cover a variety of computational methods that have been reported for the energetic analysis of protein-protein interfaces in search of hot-spots, and the structural modeling of protein-protein complexes by docking. This can help to rationalize the discovery of small-molecule inhibitors of protein-protein interfaces of therapeutic interest. Computational analysis and docking can help to locate the interface, molecular dynamics can be used to find suitable cavities, and hot-spot predictions can focus the search for inhibitors of protein-protein interactions. Expert opinion: A major difficulty for applying rational drug design methods to protein-protein interactions is that in the majority of cases the complex structure is not available. Fortunately, computational docking can complement experimental data. An interesting aspect to explore in the future is the integration of these strategies for targeting PPIs with large-scale mutational analysis.
Improving machine learning reproducibility in genetic association studies with proportional instance cross validation (PICV).

PubMed

Piette, Elizabeth R; Moore, Jason H

2018-01-01

Machine learning methods and conventions are increasingly employed for the analysis of large, complex biomedical data sets, including genome-wide association studies (GWAS). Reproducibility of machine learning analyses of GWAS can be hampered by biological and statistical factors, particularly so for the investigation of non-additive genetic interactions. Application of traditional cross validation to a GWAS data set may result in poor consistency between the training and testing data set splits due to an imbalance of the interaction genotypes relative to the data as a whole. We propose a new cross validation method, proportional instance cross validation (PICV), that preserves the original distribution of an independent variable when splitting the data set into training and testing partitions. We apply PICV to simulated GWAS data with epistatic interactions of varying minor allele frequencies and prevalences and compare performance to that of a traditional cross validation procedure in which individuals are randomly allocated to training and testing partitions. Sensitivity and positive predictive value are significantly improved across all tested scenarios for PICV compared to traditional cross validation. We also apply PICV to GWAS data from a study of primary open-angle glaucoma to investigate a previously-reported interaction, which fails to significantly replicate; PICV however improves the consistency of testing and training results. Application of traditional machine learning procedures to biomedical data may require modifications to better suit intrinsic characteristics of the data, such as the potential for highly imbalanced genotype distributions in the case of epistasis detection. The reproducibility of genetic interaction findings can be improved by considering this variable imbalance in cross validation implementation, such as with PICV. This approach may be extended to problems in other domains in which imbalanced variable distributions are a concern.

Current and future contraceptive options for women living with HIV

PubMed Central

Patel, Rena C.; Bukusi, Elizabeth A.; Baeten, Jared M.

2018-01-01

Introduction Among women living with HIV, half of the pregnancies are unintended. Effective contraception can prevent unintended pregnancies and consequently reduce maternal mortality and perinatal transmission of HIV. While contraceptive options available for all women also apply to women living with HIV, specific considerations exist to the use of contraception by women living with HIV. Areas covered First, general principles guiding the use of contraception among women living with HIV are discussed, such as choice, method mix, relative effectiveness, and drug-drug interactions. Second, a detailed discussion of each contraceptive method and issues surrounding the use of that method, such as drug-drug interactions, follows. Third, future contraceptive options in advanced development for use by women or men are briefly discussed. Expert opinion Contraceptive methods available to all women should also be accessible to women living with HIV. When the relative effectiveness of a contraceptive method is reduced, for example due to drug-drug interactions with antiretrovirals, the method should still be made available to women living with HIV with the appropriate information sharing and counseling. Greater research on various aspects of contraceptive use by women living with HIV and more comprehensive testing of co-administration of hormonal contraceptives and common medications used by these women are warranted. PMID:28891343
Current and future contraceptive options for women living with HIV.

PubMed

Patel, Rena C; Bukusi, Elizabeth A; Baeten, Jared M

2018-01-01

Among women living with HIV, half of the pregnancies are unintended. Effective contraception can prevent unintended pregnancies and consequently reduce maternal mortality and perinatal transmission of HIV. While contraceptive options available for all women also apply to women living with HIV, specific considerations exist to the use of contraception by women living with HIV. Areas covered: First, general principles guiding the use of contraception among women living with HIV are discussed, such as choice, method mix, relative effectiveness, and drug-drug interactions. Second, a detailed discussion of each contraceptive method and issues surrounding the use of that method, such as drug-drug interactions, follows. Third, future contraceptive options in advanced development for use by women or men are briefly discussed. Expert opinion: Contraceptive methods available to all women should also be accessible to women living with HIV. When the relative effectiveness of a contraceptive method is reduced, for example due to drug-drug interactions with antiretrovirals, the method should still be made available to women living with HIV with the appropriate information sharing and counseling. Greater research on various aspects of contraceptive use by women living with HIV and more comprehensive testing of co-administration of hormonal contraceptives and common medications used by these women are warranted.
Interpreting the cross-sectional flow field in a river bank based on a genetic-algorithm two-dimensional heat-transport method (GA-VS2DH)

NASA Astrophysics Data System (ADS)

Su, Xiaoru; Shu, Longcang; Chen, Xunhong; Lu, Chengpeng; Wen, Zhonghui

2016-12-01

Interactions between surface waters and groundwater are of great significance for evaluating water resources and protecting ecosystem health. Heat as a tracer method is widely used in determination of the interactive exchange with high precision, low cost and great convenience. The flow in a river-bank cross-section occurs in vertical and lateral directions. In order to depict the flow path and its spatial distribution in bank areas, a genetic algorithm (GA) two-dimensional (2-D) heat-transport nested-loop method for variably saturated sediments, GA-VS2DH, was developed based on Microsoft Visual Basic 6.0. VS2DH was applied to model a 2-D bank-water flow field and GA was used to calibrate the model automatically by minimizing the difference between observed and simulated temperatures in bank areas. A hypothetical model was developed to assess the reliability of GA-VS2DH in inverse modeling in a river-bank system. Some benchmark tests were conducted to recognize the capability of GA-VS2DH. The results indicated that the simulated seepage velocity and parameters associated with GA-VS2DH were acceptable and reliable. Then GA-VS2DH was applied to two field sites in China with different sedimentary materials, to verify the reliability of the method. GA-VS2DH could be applied in interpreting the cross-sectional 2-D water flow field. The estimates of horizontal hydraulic conductivity at the Dawen River and Qinhuai River sites are 1.317 and 0.015 m/day, which correspond to sand and clay sediment in the two sites, respectively.
Analytical Quality by Design in pharmaceutical quality assurance: Development of a capillary electrophoresis method for the analysis of zolmitriptan and its impurities.

PubMed

Orlandini, Serena; Pasquini, Benedetta; Caprini, Claudia; Del Bubba, Massimo; Pinzauti, Sergio; Furlanetto, Sandra

2015-11-01

A fast and selective CE method for the determination of zolmitriptan (ZOL) and its five potential impurities has been developed applying the analytical Quality by Design principles. Voltage, temperature, buffer concentration, and pH were investigated as critical process parameters that can influence the critical quality attributes, represented by critical resolution values between peak pairs, analysis time, and peak efficiency of ZOL-dimer. A symmetric screening matrix was employed for investigating the knowledge space, and a Box-Behnken design was used to evaluate the main, interaction, and quadratic effects of the critical process parameters on the critical quality attributes. Contour plots were drawn highlighting important interactions between buffer concentration and pH, and the gained information was merged into the sweet spot plots. Design space (DS) was established by the combined use of response surface methodology and Monte Carlo simulations, introducing a probability concept and thus allowing the quality of the analytical performances to be assured in a defined domain. The working conditions (with the interval defining the DS) were as follows: BGE, 138 mM (115-150 mM) phosphate buffer pH 2.74 (2.54-2.94); temperature, 25°C (24-25°C); voltage, 30 kV. A control strategy was planned based on method robustness and system suitability criteria. The main advantages of applying the Quality by Design concept consisted of a great increase of knowledge of the analytical system, obtained throughout multivariate techniques, and of the achievement of analytical assurance of quality, derived by probability-based definition of DS. The developed method was finally validated and applied to the analysis of ZOL tablets. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Parallel mapping of optical near-field interactions by molecular motor-driven quantum dots.

PubMed

Groß, Heiko; Heil, Hannah S; Ehrig, Jens; Schwarz, Friedrich W; Hecht, Bert; Diez, Stefan

2018-04-30

In the vicinity of metallic nanostructures, absorption and emission rates of optical emitters can be modulated by several orders of magnitude 1,2 . Control of such near-field light-matter interaction is essential for applications in biosensing 3 , light harvesting 4 and quantum communication 5,6 and requires precise mapping of optical near-field interactions, for which single-emitter probes are promising candidates 7-11 . However, currently available techniques are limited in terms of throughput, resolution and/or non-invasiveness. Here, we present an approach for the parallel mapping of optical near-field interactions with a resolution of <5 nm using surface-bound motor proteins to transport microtubules carrying single emitters (quantum dots). The deterministic motion of the quantum dots allows for the interpolation of their tracked positions, resulting in an increased spatial resolution and a suppression of localization artefacts. We apply this method to map the near-field distribution of nanoslits engraved into gold layers and find an excellent agreement with finite-difference time-domain simulations. Our technique can be readily applied to a variety of surfaces for scalable, nanometre-resolved and artefact-free near-field mapping using conventional wide-field microscopes.
Recent Developments and Applications of the MMPBSA Method

PubMed Central

Wang, Changhao; Greene, D'Artagnan; Xiao, Li; Qi, Ruxi; Luo, Ray

2018-01-01

The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach has been widely applied as an efficient and reliable free energy simulation method to model molecular recognition, such as for protein-ligand binding interactions. In this review, we focus on recent developments and applications of the MMPBSA method. The methodology review covers solvation terms, the entropy term, extensions to membrane proteins and high-speed screening, and new automation toolkits. Recent applications in various important biomedical and chemical fields are also reviewed. We conclude with a few future directions aimed at making MMPBSA a more robust and efficient method. PMID:29367919
Estimation of effective brain connectivity with dual Kalman filter and EEG source localization methods.

PubMed

Rajabioun, Mehdi; Nasrabadi, Ali Motie; Shamsollahi, Mohammad Bagher

2017-09-01

Effective connectivity is one of the most important considerations in brain functional mapping via EEG. It demonstrates the effects of a particular active brain region on others. In this paper, a new method is proposed which is based on dual Kalman filter. In this method, firstly by using a brain active localization method (standardized low resolution brain electromagnetic tomography) and applying it to EEG signal, active regions are extracted, and appropriate time model (multivariate autoregressive model) is fitted to extracted brain active sources for evaluating the activity and time dependence between sources. Then, dual Kalman filter is used to estimate model parameters or effective connectivity between active regions. The advantage of this method is the estimation of different brain parts activity simultaneously with the calculation of effective connectivity between active regions. By combining dual Kalman filter with brain source localization methods, in addition to the connectivity estimation between parts, source activity is updated during the time. The proposed method performance has been evaluated firstly by applying it to simulated EEG signals with interacting connectivity simulation between active parts. Noisy simulated signals with different signal to noise ratios are used for evaluating method sensitivity to noise and comparing proposed method performance with other methods. Then the method is applied to real signals and the estimation error during a sweeping window is calculated. By comparing proposed method results in different simulation (simulated and real signals), proposed method gives acceptable results with least mean square error in noisy or real conditions.
Analysis of Synchronization Phenomena in Broadband Signals with Nonlinear Excitable Media

NASA Astrophysics Data System (ADS)

Chernihovskyi, Anton; Elger, Christian E.; Lehnertz, Klaus

2009-12-01

We apply the method of frequency-selective excitation waves in excitable media to characterize synchronization phenomena in interacting complex dynamical systems by measuring coincidence rates of induced excitations. We relax the frequency-selectivity of excitable media and demonstrate two applications of the method to signals with broadband spectra. Findings obtained from analyzing time series of coupled chaotic oscillators as well as electroencephalographic (EEG) recordings from an epilepsy patient indicate that this method can provide an alternative and complementary way to estimate the degree of phase synchronization in noisy signals.
Identification of stochastic interactions in nonlinear models of structural mechanics

NASA Astrophysics Data System (ADS)

Kala, Zdeněk

2017-07-01

In the paper, the polynomial approximation is presented by which the Sobol sensitivity analysis can be evaluated with all sensitivity indices. The nonlinear FEM model is approximated. The input area is mapped using simulations runs of Latin Hypercube Sampling method. The domain of the approximation polynomial is chosen so that it were possible to apply large number of simulation runs of Latin Hypercube Sampling method. The method presented also makes possible to evaluate higher-order sensitivity indices, which could not be identified in case of nonlinear FEM.
Ramsey's method of separated oscillating fields and its application to gravitationally induced quantum phase shifts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abele, H.; Jenke, T.; Leeb, H.

2010-03-15

We propose to apply Ramsey's method of separated oscillating fields to the spectroscopy of the quantum states in the gravity potential above a horizontal mirror. This method allows a precise measurement of quantum mechanical phaseshifts of a Schroedinger wave packet bouncing off a hard surface in the gravitational field of the Earth. Measurements with ultracold neutrons will offer a sensitivity to Newton's law or hypothetical short-ranged interactions, which is about 21 orders of magnitude below the energy scale of electromagnetism.
A Simple and Computationally Efficient Sampling Approach to Covariate Adjustment for Multifactor Dimensionality Reduction Analysis of Epistasis

PubMed Central

Gui, Jiang; Andrew, Angeline S.; Andrews, Peter; Nelson, Heather M.; Kelsey, Karl T.; Karagas, Margaret R.; Moore, Jason H.

2010-01-01

Epistasis or gene-gene interaction is a fundamental component of the genetic architecture of complex traits such as disease susceptibility. Multifactor dimensionality reduction (MDR) was developed as a nonparametric and model-free method to detect epistasis when there are no significant marginal genetic effects. However, in many studies of complex disease, other covariates like age of onset and smoking status could have a strong main effect and may potentially interfere with MDR's ability to achieve its goal. In this paper, we present a simple and computationally efficient sampling method to adjust for covariate effects in MDR. We use simulation to show that after adjustment, MDR has sufficient power to detect true gene-gene interactions. We also compare our method with the state-of-art technique in covariate adjustment. The results suggest that our proposed method performs similarly, but is more computationally efficient. We then apply this new method to an analysis of a population-based bladder cancer study in New Hampshire. PMID:20924193
Laser Spot Tracking Based on Modified Circular Hough Transform and Motion Pattern Analysis

PubMed Central

Krstinić, Damir; Skelin, Ana Kuzmanić; Milatić, Ivan

2014-01-01

Laser pointers are one of the most widely used interactive and pointing devices in different human-computer interaction systems. Existing approaches to vision-based laser spot tracking are designed for controlled indoor environments with the main assumption that the laser spot is very bright, if not the brightest, spot in images. In this work, we are interested in developing a method for an outdoor, open-space environment, which could be implemented on embedded devices with limited computational resources. Under these circumstances, none of the assumptions of existing methods for laser spot tracking can be applied, yet a novel and fast method with robust performance is required. Throughout the paper, we will propose and evaluate an efficient method based on modified circular Hough transform and Lucas–Kanade motion analysis. Encouraging results on a representative dataset demonstrate the potential of our method in an uncontrolled outdoor environment, while achieving maximal accuracy indoors. Our dataset and ground truth data are made publicly available for further development. PMID:25350502
A semi-implicit augmented IIM for Navier–Stokes equations with open, traction, or free boundary conditions

PubMed Central

Li, Zhilin; Xiao, Li; Cai, Qin; Zhao, Hongkai; Luo, Ray

2016-01-01

In this paper, a new Navier–Stokes solver based on a finite difference approximation is proposed to solve incompressible flows on irregular domains with open, traction, and free boundary conditions, which can be applied to simulations of fluid structure interaction, implicit solvent model for biomolecular applications and other free boundary or interface problems. For some problems of this type, the projection method and the augmented immersed interface method (IIM) do not work well or does not work at all. The proposed new Navier–Stokes solver is based on the local pressure boundary method, and a semi-implicit augmented IIM. A fast Poisson solver can be used in our algorithm which gives us the potential for developing fast overall solvers in the future. The time discretization is based on a second order multi-step method. Numerical tests with exact solutions are presented to validate the accuracy of the method. Application to fluid structure interaction between an incompressible fluid and a compressible gas bubble is also presented. PMID:27087702
A semi-implicit augmented IIM for Navier-Stokes equations with open, traction, or free boundary conditions.

PubMed

Li, Zhilin; Xiao, Li; Cai, Qin; Zhao, Hongkai; Luo, Ray

2015-08-15

In this paper, a new Navier-Stokes solver based on a finite difference approximation is proposed to solve incompressible flows on irregular domains with open, traction, and free boundary conditions, which can be applied to simulations of fluid structure interaction, implicit solvent model for biomolecular applications and other free boundary or interface problems. For some problems of this type, the projection method and the augmented immersed interface method (IIM) do not work well or does not work at all. The proposed new Navier-Stokes solver is based on the local pressure boundary method, and a semi-implicit augmented IIM. A fast Poisson solver can be used in our algorithm which gives us the potential for developing fast overall solvers in the future. The time discretization is based on a second order multi-step method. Numerical tests with exact solutions are presented to validate the accuracy of the method. Application to fluid structure interaction between an incompressible fluid and a compressible gas bubble is also presented.
PlenoPatch: Patch-Based Plenoptic Image Manipulation.

PubMed

Zhang, Fang-Lue; Wang, Jue; Shechtman, Eli; Zhou, Zi-Ye; Shi, Jia-Xin; Hu, Shi-Min

2017-05-01

Patch-based image synthesis methods have been successfully applied for various editing tasks on still images, videos and stereo pairs. In this work we extend patch-based synthesis to plenoptic images captured by consumer-level lenselet-based devices for interactive, efficient light field editing. In our method the light field is represented as a set of images captured from different viewpoints. We decompose the central view into different depth layers, and present it to the user for specifying the editing goals. Given an editing task, our method performs patch-based image synthesis on all affected layers of the central view, and then propagates the edits to all other views. Interaction is done through a conventional 2D image editing user interface that is familiar to novice users. Our method correctly handles object boundary occlusion with semi-transparency, thus can generate more realistic results than previous methods. We demonstrate compelling results on a wide range of applications such as hole-filling, object reshuffling and resizing, changing object depth, light field upscaling and parallax magnification.
Laser spot tracking based on modified circular Hough transform and motion pattern analysis.

PubMed

Krstinić, Damir; Skelin, Ana Kuzmanić; Milatić, Ivan

2014-10-27

Laser pointers are one of the most widely used interactive and pointing devices in different human-computer interaction systems. Existing approaches to vision-based laser spot tracking are designed for controlled indoor environments with the main assumption that the laser spot is very bright, if not the brightest, spot in images. In this work, we are interested in developing a method for an outdoor, open-space environment, which could be implemented on embedded devices with limited computational resources. Under these circumstances, none of the assumptions of existing methods for laser spot tracking can be applied, yet a novel and fast method with robust performance is required. Throughout the paper, we will propose and evaluate an efficient method based on modified circular Hough transform and Lucas-Kanade motion analysis. Encouraging results on a representative dataset demonstrate the potential of our method in an uncontrolled outdoor environment, while achieving maximal accuracy indoors. Our dataset and ground truth data are made publicly available for further development.
A stochastic vortex structure method for interacting particles in turbulent shear flows

NASA Astrophysics Data System (ADS)

Dizaji, Farzad F.; Marshall, Jeffrey S.; Grant, John R.

2018-01-01

In a recent study, we have proposed a new synthetic turbulence method based on stochastic vortex structures (SVSs), and we have demonstrated that this method can accurately predict particle transport, collision, and agglomeration in homogeneous, isotropic turbulence in comparison to direct numerical simulation results. The current paper extends the SVS method to non-homogeneous, anisotropic turbulence. The key element of this extension is a new inversion procedure, by which the vortex initial orientation can be set so as to generate a prescribed Reynolds stress field. After validating this inversion procedure for simple problems, we apply the SVS method to the problem of interacting particle transport by a turbulent planar jet. Measures of the turbulent flow and of particle dispersion, clustering, and collision obtained by the new SVS simulations are shown to compare well with direct numerical simulation results. The influence of different numerical parameters, such as number of vortices and vortex lifetime, on the accuracy of the SVS predictions is also examined.
Neural network regulation driven by autonomous neural firings

NASA Astrophysics Data System (ADS)

Cho, Myoung Won

2016-07-01

Biological neurons naturally fire spontaneously due to the existence of a noisy current. Such autonomous firings may provide a driving force for network formation because synaptic connections can be modified due to neural firings. Here, we study the effect of autonomous firings on network formation. For the temporally asymmetric Hebbian learning, bidirectional connections lose their balance easily and become unidirectional ones. Defining the difference between reciprocal connections as new variables, we could express the learning dynamics as if Ising model spins interact with each other in magnetism. We present a theoretical method to estimate the interaction between the new variables in a neural system. We apply the method to some network systems and find some tendencies of autonomous neural network regulation.
Statistical mechanics of competitive resource allocation using agent-based models

NASA Astrophysics Data System (ADS)

Chakraborti, Anirban; Challet, Damien; Chatterjee, Arnab; Marsili, Matteo; Zhang, Yi-Cheng; Chakrabarti, Bikas K.

2015-01-01

Demand outstrips available resources in most situations, which gives rise to competition, interaction and learning. In this article, we review a broad spectrum of multi-agent models of competition (El Farol Bar problem, Minority Game, Kolkata Paise Restaurant problem, Stable marriage problem, Parking space problem and others) and the methods used to understand them analytically. We emphasize the power of concepts and tools from statistical mechanics to understand and explain fully collective phenomena such as phase transitions and long memory, and the mapping between agent heterogeneity and physical disorder. As these methods can be applied to any large-scale model of competitive resource allocation made up of heterogeneous adaptive agent with non-linear interaction, they provide a prospective unifying paradigm for many scientific disciplines.
Double-quantum homonuclear rotary resonance: Efficient dipolar recovery in magic-angle spinning nuclear magnetic resonance

NASA Astrophysics Data System (ADS)

Nielsen, N. C.; Bildsøe, H.; Jakobsen, H. J.; Levitt, M. H.

1994-08-01

We describe an efficient method for the recovery of homonuclear dipole-dipole interactions in magic-angle spinning NMR. Double-quantum homonuclear rotary resonance (2Q-HORROR) is established by fulfilling the condition ωr=2ω1, where ωr is the sample rotation frequency and ω1 is the nutation frequency around an applied resonant radio frequency (rf) field. This resonance can be used for double-quantum filtering and measurement of homonuclear dipolar interactions in the presence of magic-angle spinning. The spin dynamics depend only weakly on crystallite orientation allowing good performance for powder samples. Chemical shift effects are suppressed to zeroth order. The method is demonstrated for singly and doubly 13C labeled L-alanine.

Dynamical mechanism in aero-engine gas path system using minimum spanning tree and detrended cross-correlation analysis

NASA Astrophysics Data System (ADS)

Dong, Keqiang; Zhang, Hong; Gao, You

2017-01-01

Identifying the mutual interaction in aero-engine gas path system is a crucial problem that facilitates the understanding of emerging structures in complex system. By employing the multiscale multifractal detrended cross-correlation analysis method to aero-engine gas path system, the cross-correlation characteristics between gas path system parameters are established. Further, we apply multiscale multifractal detrended cross-correlation distance matrix and minimum spanning tree to investigate the mutual interactions of gas path variables. The results can infer that the low-spool rotor speed (N1) and engine pressure ratio (EPR) are main gas path parameters. The application of proposed method contributes to promote our understanding of the internal mechanisms and structures of aero-engine dynamics.
Tunable Coarse Graining for Monte Carlo Simulations of Proteins via Smoothed Energy Tables: Direct and Exchange Simulations

PubMed Central

2015-01-01

Many commonly used coarse-grained models for proteins are based on simplified interaction sites and consequently may suffer from significant limitations, such as the inability to properly model protein secondary structure without the addition of restraints. Recent work on a benzene fluid (LettieriS.; ZuckermanD. M.J. Comput. Chem.2012, 33, 268−27522120971) suggested an alternative strategy of tabulating and smoothing fully atomistic orientation-dependent interactions among rigid molecules or fragments. Here we report our initial efforts to apply this approach to the polar and covalent interactions intrinsic to polypeptides. We divide proteins into nearly rigid fragments, construct distance and orientation-dependent tables of the atomistic interaction energies between those fragments, and apply potential energy smoothing techniques to those tables. The amount of smoothing can be adjusted to give coarse-grained models that range from the underlying atomistic force field all the way to a bead-like coarse-grained model. For a moderate amount of smoothing, the method is able to preserve about 70–90% of the α-helical structure while providing a factor of 3–10 improvement in sampling per unit computation time (depending on how sampling is measured). For a greater amount of smoothing, multiple folding–unfolding transitions of the peptide were observed, along with a factor of 10–100 improvement in sampling per unit computation time, although the time spent in the unfolded state was increased compared with less smoothed simulations. For a β hairpin, secondary structure is also preserved, albeit for a narrower range of the smoothing parameter and, consequently, for a more modest improvement in sampling. We have also applied the new method in a “resolution exchange” setting, in which each replica runs a Monte Carlo simulation with a different degree of smoothing. We obtain exchange rates that compare favorably to our previous efforts at resolution exchange (LymanE.; ZuckermanD. M.J. Chem. Theory Comput.2006, 2, 656−666). PMID:25400525
Rapid Microfluidic Mixers Utilizing Dispersion Effect and Interactively Time-Pulsed Injection

NASA Astrophysics Data System (ADS)

Leong, Jik-Chang; Tsai, Chien-Hsiung; Chang, Chin-Lung; Lin, Chiu-Feng; Fu, Lung-Ming

2007-08-01

In this paper, we present a novel active microfluidic mixer utilizing a dispersion effect in an expansion chamber and applying interactively time-pulsed driving voltages to the respective inlet fluid flows to induce electroosmotic flow velocity variations for developing a rapid mixing effect in a microchannel. Without using any additional equipment to induce flow perturbations, only a single high-voltage power source is required for simultaneously driving and mixing sample fluids, which results in a simple and low-cost system for mixing. The effects of the applied main electrical field, interactive frequency, and expansion ratio on the mixing performance are thoroughly examined experimentally and numerically. The mixing ratio can be as high as 95% within a mixing length of 3000 μm downstream from the secondary T-form when a driving electric field strength of 250 V/cm, a periodic switching frequency of 5 Hz, and the expansion ratio M=1:10 are applied. In addition, the optimization of the driving electric field, switching frequency, expansion ratio, expansion entry length, and expansion chamber length for achieving a maximum mixing ratio is also discussed in this study. The novel method proposed in this study can be used for solving the mixing problem in the field of micro-total-analysis systems in a simple manner.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Cirac, J. Ignacio; Sierra, German; Instituto de Fisica Teorica, UAM-CSIC, Madrid

We generalize the matrix product states method using the chiral vertex operators of conformal field theory and apply it to study the ground states of the XXZ spin chain, the J{sub 1}-J{sub 2} model and random Heisenberg models. We compute the overlap with the exact wave functions, spin-spin correlators, and the Renyi entropy, showing that critical systems can be described by this method. For rotational invariant ansatzs we construct an inhomogenous extension of the Haldane-Shastry model with long-range exchange interactions.
Prediction of TF target sites based on atomistic models of protein-DNA complexes

PubMed Central

Angarica, Vladimir Espinosa; Pérez, Abel González; Vasconcelos, Ana T; Collado-Vides, Julio; Contreras-Moreira, Bruno

2008-01-01

Background The specific recognition of genomic cis-regulatory elements by transcription factors (TFs) plays an essential role in the regulation of coordinated gene expression. Studying the mechanisms determining binding specificity in protein-DNA interactions is thus an important goal. Most current approaches for modeling TF specific recognition rely on the knowledge of large sets of cognate target sites and consider only the information contained in their primary sequence. Results Here we describe a structure-based methodology for predicting sequence motifs starting from the coordinates of a TF-DNA complex. Our algorithm combines information regarding the direct and indirect readout of DNA into an atomistic statistical model, which is used to estimate the interaction potential. We first measure the ability of our method to correctly estimate the binding specificities of eight prokaryotic and eukaryotic TFs that belong to different structural superfamilies. Secondly, the method is applied to two homology models, finding that sampling of interface side-chain rotamers remarkably improves the results. Thirdly, the algorithm is compared with a reference structural method based on contact counts, obtaining comparable predictions for the experimental complexes and more accurate sequence motifs for the homology models. Conclusion Our results demonstrate that atomic-detail structural information can be feasibly used to predict TF binding sites. The computational method presented here is universal and might be applied to other systems involving protein-DNA recognition. PMID:18922190
An evolution in listening: An analytical and critical study of structural, acoustic, and phenomenal aspects of selected works by Pauline Oliveros

NASA Astrophysics Data System (ADS)

Setar, Katherine Marie

1997-08-01

This dissertation analytically and critically examines composer Pauline Oliveros's philosophy of 'listening' as it applies to selected works created between 1961 and 1984. The dissertation is organized through the application of two criteria: three perspectives of listening (empirical, phenomenal, and, to a lesser extent, personal), and categories derived, in part, from her writings and interviews (improvisational, traditional, theatrical, electronic, meditational, and interactive). In general, Oliveros's works may be categorized by one of two listening perspectives. The 'empirical' listening perspective, which generally includes pure acoustic phenomenon, independent from human interpretation, is exemplified in the analyses of Sound Patterns (1961), OH HA AH (1968), and, to a lesser extent, I of IV (1966). The 'phenomenal' listening perspective, which involves the human interaction with the pure acoustic phenomenon, includes a critical examination of her post-1971 'meditation' pieces and an analytical and critical examination of her tonal 'interactive' improvisations in highly resonant space, such as Watertank Software (1984). The most pervasive element of Oliveros's stylistic evolution is her gradual change from the hierarchical aesthetic of the traditional composer, to one in which creative control is more equally shared by all participants. Other significant contributions by Oliveros include the probable invention of the 'meditation' genre, an emphasis on the subjective perceptions of musical participants as a means to greater musical awareness, her musical exploration of highly resonant space, and her pioneering work in American electronic music. Both analytical and critical commentary were applied to selective representative works from Oliveros's six compositional categories. The analytical methods applied to the Oliveros's works include Wayne Slawson's vowel/formant theory as described in his book, Sound Color, an original method of categorizing consonants as noise sources based upon the principles of the International Phonetic Association, traditional morphological analyses, linear-extrapolation analyses which are derived from Schenker's theory, and discussions of acoustic phenomena as they apply to such practices as 1960s electronic studio techniques and the dynamics of room acoustics.
Nonparametric Determination of Redshift Evolution Index of Dark Energy

NASA Astrophysics Data System (ADS)

Ziaeepour, Houri

We propose a nonparametric method to determine the sign of γ — the redshift evolution index of dark energy. This is important for distinguishing between positive energy models, a cosmological constant, and what is generally called ghost models. Our method is based on geometrical properties and is more tolerant to uncertainties of other cosmological parameters than fitting methods in what concerns the sign of γ. The same parametrization can also be used for determining γ and its redshift dependence by fitting. We apply this method to SNLS supernovae and to gold sample of re-analyzed supernovae data from Riess et al. Both datasets show strong indication of a negative γ. If this result is confirmed by more extended and precise data, many of the dark energy models, including simple cosmological constant, standard quintessence models without interaction between quintessence scalar field(s) and matter, and scaling models are ruled out. We have also applied this method to Gurzadyan-Xue models with varying fundamental constants to demonstrate the possibility of using it to test other cosmologies.
Model parameter learning using Kullback-Leibler divergence

NASA Astrophysics Data System (ADS)

Lin, Chungwei; Marks, Tim K.; Pajovic, Milutin; Watanabe, Shinji; Tung, Chih-kuan

2018-02-01

In this paper, we address the following problem: For a given set of spin configurations whose probability distribution is of the Boltzmann type, how do we determine the model coupling parameters? We demonstrate that directly minimizing the Kullback-Leibler divergence is an efficient method. We test this method against the Ising and XY models on the one-dimensional (1D) and two-dimensional (2D) lattices, and provide two estimators to quantify the model quality. We apply this method to two types of problems. First, we apply it to the real-space renormalization group (RG). We find that the obtained RG flow is sufficiently good for determining the phase boundary (within 1% of the exact result) and the critical point, but not accurate enough for critical exponents. The proposed method provides a simple way to numerically estimate amplitudes of the interactions typically truncated in the real-space RG procedure. Second, we apply this method to the dynamical system composed of self-propelled particles, where we extract the parameter of a statistical model (a generalized XY model) from a dynamical system described by the Viscek model. We are able to obtain reasonable coupling values corresponding to different noise strengths of the Viscek model. Our method is thus able to provide quantitative analysis of dynamical systems composed of self-propelled particles.
Modeling the virus-immune system interactions in the peripheral bloodstream of HIV infected individuals using a cellular automata model with considering the effects of antiretroviral therapy.

PubMed

Golpayegani, Gelayol Nazari; Jafari, Amir Homayoun; Dabanloo, Nader Jafarnia

2017-01-01

According to the World Health Organization, by the end of last year, about 37 million people throughout the world were diagnosed with AIDS and millions of people die each year from this disease. To develop an appropriate model which depicts the mechanism of the dynamics involved in the interactions between HIV and immune system in peripheral bloodstream of HIV infected individuals by considering the phenomena of virus mutation and taking into account the role of latently infected cells in speared of infection and considering the effects of antiretroviral drugs and occurrence of drug resistance in our model in order to assess the results obtained from applying different therapeutic methods. Two-dimensional CA model with Moor neighboring was developed. Various agents which they were referring to peripheral bloodstream particles of HIV infected individuals were defined. Then the biological rules were extracted from both expert knowledge and the authoritative articles. The extracted rules were applied for updating the states of these agents. The effects of using antiretroviral drug treatment were considered by applying drug's effectiveness of both of protease and reverse transcriptase inhibitors as two separate inputs of model. Time evolution curves of concentrations of defined agents were shown as our results. In case of considering no treatment, our results showed that concentrations of healthy CD4+T cells reached the threshold of AIDS after a bout 250 weeks. By applying monotherapy method, the concentrations of these cells remained on the threshold of AIDS for a long time and applying combined antiretroviral therapy (cART) method leaded to increase the concentration of these cells 20% upper than threshold of AIDS. Also, by applying monotherapy and cART compared with no treatment, the concentrations of infected CD4+T cells 10% and 40% decreased further, respectively and for the level of viral load, leads to a reduction of almost 55% and 90%, respectively. Belated treatment, comparison with early treatment, caused almost 10% reduce (increase) in steady state concentrations of healthy (infected) cells.
Spectral study of interaction between chondroitin sulfate and nanoparticles and its application in quantitative analysis

NASA Astrophysics Data System (ADS)

Ma, Yi; Wei, Maojie; Zhang, Xiao; Zhao, Ting; Liu, Xiumei; Zhou, Guanglian

2016-01-01

In this work, the interaction between chondroitin sulfate (CS) and gold nanoparticles (GNPs) and silver nanoparticles (SNPs) was characterized for the first time. Plasma resonance scattering (PRS) and plasma resonance absorption (PRA) were used to investigate the characteristics of their spectrum. The results suggested that the CS with negative charge could interact with metal nanoparticles with negative charge and the adsorption of CS on the surface of SNPs was more regular than that of GNPs. The resonance scattering spectra also further confirmed the interaction between CS and SNPs. A new method for detection of CS based on the interaction was developed. CS concentrations in the range of 0.02-3.5 μg/mL were proportional to the decreases of absorbance of SNPs. Compared with other reported methods, the proposed method is simple and workable without complex process, high consumption and expensive equipments. The developed method was applied to the determination of the CS contents from different biological origins and the results were compared with those obtained by the method of Chinese Pharmacopeia. The effects of matrix in plasma and other glycosaminoglycans on the determination of CS were also investigated. The results showed that a small quantity of blood plasma had no effect on the determination of CS and when the concentration ratio of CS to heparin was more than 10:1, the influence of heparin on the detection of CS could be ignored. This work gave a specific research direction for the detection of CS in the presence of metal nanoparticles.
Systems thinking perspectives applied to healthcare transition for youth with disabilities: a paradigm shift for practice, policy and research.

PubMed

Hamdani, Y; Jetha, A; Norman, C

2011-11-01

Healthcare transition (HCT) for youth with disabilities is a complex phenomenon influenced by multiple interacting factors, including health, personal and environmental factors. Current research on the transition to adulthood for disabled youth has primarily focused on identifying these multilevel factors to guide the development of interventions to improve the HCT process. However, little is known about how this complex array of factors interacts and contributes to successful HCT. Systems thinking provides a theoretically informed perspective that accounts for complexity and can contribute to enhanced understanding of the interactions among HCT factors. The objective of this paper is to introduce general concepts of systems thinking as applied to HCT practice and research. Several systems thinking concepts and principles are introduced and a discussion of HCT as a complex system is provided. Systems dynamics methodology is described as one systems method for conceptualizing HCT. A preliminary systems dynamics model is presented to facilitate discourse on the application of systems thinking principles to HCT practice, policy and research. An understanding of the complex interactions and patterns of relationships in HCT can assist health policy makers and practitioners in determining key areas of intervention, the impact of these interventions on the system and the potential intended and unintended consequences of change. This paper provides initial examination of applying systems thinking to inform future research and practice on HCT. © 2011 Blackwell Publishing Ltd.
A Simple and Computationally Efficient Approach to Multifactor Dimensionality Reduction Analysis of Gene-Gene Interactions for Quantitative Traits

PubMed Central

Gui, Jiang; Moore, Jason H.; Williams, Scott M.; Andrews, Peter; Hillege, Hans L.; van der Harst, Pim; Navis, Gerjan; Van Gilst, Wiek H.; Asselbergs, Folkert W.; Gilbert-Diamond, Diane

2013-01-01

We present an extension of the two-class multifactor dimensionality reduction (MDR) algorithm that enables detection and characterization of epistatic SNP-SNP interactions in the context of a quantitative trait. The proposed Quantitative MDR (QMDR) method handles continuous data by modifying MDR’s constructive induction algorithm to use a T-test. QMDR replaces the balanced accuracy metric with a T-test statistic as the score to determine the best interaction model. We used a simulation to identify the empirical distribution of QMDR’s testing score. We then applied QMDR to genetic data from the ongoing prospective Prevention of Renal and Vascular End-Stage Disease (PREVEND) study. PMID:23805232
A viscous-inviscid interactive compressor calculations

NASA Technical Reports Server (NTRS)

Johnston, W.; Sockol, P. M.

1978-01-01

A viscous-inviscid interactive procedure for subsonic flow is developed and applied to an axial compressor stage. Calculations are carried out on a two-dimensional blade-to-blade region of constant radius assumed to occupy a mid-span location. Hub and tip effects are neglected. The Euler equations are solved by MacCormack's method, a viscous marching procedure is used in the boundary layers and wake, and an iterative interaction scheme is constructed that matches them in a way that incorporates information related to momentum and enthalpy thicknesses as well as the displacement thickness. The calculations are quasi-three-dimensional in the sense that the boundary layer and wake solutions allow for the presence of spanwise (radial) velocities.
Dipolar and spinor bosonic systems

NASA Astrophysics Data System (ADS)

Yukalov, V. I.

2018-05-01

The main properties and methods of describing dipolar and spinor atomic systems, composed of bosonic atoms or molecules, are reviewed. The general approach for the correct treatment of Bose-condensed atomic systems with nonlocal interaction potentials is explained. The approach is applied to Bose-condensed systems with dipolar interaction potentials. The properties of systems with spinor interaction potentials are described. Trapped atoms and atoms in optical lattices are considered. Effective spin Hamiltonians for atoms in optical lattices are derived. The possibility of spintronics with cold atom is emphasized. The present review differs from the previous review articles by concentrating on a thorough presentation of basic theoretical points, helping the reader to better follow mathematical details and to make clearer physical conclusions.
A systematic molecular dynamics approach to the study of peptide Keap1-Nrf2 protein-protein interaction inhibitors and its application to p62 peptides.

PubMed

Lu, Meng-Chen; Yuan, Zhen-Wei; Jiang, Yong-Lin; Chen, Zhi-Yun; You, Qi-Dong; Jiang, Zheng-Yu

2016-04-01

Protein-protein interactions (PPIs) as drug targets have been gaining growing interest, though developing drug-like small molecule PPI inhibitors remains challenging. Peptide PPI inhibitors, which can provide informative data on the PPI interface, are good starting points to develop small molecule modulators. Computational methods combining molecular dynamics simulations and binding energy calculations could give both the structural and the energetic perspective of peptide PPI inhibitors. Herein, we set up a computational workflow to investigate Keap1-Nrf2 peptide PPI inhibitors and predict the activity of novel sequences. Furthermore, we applied this method to investigate p62 peptides as PPI inhibitors of Keap1-Nrf2 and explored the activity change induced by the phosphorylation of serine. Our results showed that because of the unfavorable solvation effects, the binding affinity of the phosphorylated p62 peptide is lower than the Nrf2 ETGE peptide. Our research results not only provide a useful method to investigate the Keap1-Nrf2 peptide inhibitors, but also give a good example to show how to incorporate computational methods into the study of peptide PPI inhibitors. Besides, applying this method to p62 peptides provides a detailed explanation for the expression of cytoprotective Nrf2 targets induced by p62 phosphorylation, which may benefit the further study of the crosstalk between the Keap1-Nrf2 pathway and p62-mediated selective autophagy.
Improving the iterative Linear Interaction Energy approach using automated recognition of configurational transitions.

PubMed

Vosmeer, C Ruben; Kooi, Derk P; Capoferri, Luigi; Terpstra, Margreet M; Vermeulen, Nico P E; Geerke, Daan P

2016-01-01

Recently an iterative method was proposed to enhance the accuracy and efficiency of ligand-protein binding affinity prediction through linear interaction energy (LIE) theory. For ligand binding to flexible Cytochrome P450s (CYPs), this method was shown to decrease the root-mean-square error and standard deviation of error prediction by combining interaction energies of simulations starting from different conformations. Thereby, different parts of protein-ligand conformational space are sampled in parallel simulations. The iterative LIE framework relies on the assumption that separate simulations explore different local parts of phase space, and do not show transitions to other parts of configurational space that are already covered in parallel simulations. In this work, a method is proposed to (automatically) detect such transitions during the simulations that are performed to construct LIE models and to predict binding affinities. Using noise-canceling techniques and splines to fit time series of the raw data for the interaction energies, transitions during simulation between different parts of phase space are identified. Boolean selection criteria are then applied to determine which parts of the interaction energy trajectories are to be used as input for the LIE calculations. Here we show that this filtering approach benefits the predictive quality of our previous CYP 2D6-aryloxypropanolamine LIE model. In addition, an analysis is performed of the gain in computational efficiency that can be obtained from monitoring simulations using the proposed filtering method and by prematurely terminating simulations accordingly.
Analysis of plant nucleotide sugars by hydrophilic interaction liquid chromatography and tandem mass spectrometry.

PubMed

Ito, Jun; Herter, Thomas; Baidoo, Edward E K; Lao, Jeemeng; Vega-Sánchez, Miguel E; Michelle Smith-Moritz, A; Adams, Paul D; Keasling, Jay D; Usadel, Björn; Petzold, Christopher J; Heazlewood, Joshua L

2014-03-01

Understanding the intricate metabolic processes involved in plant cell wall biosynthesis is limited by difficulties in performing sensitive quantification of many involved compounds. Hydrophilic interaction liquid chromatography is a useful technique for the analysis of hydrophilic metabolites from complex biological extracts and forms the basis of this method to quantify plant cell wall precursors. A zwitterionic silica-based stationary phase has been used to separate hydrophilic nucleotide sugars involved in cell wall biosynthesis from milligram amounts of leaf tissue. A tandem mass spectrometry operating in selected reaction monitoring mode was used to quantify nucleotide sugars. This method was highly repeatable and quantified 12 nucleotide sugars at low femtomole quantities, with linear responses up to four orders of magnitude to several 100pmol. The method was also successfully applied to the analysis of purified leaf extracts from two model plant species with variations in their cell wall sugar compositions and indicated significant differences in the levels of 6 out of 12 nucleotide sugars. The plant nucleotide sugar extraction procedure was demonstrated to have good recovery rates with minimal matrix effects. The approach results in a significant improvement in sensitivity when applied to plant samples over currently employed techniques. Copyright © 2013 Elsevier Inc. All rights reserved.
3D-QSPR Method of Computational Technique Applied on Red Reactive Dyes by Using CoMFA Strategy

PubMed Central

Mahmood, Uzma; Rashid, Sitara; Ali, S. Ishrat; Parveen, Rasheeda; Zaheer-ul-Haq; Ambreen, Nida; Khan, Khalid Mohammed; Perveen, Shahnaz; Voelter, Wolfgang

2011-01-01

Cellulose fiber is a tremendous natural resource that has broad application in various productions including the textile industry. The dyes, which are commonly used for cellulose printing, are “reactive dyes” because of their high wet fastness and brilliant colors. The interaction of various dyes with the cellulose fiber depends upon the physiochemical properties that are governed by specific features of the dye molecule. The binding pattern of the reactive dye with cellulose fiber is called the ligand-receptor concept. In the current study, the three dimensional quantitative structure property relationship (3D-QSPR) technique was applied to understand the red reactive dyes interactions with the cellulose by the Comparative Molecular Field Analysis (CoMFA) method. This method was successfully utilized to predict a reliable model. The predicted model gives satisfactory statistical results and in the light of these, it was further analyzed. Additionally, the graphical outcomes (contour maps) help us to understand the modification pattern and to correlate the structural changes with respect to the absorptivity. Furthermore, the final selected model has potential to assist in understanding the charachteristics of the external test set. The study could be helpful to design new reactive dyes with better affinity and selectivity for the cellulose fiber. PMID:22272108
Flood analysis in mixed-urban areas reflecting interactions with the complete water cycle through coupled hydrologic-hydraulic modelling.

PubMed

Sto Domingo, N D; Refsgaard, A; Mark, O; Paludan, B

2010-01-01

The potential devastating effects of urban flooding have given high importance to thorough understanding and management of water movement within catchments, and computer modelling tools have found widespread use for this purpose. The state-of-the-art in urban flood modelling is the use of a coupled 1D pipe and 2D overland flow model to simultaneously represent pipe and surface flows. This method has been found to be accurate for highly paved areas, but inappropriate when land hydrology is important. The objectives of this study are to introduce a new urban flood modelling procedure that is able to reflect system interactions with hydrology, verify that the new procedure operates well, and underline the importance of considering the complete water cycle in urban flood analysis. A physically-based and distributed hydrological model was linked to a drainage network model for urban flood analysis, and the essential components and concepts used were described in this study. The procedure was then applied to a catchment previously modelled with the traditional 1D-2D procedure to determine if the new method performs similarly well. Then, results from applying the new method in a mixed-urban area were analyzed to determine how important hydrologic contributions are to flooding in the area.
Long Range Debye-Hückel Correction for Computation of Grid-based Electrostatic Forces Between Biomacromolecules

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mereghetti, Paolo; Martinez, M.; Wade, Rebecca C.

Brownian dynamics (BD) simulations can be used to study very large molecular systems, such as models of the intracellular environment, using atomic-detail structures. Such simulations require strategies to contain the computational costs, especially for the computation of interaction forces and energies. A common approach is to compute interaction forces between macromolecules by precomputing their interaction potentials on three-dimensional discretized grids. For long-range interactions, such as electrostatics, grid-based methods are subject to finite size errors. We describe here the implementation of a Debye-Hückel correction to the grid-based electrostatic potential used in the SDA BD simulation software that was applied to simulatemore » solutions of bovine serum albumin and of hen egg white lysozyme.« less

ROCS: a Reproducibility Index and Confidence Score for Interaction Proteomics Studies

PubMed Central

2012-01-01

Background Affinity-Purification Mass-Spectrometry (AP-MS) provides a powerful means of identifying protein complexes and interactions. Several important challenges exist in interpreting the results of AP-MS experiments. First, the reproducibility of AP-MS experimental replicates can be low, due both to technical variability and the dynamic nature of protein interactions in the cell. Second, the identification of true protein-protein interactions in AP-MS experiments is subject to inaccuracy due to high false negative and false positive rates. Several experimental approaches can be used to mitigate these drawbacks, including the use of replicated and control experiments and relative quantification to sensitively distinguish true interacting proteins from false ones. Methods To address the issues of reproducibility and accuracy of protein-protein interactions, we introduce a two-step method, called ROCS, which makes use of Indicator Prey Proteins to select reproducible AP-MS experiments, and of Confidence Scores to select specific protein-protein interactions. The Indicator Prey Proteins account for measures of protein identifiability as well as protein reproducibility, effectively allowing removal of outlier experiments that contribute noise and affect downstream inferences. The filtered set of experiments is then used in the Protein-Protein Interaction (PPI) scoring step. Prey protein scoring is done by computing a Confidence Score, which accounts for the probability of occurrence of prey proteins in the bait experiments relative to the control experiment, where the significance cutoff parameter is estimated by simultaneously controlling false positives and false negatives against metrics of false discovery rate and biological coherence respectively. In summary, the ROCS method relies on automatic objective criterions for parameter estimation and error-controlled procedures. Results We illustrate the performance of our method by applying it to five previously published AP-MS experiments, each containing well characterized protein interactions, allowing for systematic benchmarking of ROCS. We show that our method may be used on its own to make accurate identification of specific, biologically relevant protein-protein interactions, or in combination with other AP-MS scoring methods to significantly improve inferences. Conclusions Our method addresses important issues encountered in AP-MS datasets, making ROCS a very promising tool for this purpose, either on its own or in conjunction with other methods. We anticipate that our methodology may be used more generally in proteomics studies and databases, where experimental reproducibility issues arise. The method is implemented in the R language, and is available as an R package called “ROCS”, freely available from the CRAN repository http://cran.r-project.org/. PMID:22682516
NASA Formal Methods Workshop, 1990

NASA Technical Reports Server (NTRS)

Butler, Ricky W. (Compiler)

1990-01-01

The workshop brought together researchers involved in the NASA formal methods research effort for detailed technical interchange and provided a mechanism for interaction with representatives from the FAA and the aerospace industry. The workshop also included speakers from industry to debrief the formal methods researchers on the current state of practice in flight critical system design, verification, and certification. The goals were: define and characterize the verification problem for ultra-reliable life critical flight control systems and the current state of practice in industry today; determine the proper role of formal methods in addressing these problems, and assess the state of the art and recent progress toward applying formal methods to this area.
Incorporating time-delays in S-System model for reverse engineering genetic networks.

PubMed

Chowdhury, Ahsan Raja; Chetty, Madhu; Vinh, Nguyen Xuan

2013-06-18

In any gene regulatory network (GRN), the complex interactions occurring amongst transcription factors and target genes can be either instantaneous or time-delayed. However, many existing modeling approaches currently applied for inferring GRNs are unable to represent both these interactions simultaneously. As a result, all these approaches cannot detect important interactions of the other type. S-System model, a differential equation based approach which has been increasingly applied for modeling GRNs, also suffers from this limitation. In fact, all S-System based existing modeling approaches have been designed to capture only instantaneous interactions, and are unable to infer time-delayed interactions. In this paper, we propose a novel Time-Delayed S-System (TDSS) model which uses a set of delay differential equations to represent the system dynamics. The ability to incorporate time-delay parameters in the proposed S-System model enables simultaneous modeling of both instantaneous and time-delayed interactions. Furthermore, the delay parameters are not limited to just positive integer values (corresponding to time stamps in the data), but can also take fractional values. Moreover, we also propose a new criterion for model evaluation exploiting the sparse and scale-free nature of GRNs to effectively narrow down the search space, which not only reduces the computation time significantly but also improves model accuracy. The evaluation criterion systematically adapts the max-min in-degrees and also systematically balances the effect of network accuracy and complexity during optimization. The four well-known performance measures applied to the experimental studies on synthetic networks with various time-delayed regulations clearly demonstrate that the proposed method can capture both instantaneous and delayed interactions correctly with high precision. The experiments carried out on two well-known real-life networks, namely IRMA and SOS DNA repair network in Escherichia coli show a significant improvement compared with other state-of-the-art approaches for GRN modeling.
Timescale analysis of rule-based biochemical reaction networks

PubMed Central

Klinke, David J.; Finley, Stacey D.

2012-01-01

The flow of information within a cell is governed by a series of protein-protein interactions that can be described as a reaction network. Mathematical models of biochemical reaction networks can be constructed by repetitively applying specific rules that define how reactants interact and what new species are formed upon reaction. To aid in understanding the underlying biochemistry, timescale analysis is one method developed to prune the size of the reaction network. In this work, we extend the methods associated with timescale analysis to reaction rules instead of the species contained within the network. To illustrate this approach, we applied timescale analysis to a simple receptor-ligand binding model and a rule-based model of Interleukin-12 (IL-12) signaling in näive CD4+ T cells. The IL-12 signaling pathway includes multiple protein-protein interactions that collectively transmit information; however, the level of mechanistic detail sufficient to capture the observed dynamics has not been justified based upon the available data. The analysis correctly predicted that reactions associated with JAK2 and TYK2 binding to their corresponding receptor exist at a pseudo-equilibrium. In contrast, reactions associated with ligand binding and receptor turnover regulate cellular response to IL-12. An empirical Bayesian approach was used to estimate the uncertainty in the timescales. This approach complements existing rank- and flux-based methods that can be used to interrogate complex reaction networks. Ultimately, timescale analysis of rule-based models is a computational tool that can be used to reveal the biochemical steps that regulate signaling dynamics. PMID:21954150
Single column comprehensive analysis of pharmaceutical preparations using dual-injection mixed-mode (ion-exchange and reversed-phase) and hydrophilic interaction liquid chromatography.

PubMed

Kazarian, Artaches A; Taylor, Mark R; Haddad, Paul R; Nesterenko, Pavel N; Paull, Brett

2013-12-01

The comprehensive separation and detection of hydrophobic and hydrophilic active pharmaceutical ingredients (APIs), their counter-ions (organic, inorganic) and excipients, using a single mixed-mode chromatographic column, and a dual injection approach is presented. Using a mixed-mode Thermo Fisher Acclaim Trinity P1 column, APIs, their counter-ions and possible degradants were first separated using a combination of anion-exchange, cation-exchange and hydrophobic interactions, using a mobile phase consisting of a dual organic modifier/salt concentration gradient. A complementary method was also developed using the same column for the separation of hydrophilic bulk excipients, using hydrophilic interaction liquid chromatography (HILIC) under high organic solvent mobile phase conditions. These two methods were then combined within a single gradient run using dual sample injection, with the first injection at the start of the applied gradient (mixed-mode retention of solutes), followed by a second sample injection at the end of the gradient (HILIC retention of solutes). Detection using both ultraviolet absorbance and refractive index enabled the sensitive detection of APIs and UV-absorbing counter-ions, together with quantitative determination of bulk excipients. The developed approach was applied successfully to the analysis of a dry powder inhalers (Flixotide(®), Spiriva(®)), enabling comprehensive quantification of all APIs and excipients in the sample. Copyright © 2013 Elsevier B.V. All rights reserved.
Cultural and climatic changes shape the evolutionary history of the Uralic languages.

PubMed

Honkola, T; Vesakoski, O; Korhonen, K; Lehtinen, J; Syrjänen, K; Wahlberg, N

2013-06-01

Quantitative phylogenetic methods have been used to study the evolutionary relationships and divergence times of biological species, and recently, these have also been applied to linguistic data to elucidate the evolutionary history of language families. In biology, the factors driving macroevolutionary processes are assumed to be either mainly biotic (the Red Queen model) or mainly abiotic (the Court Jester model) or a combination of both. The applicability of these models is assumed to depend on the temporal and spatial scale observed as biotic factors act on species divergence faster and in smaller spatial scale than the abiotic factors. Here, we used the Uralic language family to investigate whether both 'biotic' interactions (i.e. cultural interactions) and abiotic changes (i.e. climatic fluctuations) are also connected to language diversification. We estimated the times of divergence using Bayesian phylogenetics with a relaxed-clock method and related our results to climatic, historical and archaeological information. Our timing results paralleled the previous linguistic studies but suggested a later divergence of Finno-Ugric, Finnic and Saami languages. Some of the divergences co-occurred with climatic fluctuation and some with cultural interaction and migrations of populations. Thus, we suggest that both 'biotic' and abiotic factors contribute either directly or indirectly to the diversification of languages and that both models can be applied when studying language evolution. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.
A study of polaritonic transparency in couplers made from excitonic materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Singh, Mahi R.; Racknor, Chris

2015-03-14

We have studied light matter interaction in quantum dot and exciton-polaritonic coupler hybrid systems. The coupler is made by embedding two slabs of an excitonic material (CdS) into a host excitonic material (ZnO). An ensemble of non-interacting quantum dots is doped in the coupler. The bound exciton polariton states are calculated in the coupler using the transfer matrix method in the presence of the coupling between the external light (photons) and excitons. These bound exciton-polaritons interact with the excitons present in the quantum dots and the coupler is acting as a reservoir. The Schrödinger equation method has been used tomore » calculate the absorption coefficient in quantum dots. It is found that when the distance between two slabs (CdS) is greater than decay length of evanescent waves the absorption spectrum has two peaks and one minimum. The minimum corresponds to a transparent state in the system. However, when the distance between the slabs is smaller than the decay length of evanescent waves, the absorption spectra has three peaks and two transparent states. In other words, one transparent state can be switched to two transparent states when the distance between the two layers is modified. This could be achieved by applying stress and strain fields. It is also found that transparent states can be switched on and off by applying an external control laser field.« less
Multi-Connection Pattern Analysis: Decoding the representational content of neural communication.

PubMed

Li, Yuanning; Richardson, Robert Mark; Ghuman, Avniel Singh

2017-11-15

The lack of multivariate methods for decoding the representational content of interregional neural communication has left it difficult to know what information is represented in distributed brain circuit interactions. Here we present Multi-Connection Pattern Analysis (MCPA), which works by learning mappings between the activity patterns of the populations as a factor of the information being processed. These maps are used to predict the activity from one neural population based on the activity from the other population. Successful MCPA-based decoding indicates the involvement of distributed computational processing and provides a framework for probing the representational structure of the interaction. Simulations demonstrate the efficacy of MCPA in realistic circumstances. In addition, we demonstrate that MCPA can be applied to different signal modalities to evaluate a variety of hypothesis associated with information coding in neural communications. We apply MCPA to fMRI and human intracranial electrophysiological data to provide a proof-of-concept of the utility of this method for decoding individual natural images and faces in functional connectivity data. We further use a MCPA-based representational similarity analysis to illustrate how MCPA may be used to test computational models of information transfer among regions of the visual processing stream. Thus, MCPA can be used to assess the information represented in the coupled activity of interacting neural circuits and probe the underlying principles of information transformation between regions. Copyright © 2017 Elsevier Inc. All rights reserved.
Learning to recognize rat social behavior: Novel dataset and cross-dataset application.

PubMed

Lorbach, Malte; Kyriakou, Elisavet I; Poppe, Ronald; van Dam, Elsbeth A; Noldus, Lucas P J J; Veltkamp, Remco C

2018-04-15

Social behavior is an important aspect of rodent models. Automated measuring tools that make use of video analysis and machine learning are an increasingly attractive alternative to manual annotation. Because machine learning-based methods need to be trained, it is important that they are validated using data from different experiment settings. To develop and validate automated measuring tools, there is a need for annotated rodent interaction datasets. Currently, the availability of such datasets is limited to two mouse datasets. We introduce the first, publicly available rat social interaction dataset, RatSI. We demonstrate the practical value of the novel dataset by using it as the training set for a rat interaction recognition method. We show that behavior variations induced by the experiment setting can lead to reduced performance, which illustrates the importance of cross-dataset validation. Consequently, we add a simple adaptation step to our method and improve the recognition performance. Most existing methods are trained and evaluated in one experimental setting, which limits the predictive power of the evaluation to that particular setting. We demonstrate that cross-dataset experiments provide more insight in the performance of classifiers. With our novel, public dataset we encourage the development and validation of automated recognition methods. We are convinced that cross-dataset validation enhances our understanding of rodent interactions and facilitates the development of more sophisticated recognition methods. Combining them with adaptation techniques may enable us to apply automated recognition methods to a variety of animals and experiment settings. Copyright © 2017 Elsevier B.V. All rights reserved.
Development, validation and application of a hydrophilic interaction liquid chromatography-evaporative light scattering detection based method for process control of hydrolysis of xylans obtained from different agricultural wastes.

PubMed

Li, Fangbing; Wang, Hui; Xin, Huaxia; Cai, Jianfeng; Fu, Qing; Jin, Yu

2016-12-01

Purified standards of xylooligosaccharides (XOSs) (DP2-6) were first prepared from a mixture of XOSs using solid phase extraction (SPE), followed by semi-preparative liquid chromatography both under hydrophilic interaction liquid chromatography (HILIC) modes. Then, an accurate quantitative analysis method based on hydrophilic interaction liquid chromatography-evaporative light scattering detection (HILIC-ELSD) was developed and validated for simultaneous determination of xylose (X1), xylobiose (X2), xylotriose (X3), xylotetraose (X4), xylopentaose (X5), and xylohexaose (X6). This developed HILIC-ELSD method was applied to the comparison of different hydrolysis methods for xylans and assessment of XOSs contents from different agricultural wastes. The result indicated that enzymatic hydrolysis was preferable with fewer by-products and high XOSs yield. The XOSs yield (48.40%) from sugarcane bagasse xylan was the highest, showing conversions of 11.21g X2, 12.75g X3, 4.54g X4, 13.31g X5, and 6.78g X6 from 100g xylan. Copyright © 2016 Elsevier Ltd. All rights reserved.
Prediction of protein orientation upon immobilization on biological and nonbiological surfaces

NASA Astrophysics Data System (ADS)

Talasaz, Amirali H.; Nemat-Gorgani, Mohsen; Liu, Yang; Ståhl, Patrik; Dutton, Robert W.; Ronaghi, Mostafa; Davis, Ronald W.

2006-10-01

We report on a rapid simulation method for predicting protein orientation on a surface based on electrostatic interactions. New methods for predicting protein immobilization are needed because of the increasing use of biosensors and protein microarrays, two technologies that use protein immobilization onto a solid support, and because the orientation of an immobilized protein is important for its function. The proposed simulation model is based on the premise that the protein interacts with the electric field generated by the surface, and this interaction defines the orientation of attachment. Results of this model are in agreement with experimental observations of immobilization of mitochondrial creatine kinase and type I hexokinase on biological membranes. The advantages of our method are that it can be applied to any protein with a known structure; it does not require modeling of the surface at atomic resolution and can be run relatively quickly on readily available computing resources. Finally, we also propose an orientation of membrane-bound cytochrome c, a protein for which the membrane orientation has not been unequivocally determined. electric double layer | electrostatic simulations | orientation flexibility
Reverse Nearest Neighbor Search on a Protein-Protein Interaction Network to Infer Protein-Disease Associations.

PubMed

Suratanee, Apichat; Plaimas, Kitiporn

2017-01-01

The associations between proteins and diseases are crucial information for investigating pathological mechanisms. However, the number of known and reliable protein-disease associations is quite small. In this study, an analysis framework to infer associations between proteins and diseases was developed based on a large data set of a human protein-protein interaction network integrating an effective network search, namely, the reverse k -nearest neighbor (R k NN) search. The R k NN search was used to identify an impact of a protein on other proteins. Then, associations between proteins and diseases were inferred statistically. The method using the R k NN search yielded a much higher precision than a random selection, standard nearest neighbor search, or when applying the method to a random protein-protein interaction network. All protein-disease pair candidates were verified by a literature search. Supporting evidence for 596 pairs was identified. In addition, cluster analysis of these candidates revealed 10 promising groups of diseases to be further investigated experimentally. This method can be used to identify novel associations to better understand complex relationships between proteins and diseases.
Molecular dynamics simulations and novel drug discovery.

PubMed

Liu, Xuewei; Shi, Danfeng; Zhou, Shuangyan; Liu, Hongli; Liu, Huanxiang; Yao, Xiaojun

2018-01-01

Molecular dynamics (MD) simulations can provide not only plentiful dynamical structural information on biomacromolecules but also a wealth of energetic information about protein and ligand interactions. Such information is very important to understanding the structure-function relationship of the target and the essence of protein-ligand interactions and to guiding the drug discovery and design process. Thus, MD simulations have been applied widely and successfully in each step of modern drug discovery. Areas covered: In this review, the authors review the applications of MD simulations in novel drug discovery, including the pathogenic mechanisms of amyloidosis diseases, virtual screening and the interaction mechanisms between drugs and targets. Expert opinion: MD simulations have been used widely in investigating the pathogenic mechanisms of diseases caused by protein misfolding, in virtual screening, and in investigating drug resistance mechanisms caused by mutations of the target. These issues are very difficult to solve by experimental methods alone. Thus, in the future, MD simulations will have wider application with the further improvement of computational capacity and the development of better sampling methods and more accurate force fields together with more efficient analysis methods.
Recent progress in the analysis of iced airfoils and wings

NASA Technical Reports Server (NTRS)

Cebeci, Tuncer; Chen, Hsun H.; Kaups, Kalle; Schimke, Sue

1992-01-01

Recent work on the analysis of iced airfoils and wings is described. Ice shapes for multielement airfoils and wings are computed using an extension of the LEWICE code that was developed for single airfoils. The aerodynamic properties of the iced wing are determined with an interactive scheme in which the solutions of the inviscid flow equations are obtained from a panel method and the solutions of the viscous flow equations are obtained from an inverse three-dimensional finite-difference boundary-layer method. A new interaction law is used to couple the inviscid and viscous flow solutions. The newly developed LEWICE multielement code is amplified to a high-lift configuration to calculate the ice shapes on the slat and on the main airfoil and on a four-element airfoil. The application of the LEWICE wing code to the calculation of ice shapes on a MS-317 swept wing shows good agreement with measurements. The interactive boundary-layer method is applied to a tapered iced wing in order to study the effect of icing on the aerodynamic properties of the wing at several angles of attack.
An Introduction to Recursive Partitioning: Rationale, Application, and Characteristics of Classification and Regression Trees, Bagging, and Random Forests

ERIC Educational Resources Information Center

Strobl, Carolin; Malley, James; Tutz, Gerhard

2009-01-01

Recursive partitioning methods have become popular and widely used tools for nonparametric regression and classification in many scientific fields. Especially random forests, which can deal with large numbers of predictor variables even in the presence of complex interactions, have been applied successfully in genetics, clinical medicine, and…
Applying Argumentation Analysis To Assess the Quality of University Oceanography Students' Scientific Writing.

ERIC Educational Resources Information Center

Takao, Allison Y.; Prothero, William A.; Kelly, Gregory J.

2002-01-01

Presents the methods and results of an assessment of students' scientific writing. Studies an introductory oceanography course in a large public university that used an interactive CD-ROM, "Our Dynamic Planet". Analyzes the quality of students' written arguments by using a grading rubric and an argumentation analysis model. Includes 18…
PEROXISOME-PROLIFERATOR ACTIVATED RECEPTORS AS A MACROMOLECULAR TARGET FOR CHEMICAL TOXICITY: MODELS OF THE INTERACTIONS OF PPARS WITH PERFLUORINATED ORGANIC COMPOUNDS-S

EPA Science Inventory

Many toxicological processes may be studied using the same paradigms as used in this study. As a result, methods applied here may have a far reaching effect for evaluating the risk of this and other classes of chemicals and other macromolecular targets.
Electrically tunable Dicke effect in a double-ring resonator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cetin, A. E.; Muestecaplioglu, Oe. E.; Department of Physics, Koc University, Sariyer, Istanbul 34450

We study the finite-element method analysis of the Dicke effect using numerical simulations in an all-optical system of an optical waveguide side-coupled to two interacting ring resonators in a liquid crystal environment. The system is shown to exhibit all the signatures of the Dicke effect under active and reversible control by an applied voltage.
Mass Media Representation of Teaching: A Behaviour Analysis Approach.

ERIC Educational Resources Information Center

Hobbs, Sandy; Mackie, Stirling

Although psychological studies of the mass media have been dominated by cognitivist and psychodynamic concepts, a study of the mass media using a behavior analysis method may be used to analyze the content of the mass media. By applying that analysis to fictional teacher-learner interactions an interpretation of those relationships can be made and…
Free-Surface Flow and Fluid-Object Interaction Modeling With Emphasis on Ship Hydrodynamics

DTIC Science & Technology

2012-01-01

0 on Cawt (21) in a weak sense. Equation (20) is the Eikonal partial differential equation subject to the interior constraint given by Eq. (21). To...tion, respectively. The formulation given by Eq. (22) is the SUPG method [30] applied to the Eikonal equation. At the steady state, the above problem

Optimal graph search segmentation using arc-weighted graph for simultaneous surface detection of bladder and prostate.

PubMed

Song, Qi; Wu, Xiaodong; Liu, Yunlong; Smith, Mark; Buatti, John; Sonka, Milan

2009-01-01

We present a novel method for globally optimal surface segmentation of multiple mutually interacting objects, incorporating both edge and shape knowledge in a 3-D graph-theoretic approach. Hard surface interacting constraints are enforced in the interacting regions, preserving the geometric relationship of those partially interacting surfaces. The soft smoothness a priori shape compliance is introduced into the energy functional to provide shape guidance. The globally optimal surfaces can be simultaneously achieved by solving a maximum flow problem based on an arc-weighted graph representation. Representing the segmentation problem in an arc-weighted graph, one can incorporate a wider spectrum of constraints into the formulation, thus increasing segmentation accuracy and robustness in volumetric image data. To the best of our knowledge, our method is the first attempt to introduce the arc-weighted graph representation into the graph-searching approach for simultaneous segmentation of multiple partially interacting objects, which admits a globally optimal solution in a low-order polynomial time. Our new approach was applied to the simultaneous surface detection of bladder and prostate. The result was quite encouraging in spite of the low saliency of the bladder and prostate in CT images.
AlignNemo: a local network alignment method to integrate homology and topology.

PubMed

Ciriello, Giovanni; Mina, Marco; Guzzi, Pietro H; Cannataro, Mario; Guerra, Concettina

2012-01-01

Local network alignment is an important component of the analysis of protein-protein interaction networks that may lead to the identification of evolutionary related complexes. We present AlignNemo, a new algorithm that, given the networks of two organisms, uncovers subnetworks of proteins that relate in biological function and topology of interactions. The discovered conserved subnetworks have a general topology and need not to correspond to specific interaction patterns, so that they more closely fit the models of functional complexes proposed in the literature. The algorithm is able to handle sparse interaction data with an expansion process that at each step explores the local topology of the networks beyond the proteins directly interacting with the current solution. To assess the performance of AlignNemo, we ran a series of benchmarks using statistical measures as well as biological knowledge. Based on reference datasets of protein complexes, AlignNemo shows better performance than other methods in terms of both precision and recall. We show our solutions to be biologically sound using the concept of semantic similarity applied to Gene Ontology vocabularies. The binaries of AlignNemo and supplementary details about the algorithms and the experiments are available at: sourceforge.net/p/alignnemo.
Hidden dimensions: the analysis of interaction in nurse-patient encounters.

PubMed

Chatwin, John

2008-01-01

It is well established that the success of much healthcare provision is strongly linked to the quality of interaction that occurs between healthcare professionals and patients. Nurse-led consultations are becoming ever more common in primary care, and patient satisfaction with this type of clinical encounter is reportedly high. While many fields of health care have been the subject of detailed interactional and socio-linguistic analysis, nurse-patient encounters are currently under-represented. This article will outline how one particular socio-linguistic approach - conversation analysis (CA) - can be applied to the investigation of nurse-led consultations. It will illustrate how the unique perspective that this method offers can reveal aspects of behaviour that would otherwise be inaccessible, and discusses the practical implications that a greater understanding of these behaviours can have for improving quality of care. The CA method is illustrated through the presentation and analysis of data collected as part of a recent study into nurse/patient interaction in a specialist wound dressing clinic. The sequential and treatment-related consequences of a simple interactional misalignment during the initial stages of a consultation are explored, and used to demonstrate how such misalignments can impact on treatment processes.
JET2 Viewer: a database of predicted multiple, possibly overlapping, protein-protein interaction sites for PDB structures.

PubMed

Ripoche, Hugues; Laine, Elodie; Ceres, Nicoletta; Carbone, Alessandra

2017-01-04

The database JET2 Viewer, openly accessible at http://www.jet2viewer.upmc.fr/, reports putative protein binding sites for all three-dimensional (3D) structures available in the Protein Data Bank (PDB). This knowledge base was generated by applying the computational method JET 2 at large-scale on more than 20 000 chains. JET 2 strategy yields very precise predictions of interacting surfaces and unravels their evolutionary process and complexity. JET2 Viewer provides an online intelligent display, including interactive 3D visualization of the binding sites mapped onto PDB structures and suitable files recording JET 2 analyses. Predictions were evaluated on more than 15 000 experimentally characterized protein interfaces. This is, to our knowledge, the largest evaluation of a protein binding site prediction method. The overall performance of JET 2 on all interfaces are: Sen = 52.52, PPV = 51.24, Spe = 80.05, Acc = 75.89. The data can be used to foster new strategies for protein-protein interactions modulation and interaction surface redesign. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
Navier-Stokes computations with finite-rate chemistry for LO2/LH2 rocket engine plume flow studies

NASA Technical Reports Server (NTRS)

Dougherty, N. Sam; Liu, Baw-Lin

1991-01-01

Computational fluid dynamics methods have been developed and applied to Space Shuttle Main Engine LO2/LH2 plume flow simulation/analysis of airloading and convective base heating effects on the vehicle at high flight velocities and altitudes. New methods are described which were applied to the simulation of a Return-to-Launch-Site abort where the vehicle would fly briefly at negative angles of attack into its own plume. A simplified two-perfect-gases-mixing approach is used where one gas is the plume and the other is air at 180-deg and 135-deg flight angle of attack. Related research has resulted in real gas multiple-plume interaction methods with finite-rate chemistry described herein which are applied to the same high-altitude-flight conditions of 0 deg angle of attack. Continuing research plans are to study Orbiter wake/plume flows at several Mach numbers and altitudes during ascent and then to merge this model with the Shuttle 'nose-to-tail' aerodynamic and SRB plume models for an overall 'nose-to-plume' capability. These new methods are also applicable to future launch vehicles using clustered-engine LO2/LH2 propulsion.
Location of cholesterol in liposomes by using small-angle X-ray scattering (SAXS) data and the generalized indirect Fourier transformation (GIFT) method.

PubMed

Aburai, Kenichi; Ogura, Taku; Hyodo, Ryo; Sakai, Hideki; Abe, Masahiko; Glatter, Otto

2013-01-01

We investigated the location of cholesterol (Chol) in liposomes and its interaction with phospholipids using small-angle x-ray scattering (SAXS) data and applying the generalized indirect Fourier transformation (GIFT) method. The GIFT method has been applied to lamellar liquid crystal systems and it gives quantitative data on bilayer thickness, electron density profile, and membrane flexibility (Caillé parameter). When the GIFT method is applied to the SAXS data of dipalmitoylphosphatidylcholine (DPPC) alone (Chol [-]) or a DPPC/Chol = 7/3 mixed system (Chol [+], molar ratio), change in the bilayer thickness was insignificant in both systems. However, the electron density for the Chol (+) system was higher than that for the Chol (-) system at the location of hydrophilic groups of phospholipids, and whereas Caillé parameter value increased with temperature for the Chol (-) system, no significant change with temperature was observed in the Caillé parameter for the Chol (+) system. These results indicated that Chol is located in the vicinity of the hydrophilic group of the phospholipids and constricts the packing of the acyl chain of phospholipids in the bilayer.
When the firm prevents the crash: Avoiding market collapse with partial control.

PubMed

Levi, Asaf; Sabuco, Juan; A F Sanjuán, Miguel

2017-01-01

Market collapse is one of the most dramatic events in economics. Such a catastrophic event can emerge from the nonlinear interactions between the economic agents at the micro level of the economy. Transient chaos might be a good description of how a collapsing market behaves. In this work, we apply a new control method, the partial control method, with the goal of avoiding this disastrous event. Contrary to common control methods that try to influence the system from the outside, here the market is controlled from the bottom up by one of the most basic components of the market-the firm. This is the first time that the partial control method is applied on a strictly economical system in which we also introduce external disturbances. We show how the firm is capable of controlling the system avoiding the collapse by only adjusting the selling price of the product or the quantity of production in accordance to the market circumstances. Additionally, we demonstrate how a firm with a large market share is capable of influencing the demand achieving price stability across the retail and wholesale markets. Furthermore, we prove that the control applied in both cases is much smaller than the external disturbances.
DDR: efficient computational method to predict drug-target interactions using graph mining and machine learning approaches.

PubMed

Olayan, Rawan S; Ashoor, Haitham; Bajic, Vladimir B

2018-04-01

Finding computationally drug-target interactions (DTIs) is a convenient strategy to identify new DTIs at low cost with reasonable accuracy. However, the current DTI prediction methods suffer the high false positive prediction rate. We developed DDR, a novel method that improves the DTI prediction accuracy. DDR is based on the use of a heterogeneous graph that contains known DTIs with multiple similarities between drugs and multiple similarities between target proteins. DDR applies non-linear similarity fusion method to combine different similarities. Before fusion, DDR performs a pre-processing step where a subset of similarities is selected in a heuristic process to obtain an optimized combination of similarities. Then, DDR applies a random forest model using different graph-based features extracted from the DTI heterogeneous graph. Using 5-repeats of 10-fold cross-validation, three testing setups, and the weighted average of area under the precision-recall curve (AUPR) scores, we show that DDR significantly reduces the AUPR score error relative to the next best start-of-the-art method for predicting DTIs by 34% when the drugs are new, by 23% when targets are new and by 34% when the drugs and the targets are known but not all DTIs between them are not known. Using independent sources of evidence, we verify as correct 22 out of the top 25 DDR novel predictions. This suggests that DDR can be used as an efficient method to identify correct DTIs. The data and code are provided at https://bitbucket.org/RSO24/ddr/. vladimir.bajic@kaust.edu.sa. Supplementary data are available at Bioinformatics online.
Quality by Design approach in the development of hydrophilic interaction liquid chromatographic method for the analysis of iohexol and its impurities.

PubMed

Jovanović, Marko; Rakić, Tijana; Tumpa, Anja; Jančić Stojanović, Biljana

2015-06-10

This study presents the development of hydrophilic interaction liquid chromatographic method for the analysis of iohexol, its endo-isomer and three impurities following Quality by Design (QbD) approach. The main objective of the method was to identify the conditions where adequate separation quality in minimal analysis duration could be achieved within a robust region that guarantees the stability of method performance. The relationship between critical process parameters (acetonitrile content in the mobile phase, pH of the water phase and ammonium acetate concentration in the water phase) and critical quality attributes is created applying design of experiments methodology. The defined mathematical models and Monte Carlo simulation are used to evaluate the risk of uncertainty in models prediction and incertitude in adjusting the process parameters and to identify the design space. The borders of the design space are experimentally verified and confirmed that the quality of the method is preserved in this region. Moreover, Plackett-Burman design is applied for experimental robustness testing and method is fully validated to verify the adequacy of selected optimal conditions: the analytical column ZIC HILIC (100 mm × 4.6 mm, 5 μm particle size); mobile phase consisted of acetonitrile-water phase (72 mM ammonium acetate, pH adjusted to 6.5 with glacial acetic acid) (86.7:13.3) v/v; column temperature 25 °C, mobile phase flow rate 1 mL min(-1), wavelength of detection 254 nm. Copyright © 2015 Elsevier B.V. All rights reserved.
Utilizing a Robotic Sprayer for High Lateral and Mass Resolution MALDI FT-ICR MSI of Microbial Cultures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderton, Christopher R.; Chu, Rosalie K.; Tolic, Nikola

The ability to visualize biochemical interactions between microbial communities using MALDI MSI has provided tremendous insights into a variety of biological fields. Matrix application using a sieve proved to be incredibly useful, but it had many limitations that include uneven matrix coverage and limitation in the types of matrices one could employ in their studies. Recently, there has been a concerted effort to improve matrix application for studying agar plated microbial cultures, many of which utilized automated matrix sprayers. Here, we describe the usefulness of using a robotic sprayer for matrix application. The robotic sprayer has two-dimensional control over wheremore » matrix is applied and a heated capillary that allows for rapid drying of the applied matrix. This method provided a significant increase in MALDI sensitivity over the sieve method, as demonstrated by FT-ICR MS analysis, facilitating the ability to gain higher lateral resolution MS images of Bacillus Subtilis than previously reported. This method also allowed for the use of different matrices to be applied to the culture surfaces.« less
Pressor mechanism evaluation for phytochemical compounds using in silico compound-protein interaction prediction.

PubMed

He, Min; Cao, Dong-Sheng; Liang, Yi-Zeng; Li, Ya-Ping; Liu, Ping-Le; Xu, Qing-Song; Huang, Ren-Bin

2013-10-01

In this study, a method was applied to evaluate pressor mechanisms through compound-protein interactions. Our method assumed that the compounds with different pressor mechanisms should bind to different target proteins, and thereby these mechanisms could be differentiated using compound-protein interactions. Twenty-six phytochemical components and 46 tested target proteins related to blood pressure (BP) elevation were collected. Then, in silico compound-protein interactions prediction probabilities were calculated using a random forest model, which have been implemented in a web server, and the credibility was judged using related literature and other methods. Further, a heat map was constructed, it clearly showed different prediction probabilities accompanied with hierarchical clustering analysis results. Followed by a compound-protein interaction network was depicted according to the results, we can see the connectivity layout of phytochemical components with different target proteins within the BP elevation network, which guided the hypothesis generation of poly-pharmacology. Lastly, principal components analysis (PCA) was carried out upon the prediction probabilities, and pressor targets could be divided into three large classes: neurotransmitter receptors, hormones receptors and monoamine oxidases. In addition, steroid glycosides seem to be close to the region of hormone receptors, and a weak difference existed between them. This work explored the possibility for pharmacological or toxicological mechanism classification using compound-protein interactions. Such approaches could also be used to deduce pharmacological or toxicological mechanisms for uncharacterized compounds. Copyright © 2013 Elsevier Inc. All rights reserved.
Application of parallel distributed Lagrange multiplier technique to simulate coupled Fluid-Granular flows in pipes with varying Cross-Sectional area

DOE PAGES

Kanarska, Yuliya; Walton, Otis

2015-11-30

Fluid-granular flows are common phenomena in nature and industry. Here, an efficient computational technique based on the distributed Lagrange multiplier method is utilized to simulate complex fluid-granular flows. Each particle is explicitly resolved on an Eulerian grid as a separate domain, using solid volume fractions. The fluid equations are solved through the entire computational domain, however, Lagrange multiplier constrains are applied inside the particle domain such that the fluid within any volume associated with a solid particle moves as an incompressible rigid body. The particle–particle interactions are implemented using explicit force-displacement interactions for frictional inelastic particles similar to the DEMmore » method with some modifications using the volume of an overlapping region as an input to the contact forces. Here, a parallel implementation of the method is based on the SAMRAI (Structured Adaptive Mesh Refinement Application Infrastructure) library.« less
Acoustic coupled fluid-structure interactions using a unified fast multipole boundary element method.

PubMed

Wilkes, Daniel R; Duncan, Alec J

2015-04-01

This paper presents a numerical model for the acoustic coupled fluid-structure interaction (FSI) of a submerged finite elastic body using the fast multipole boundary element method (FMBEM). The Helmholtz and elastodynamic boundary integral equations (BIEs) are, respectively, employed to model the exterior fluid and interior solid domains, and the pressure and displacement unknowns are coupled between conforming meshes at the shared boundary interface to achieve the acoustic FSI. The low frequency FMBEM is applied to both BIEs to reduce the algorithmic complexity of the iterative solution from O(N(2)) to O(N(1.5)) operations per matrix-vector product for N boundary unknowns. Numerical examples are presented to demonstrate the algorithmic and memory complexity of the method, which are shown to be in good agreement with the theoretical estimates, while the solution accuracy is comparable to that achieved by a conventional finite element-boundary element FSI model.
irGPU.proton.Net: Irregular strong charge interaction networks of protonatable groups in protein molecules--a GPU solver using the fast multipole method and statistical thermodynamics.

PubMed

Kantardjiev, Alexander A

2015-04-05

A cluster of strongly interacting ionization groups in protein molecules with irregular ionization behavior is suggestive for specific structure-function relationship. However, their computational treatment is unconventional (e.g., lack of convergence in naive self-consistent iterative algorithm). The stringent evaluation requires evaluation of Boltzmann averaged statistical mechanics sums and electrostatic energy estimation for each microstate. irGPU: Irregular strong interactions in proteins--a GPU solver is novel solution to a versatile problem in protein biophysics--atypical protonation behavior of coupled groups. The computational severity of the problem is alleviated by parallelization (via GPU kernels) which is applied for the electrostatic interaction evaluation (including explicit electrostatics via the fast multipole method) as well as statistical mechanics sums (partition function) estimation. Special attention is given to the ease of the service and encapsulation of theoretical details without sacrificing rigor of computational procedures. irGPU is not just a solution-in-principle but a promising practical application with potential to entice community into deeper understanding of principles governing biomolecule mechanisms. © 2015 Wiley Periodicals, Inc.
Monte Carlo renormalization-group study of the Baxter-Wu model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Novotny, M.A.; Landau, D.P.; Swendsen, R.H.

1982-07-01

The effectiveness of a Monte Carlo renormalization-group method is studied by applying it to the Baxter-Wu model (Ising spins on a triangular lattice with three-spin interactions). The calculations yield three relevent eigenvalues in good agreement with exact or conjectured results. We demonstrate that the method is capable of distinguishing between models expected to be in the same universality class, when one of them (four-state Potts) exhibits logarithmic corrections to the usual power-law singularities and the other (Baxter-Wu) does not.
Strippable containment and decontamination coating composition and method of use

DOEpatents

Moore, Robert C [Edgewood, NM; Tucker, Mark D [Albuquerque, NM; Jones, Joseph A [Albuquerque, NM

2009-04-07

A method for containing at least a portion of radioisotopes, radionuclides, heavy metal or combination thereof contaminating a substrate wherein a containment composition is applied to the substrate. The ingredients within the containment composition interact with the contaminants on the surface of the substrate until the containment composition has polymerized to a water insoluble form containing at least a portion of the contaminates enmeshed therein. The dried composition is removed from the contaminated surface removing with the composition at least a portion of the contaminate.
A robust multifactor dimensionality reduction method for detecting gene-gene interactions with application to the genetic analysis of bladder cancer susceptibility

PubMed Central

Gui, Jiang; Andrew, Angeline S.; Andrews, Peter; Nelson, Heather M.; Kelsey, Karl T.; Karagas, Margaret R.; Moore, Jason H.

2010-01-01

A central goal of human genetics is to identify and characterize susceptibility genes for common complex human diseases. An important challenge in this endeavor is the modeling of gene-gene interaction or epistasis that can result in non-additivity of genetic effects. The multifactor dimensionality reduction (MDR) method was developed as machine learning alternative to parametric logistic regression for detecting interactions in absence of significant marginal effects. The goal of MDR is to reduce the dimensionality inherent in modeling combinations of polymorphisms using a computational approach called constructive induction. Here, we propose a Robust Multifactor Dimensionality Reduction (RMDR) method that performs constructive induction using a Fisher’s Exact Test rather than a predetermined threshold. The advantage of this approach is that only those genotype combinations that are determined to be statistically significant are considered in the MDR analysis. We use two simulation studies to demonstrate that this approach will increase the success rate of MDR when there are only a few genotype combinations that are significantly associated with case-control status. We show that there is no loss of success rate when this is not the case. We then apply the RMDR method to the detection of gene-gene interactions in genotype data from a population-based study of bladder cancer in New Hampshire. PMID:21091664
Application programming in C# environment with recorded user software interactions and its application in autopilot of VMAT/IMRT treatment planning.

PubMed

Wang, Henry; Xing, Lei

2016-11-08

An autopilot scheme of volumetric-modulated arc therapy (VMAT)/intensity-modulated radiation therapy (IMRT) planning with the guidance of prior knowl-edge is established with recorded interactions between a planner and a commercial treatment planning system (TPS). Microsoft (MS) Visual Studio Coded UI is applied to record some common planner-TPS interactions as subroutines. The TPS used in this study is a Windows-based Eclipse system. The interactions of our application program with Eclipse TPS are realized through a series of subrou-tines obtained by prerecording the mouse clicks or keyboard strokes of a planner in operating the TPS. A strategy to autopilot Eclipse VMAT/IMRT plan selection process is developed as a specific example of the proposed "scripting" method. The autopiloted planning is navigated by a decision function constructed with a reference plan that has the same prescription and similar anatomy with the case at hand. The calculation proceeds by alternating between the Eclipse optimization and the outer-loop optimization independent of the Eclipse. In the C# program, the dosimetric characteristics of a reference treatment plan are used to assess and modify the Eclipse planning parameters and to guide the search for a clinically sensible treatment plan. The approach is applied to plan a head and neck (HN) VMAT case and a prostate IMRT case. Our study demonstrated the feasibility of application programming method in C# environment with recorded interactions of planner-TPS. The process mimics a planner's planning process and automatically provides clinically sensible treatment plans that would otherwise require a large amount of manual trial and error of a planner. The proposed technique enables us to harness a commercial TPS by application programming via the use of recorded human computer interactions and provides an effective tool to greatly facilitate the treatment planning process. © 2016 The Authors.
Interpersonal behaviors and socioemotional interaction of medical students in a virtual clinical encounter

PubMed Central

2014-01-01

Background The virtual clinical encounter (VCE) may function as an important support for medical students in or prior to clinical practice to train and ease communication and socioemotional interactions with patients. Few studies have however focused on the dynamics of interpersonal behaviors in clinical interviewing with a virtual patient (VP) and the affective responses evoked by such a learning experience. The study was designed to investigate the dynamics and congruence of interpersonal behaviors and socioemotional interaction exhibited during the learning experience in a VCE, and to evaluate which interaction design characteristics contribute most to the behavioral and affective engagement in medical students. Methods Thirty medical students (sixth semester) participated voluntarily in an exploratory observational study with a highly interactive VP case based on a trustworthy VP encounter with a natural and realistic dialogue interface. Students worked collaboratively in pairs. They were videotaped for further behavioral analysis and self-reported (in both a survey and an interview) their personal opinions, perceptions and attitudes about the VCE. A mixed methods approach was applied. Results All participants demonstrated an adequate, respectful and relevant clinical case management and to obtain psychosocial history. The collaborative workspace played its role and led to dynamic and engaged discussions fostering thus shared understanding. The results suggest that the VCE studied was perceived as a meaningful, intrinsically motivational and activating learning environment, and was found to socially and emotionally engage learners. We also found that VCEs have the potential to support the development of relevant and congruent interpersonal communication skills in trainees. Conclusions By taking advantage of socioemotional interaction, VCEs promote not only critical reflection skills or strategy-selection skills, but also to develop listening and nonverbal skills, induce self-awareness and target coping behaviours. We believe that, if applied in early medical education, this learning approach may facilitate clinical encounters at an early stage and contribute to responsible clinical decision making. PMID:24685070
Application programming in C# environment with recorded user software interactions and its application in autopilot of VMAT/IMRT treatment planning

PubMed Central

Wang, Henry

2016-01-01

An autopilot scheme of volumetric‐modulated arc therapy (VMAT)/intensity‐modulated radiation therapy (IMRT) planning with the guidance of prior knowledge is established with recorded interactions between a planner and a commercial treatment planning system (TPS). Microsoft (MS) Visual Studio Coded UI is applied to record some common planner‐TPS interactions as subroutines. The TPS used in this study is a Windows‐based Eclipse system. The interactions of our application program with Eclipse TPS are realized through a series of subroutines obtained by prerecording the mouse clicks or keyboard strokes of a planner in operating the TPS. A strategy to autopilot Eclipse VMAT/IMRT plan selection process is developed as a specific example of the proposed “scripting” method. The autopiloted planning is navigated by a decision function constructed with a reference plan that has the same prescription and similar anatomy with the case at hand. The calculation proceeds by alternating between the Eclipse optimization and the outer‐loop optimization independent of the Eclipse. In the C# program, the dosimetric characteristics of a reference treatment plan are used to assess and modify the Eclipse planning parameters and to guide the search for a clinically sensible treatment plan. The approach is applied to plan a head and neck (HN) VMAT case and a prostate IMRT case. Our study demonstrated the feasibility of application programming method in C# environment with recorded interactions of planner‐TPS. The process mimics a planner's planning process and automatically provides clinically sensible treatment plans that would otherwise require a large amount of manual trial and error of a planner. The proposed technique enables us to harness a commercial TPS by application programming via the use of recorded human computer interactions and provides an effective tool to greatly facilitate the treatment planning process. PACS number(s): 87.55.D‐, 87.55.kd, 87.55.de PMID:27929493

Transforming Collaborative Process Models into Interface Process Models by Applying an MDA Approach

NASA Astrophysics Data System (ADS)

Lazarte, Ivanna M.; Chiotti, Omar; Villarreal, Pablo D.

Collaborative business models among enterprises require defining collaborative business processes. Enterprises implement B2B collaborations to execute these processes. In B2B collaborations the integration and interoperability of processes and systems of the enterprises are required to support the execution of collaborative processes. From a collaborative process model, which describes the global view of the enterprise interactions, each enterprise must define the interface process that represents the role it performs in the collaborative process in order to implement the process in a Business Process Management System. Hence, in this work we propose a method for the automatic generation of the interface process model of each enterprise from a collaborative process model. This method is based on a Model-Driven Architecture to transform collaborative process models into interface process models. By applying this method, interface processes are guaranteed to be interoperable and defined according to a collaborative process.
A Nonlinear Model for Gene-Based Gene-Environment Interaction.

PubMed

Sa, Jian; Liu, Xu; He, Tao; Liu, Guifen; Cui, Yuehua

2016-06-04

A vast amount of literature has confirmed the role of gene-environment (G×E) interaction in the etiology of complex human diseases. Traditional methods are predominantly focused on the analysis of interaction between a single nucleotide polymorphism (SNP) and an environmental variable. Given that genes are the functional units, it is crucial to understand how gene effects (rather than single SNP effects) are influenced by an environmental variable to affect disease risk. Motivated by the increasing awareness of the power of gene-based association analysis over single variant based approach, in this work, we proposed a sparse principle component regression (sPCR) model to understand the gene-based G×E interaction effect on complex disease. We first extracted the sparse principal components for SNPs in a gene, then the effect of each principal component was modeled by a varying-coefficient (VC) model. The model can jointly model variants in a gene in which their effects are nonlinearly influenced by an environmental variable. In addition, the varying-coefficient sPCR (VC-sPCR) model has nice interpretation property since the sparsity on the principal component loadings can tell the relative importance of the corresponding SNPs in each component. We applied our method to a human birth weight dataset in Thai population. We analyzed 12,005 genes across 22 chromosomes and found one significant interaction effect using the Bonferroni correction method and one suggestive interaction. The model performance was further evaluated through simulation studies. Our model provides a system approach to evaluate gene-based G×E interaction.
Identification of Histone Deacetylase (HDAC) as a drug target against MRSA via interolog method of protein-protein interaction prediction.

PubMed

Uddin, Reaz; Tariq, Syeda Sumayya; Azam, Syed Sikander; Wadood, Abdul; Moin, Syed Tarique

2017-08-30

Patently, Protein-Protein Interactions (PPIs) lie at the core of significant biological functions and make the foundation of host-pathogen relationships. Hence, the current study is aimed to use computational biology techniques to predict host-pathogen Protein-Protein Interactions (HP-PPIs) between MRSA and Humans as potential drug targets ultimately proposing new possible inhibitors against them. As a matter of fact this study is based on the Interolog method which implies that homologous proteins retain their ability to interact. A distant homolog approach based on Interolog method was employed to speculate MRSA protein homologs in Humans using PSI-BLAST. In addition the protein interaction partners of these homologs as listed in Database of Interacting Proteins (DIP) were predicted to interact with MRSA as well. Moreover, a direct approach using BLAST was also applied so as to attain further confidence in the strategy. Consequently, the common HP-PPIs predicted by both approaches are suggested as potential drug targets (22%) whereas, the unique HP-PPIs estimated only through distant homolog approach are presented as novel drug targets (12%). Furthermore, the most repeated entry in our results was found to be MRSA Histone Deacetylase (HDAC) which was then modeled using SWISS-MODEL. Eventually, small molecules from ZINC, selected randomly, were docked against HDAC using Auto Dock and are suggested as potential binders (inhibitors) based on their energetic profiles. Thus the current study provides basis for further in-depth analysis of such data which not only include MRSA but other deadly pathogens as well. Copyright © 2017 Elsevier B.V. All rights reserved.
RESEARCH: Conceptualizing Environmental Stress: A Stress-Response Model of Coastal Sandy Barriers.

PubMed

Gabriel; Kreutzwiser

2000-01-01

/ The purpose of this paper is to develop and apply a conceptual framework of environmental stress-response for a geomorphic system. Constructs and methods generated from the literature were applied in the development of an integrative stress-response framework using existing environmental assessment techniques: interaction matrices and a systems diagram. Emphasis is on the interaction between environmental stress and the geomorphic environment of a sandy barrier system. The model illustrates a number of stress concepts pertinent to modeling environmental stress-response, including those related to stress-dependency, frequency-recovery relationships, environmental heterogeneity, spatial hierarchies and linkages, and temporal change. Sandy barrier stress-response and recovery are greatly impacted by fluctuating water levels, stress intensity and frequency, as well as environmental gradients such as differences in sediment storage and supply. Aspects of these stress-response variables are articulated in terms of three main challenges to management: dynamic stability, spatial integrity, and temporal variability. These in turn form the framework for evaluative principles that may be applied to assess how policies and management practices reflect key biophysical processes and human stresses identified by the model.
Dynamics of Disagreement: Large-Scale Temporal Network Analysis Reveals Negative Interactions in Online Collaboration

NASA Astrophysics Data System (ADS)

Tsvetkova, Milena; García-Gavilanes, Ruth; Yasseri, Taha

2016-11-01

Disagreement and conflict are a fact of social life. However, negative interactions are rarely explicitly declared and recorded and this makes them hard for scientists to study. In an attempt to understand the structural and temporal features of negative interactions in the community, we use complex network methods to analyze patterns in the timing and configuration of reverts of article edits to Wikipedia. We investigate how often and how fast pairs of reverts occur compared to a null model in order to control for patterns that are natural to the content production or are due to the internal rules of Wikipedia. Our results suggest that Wikipedia editors systematically revert the same person, revert back their reverter, and come to defend a reverted editor. We further relate these interactions to the status of the involved editors. Even though the individual reverts might not necessarily be negative social interactions, our analysis points to the existence of certain patterns of negative social dynamics within the community of editors. Some of these patterns have not been previously explored and carry implications for the knowledge collection practice conducted on Wikipedia. Our method can be applied to other large-scale temporal collaboration networks to identify the existence of negative social interactions and other social processes.
Interface projection techniques for fluid-structure interaction modeling with moving-mesh methods

NASA Astrophysics Data System (ADS)

Tezduyar, Tayfun E.; Sathe, Sunil; Pausewang, Jason; Schwaab, Matthew; Christopher, Jason; Crabtree, Jason

2008-12-01

The stabilized space-time fluid-structure interaction (SSTFSI) technique developed by the Team for Advanced Flow Simulation and Modeling (T★AFSM) was applied to a number of 3D examples, including arterial fluid mechanics and parachute aerodynamics. Here we focus on the interface projection techniques that were developed as supplementary methods targeting the computational challenges associated with the geometric complexities of the fluid-structure interface. Although these supplementary techniques were developed in conjunction with the SSTFSI method and in the context of air-fabric interactions, they can also be used in conjunction with other moving-mesh methods, such as the Arbitrary Lagrangian-Eulerian (ALE) method, and in the context of other classes of FSI applications. The supplementary techniques currently consist of using split nodal values for pressure at the edges of the fabric and incompatible meshes at the air-fabric interfaces, the FSI Geometric Smoothing Technique (FSI-GST), and the Homogenized Modeling of Geometric Porosity (HMGP). Using split nodal values for pressure at the edges and incompatible meshes at the interfaces stabilizes the structural response at the edges of the membrane used in modeling the fabric. With the FSI-GST, the fluid mechanics mesh is sheltered from the consequences of the geometric complexity of the structure. With the HMGP, we bypass the intractable complexities of the geometric porosity by approximating it with an “equivalent”, locally-varying fabric porosity. As test cases demonstrating how the interface projection techniques work, we compute the air-fabric interactions of windsocks, sails and ringsail parachutes.
Probing the chemical interaction space governed by 4-aminosubstituted benzenesulfonamides and carbonic anhydrase isoforms.

PubMed

Rasti, Behnam; Heravi, Yeganeh Entezari

2018-06-01

Isoform diversity, critical physiological roles and involvement in major diseases/disorders such as glaucoma, epilepsy, Alzheimer's disease, obesity, and cancers have made carbonic anhydrase (CA), one of the most interesting case studies in the field of computer aided drug design. Since applying non-selective inhibitors can result in major side effects, there have been considerable efforts so far to achieve selective inhibitors for different isoforms of CA. Using proteochemometrics approach, the chemical interaction space governed by a group of 4-amino-substituted benzenesulfonamides and human CAs has been explored in the present study. Several validation methods have been utilized to assess the validity, robustness and predictivity power of the proposed proteochemometric model. Our model has offered major structural information that can be applied to design new selective inhibitors for distinct isoforms of CA. To prove the applicability of the proposed model, new compounds have been designed based on the offered discriminative structural features.
GLO-STIX: Graph-Level Operations for Specifying Techniques and Interactive eXploration

PubMed Central

Stolper, Charles D.; Kahng, Minsuk; Lin, Zhiyuan; Foerster, Florian; Goel, Aakash; Stasko, John; Chau, Duen Horng

2015-01-01

The field of graph visualization has produced a wealth of visualization techniques for accomplishing a variety of analysis tasks. Therefore analysts often rely on a suite of different techniques, and visual graph analysis application builders strive to provide this breadth of techniques. To provide a holistic model for specifying network visualization techniques (as opposed to considering each technique in isolation) we present the Graph-Level Operations (GLO) model. We describe a method for identifying GLOs and apply it to identify five classes of GLOs, which can be flexibly combined to re-create six canonical graph visualization techniques. We discuss advantages of the GLO model, including potentially discovering new, effective network visualization techniques and easing the engineering challenges of building multi-technique graph visualization applications. Finally, we implement the GLOs that we identified into the GLO-STIX prototype system that enables an analyst to interactively explore a graph by applying GLOs. PMID:26005315
DOE Office of Scientific and Technical Information (OSTI.GOV)

Quon, Eliot; Platt, Andrew; Yu, Yi-Hsiang

Extreme loads are often a key cost driver for wave energy converters (WECs). As an alternative to exhaustive Monte Carlo or long-term simulations, the most likely extreme response (MLER) method allows mid- and high-fidelity simulations to be used more efficiently in evaluating WEC response to events at the edges of the design envelope, and is therefore applicable to system design analysis. The study discussed in this paper applies the MLER method to investigate the maximum heave, pitch, and surge force of a point absorber WEC. Most likely extreme waves were obtained from a set of wave statistics data based onmore » spectral analysis and the response amplitude operators (RAOs) of the floating body; the RAOs were computed from a simple radiation-and-diffraction-theory-based numerical model. A weakly nonlinear numerical method and a computational fluid dynamics (CFD) method were then applied to compute the short-term response to the MLER wave. Effects of nonlinear wave and floating body interaction on the WEC under the anticipated 100-year waves were examined by comparing the results from the linearly superimposed RAOs, the weakly nonlinear model, and CFD simulations. Overall, the MLER method was successfully applied. In particular, when coupled to a high-fidelity CFD analysis, the nonlinear fluid dynamics can be readily captured.« less
A Brownian dynamics study on ferrofluid colloidal dispersions using an iterative constraint method to satisfy Maxwell’s equations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dubina, Sean Hyun, E-mail: sdubin2@uic.edu; Wedgewood, Lewis Edward, E-mail: wedge@uic.edu

2016-07-15

Ferrofluids are often favored for their ability to be remotely positioned via external magnetic fields. The behavior of particles in ferromagnetic clusters under uniformly applied magnetic fields has been computationally simulated using the Brownian dynamics, Stokesian dynamics, and Monte Carlo methods. However, few methods have been established that effectively handle the basic principles of magnetic materials, namely, Maxwell’s equations. An iterative constraint method was developed to satisfy Maxwell’s equations when a uniform magnetic field is imposed on ferrofluids in a heterogeneous Brownian dynamics simulation that examines the impact of ferromagnetic clusters in a mesoscale particle collection. This was accomplished bymore » allowing a particulate system in a simple shear flow to advance by a time step under a uniformly applied magnetic field, then adjusting the ferroparticles via an iterative constraint method applied over sub-volume length scales until Maxwell’s equations were satisfied. The resultant ferrofluid model with constraints demonstrates that the magnetoviscosity contribution is not as substantial when compared to homogeneous simulations that assume the material’s magnetism is a direct response to the external magnetic field. This was detected across varying intensities of particle-particle interaction, Brownian motion, and shear flow. Ferroparticle aggregation was still extensively present but less so than typically observed.« less
Fulfilling the law of a single independent variable and improving the result of mathematical educational research

NASA Astrophysics Data System (ADS)

Pardimin, H.; Arcana, N.

2018-01-01

Many types of research in the field of mathematics education apply the Quasi-Experimental method and statistical analysis use t-test. Quasi-experiment has a weakness that is difficult to fulfil “the law of a single independent variable”. T-test also has a weakness that is a generalization of the conclusions obtained is less powerful. This research aimed to find ways to reduce the weaknesses of the Quasi-experimental method and improved the generalization of the research results. The method applied in the research was a non-interactive qualitative method, and the type was concept analysis. Concepts analysed are the concept of statistics, research methods of education, and research reports. The result represented a way to overcome the weaknesses of quasi-Experiments and T-test. In addition, the way was to apply a combination of Factorial Design and Balanced Design, which the authors refer to as Factorial-Balanced Design. The advantages of this design are: (1) almost fulfilling “the low of single independent variable” so no need to test the similarity of the academic ability, (2) the sample size of the experimental group and the control group became larger and equal; so it becomes robust to deal with violations of the assumptions of the ANOVA test.
A coevolution analysis for identifying protein-protein interactions by Fourier transform.

PubMed

Yin, Changchuan; Yau, Stephen S-T

2017-01-01

Protein-protein interactions (PPIs) play key roles in life processes, such as signal transduction, transcription regulations, and immune response, etc. Identification of PPIs enables better understanding of the functional networks within a cell. Common experimental methods for identifying PPIs are time consuming and expensive. However, recent developments in computational approaches for inferring PPIs from protein sequences based on coevolution theory avoid these problems. In the coevolution theory model, interacted proteins may show coevolutionary mutations and have similar phylogenetic trees. The existing coevolution methods depend on multiple sequence alignments (MSA); however, the MSA-based coevolution methods often produce high false positive interactions. In this paper, we present a computational method using an alignment-free approach to accurately detect PPIs and reduce false positives. In the method, protein sequences are numerically represented by biochemical properties of amino acids, which reflect the structural and functional differences of proteins. Fourier transform is applied to the numerical representation of protein sequences to capture the dissimilarities of protein sequences in biophysical context. The method is assessed for predicting PPIs in Ebola virus. The results indicate strong coevolution between the protein pairs (NP-VP24, NP-VP30, NP-VP40, VP24-VP30, VP24-VP40, and VP30-VP40). The method is also validated for PPIs in influenza and E.coli genomes. Since our method can reduce false positive and increase the specificity of PPI prediction, it offers an effective tool to understand mechanisms of disease pathogens and find potential targets for drug design. The Python programs in this study are available to public at URL (https://github.com/cyinbox/PPI).
An immersed boundary method for fluid-structure interaction with compressible multiphase flows

NASA Astrophysics Data System (ADS)

Wang, Li; Currao, Gaetano M. D.; Han, Feng; Neely, Andrew J.; Young, John; Tian, Fang-Bao

2017-10-01

This paper presents a two-dimensional immersed boundary method for fluid-structure interaction with compressible multiphase flows involving large structure deformations. This method involves three important parts: flow solver, structure solver and fluid-structure interaction coupling. In the flow solver, the compressible multiphase Navier-Stokes equations for ideal gases are solved by a finite difference method based on a staggered Cartesian mesh, where a fifth-order accuracy Weighted Essentially Non-Oscillation (WENO) scheme is used to handle spatial discretization of the convective term, a fourth-order central difference scheme is employed to discretize the viscous term, the third-order TVD Runge-Kutta scheme is used to discretize the temporal term, and the level-set method is adopted to capture the multi-material interface. In this work, the structure considered is a geometrically non-linear beam which is solved by using a finite element method based on the absolute nodal coordinate formulation (ANCF). The fluid dynamics and the structure motion are coupled in a partitioned iterative manner with a feedback penalty immersed boundary method where the flow dynamics is defined on a fixed Lagrangian grid and the structure dynamics is described on a global coordinate. We perform several validation cases (including fluid over a cylinder, structure dynamics, flow induced vibration of a flexible plate, deformation of a flexible panel induced by shock waves in a shock tube, an inclined flexible plate in a hypersonic flow, and shock-induced collapse of a cylindrical helium cavity in the air), and compare the results with experimental and other numerical data. The present results agree well with the published data and the current experiment. Finally, we further demonstrate the versatility of the present method by applying it to a flexible plate interacting with multiphase flows.
A coevolution analysis for identifying protein-protein interactions by Fourier transform

PubMed Central

Yin, Changchuan; Yau, Stephen S. -T.

2017-01-01

Protein-protein interactions (PPIs) play key roles in life processes, such as signal transduction, transcription regulations, and immune response, etc. Identification of PPIs enables better understanding of the functional networks within a cell. Common experimental methods for identifying PPIs are time consuming and expensive. However, recent developments in computational approaches for inferring PPIs from protein sequences based on coevolution theory avoid these problems. In the coevolution theory model, interacted proteins may show coevolutionary mutations and have similar phylogenetic trees. The existing coevolution methods depend on multiple sequence alignments (MSA); however, the MSA-based coevolution methods often produce high false positive interactions. In this paper, we present a computational method using an alignment-free approach to accurately detect PPIs and reduce false positives. In the method, protein sequences are numerically represented by biochemical properties of amino acids, which reflect the structural and functional differences of proteins. Fourier transform is applied to the numerical representation of protein sequences to capture the dissimilarities of protein sequences in biophysical context. The method is assessed for predicting PPIs in Ebola virus. The results indicate strong coevolution between the protein pairs (NP-VP24, NP-VP30, NP-VP40, VP24-VP30, VP24-VP40, and VP30-VP40). The method is also validated for PPIs in influenza and E.coli genomes. Since our method can reduce false positive and increase the specificity of PPI prediction, it offers an effective tool to understand mechanisms of disease pathogens and find potential targets for drug design. The Python programs in this study are available to public at URL (https://github.com/cyinbox/PPI). PMID:28430779
Intuitive Density Functional Theory-Based Energy Decomposition Analysis for Protein-Ligand Interactions.

PubMed

Phipps, M J S; Fox, T; Tautermann, C S; Skylaris, C-K

2017-04-11

First-principles quantum mechanical calculations with methods such as density functional theory (DFT) allow the accurate calculation of interaction energies between molecules. These interaction energies can be dissected into chemically relevant components such as electrostatics, polarization, and charge transfer using energy decomposition analysis (EDA) approaches. Typically EDA has been used to study interactions between small molecules; however, it has great potential to be applied to large biomolecular assemblies such as protein-protein and protein-ligand interactions. We present an application of EDA calculations to the study of ligands that bind to the thrombin protein, using the ONETEP program for linear-scaling DFT calculations. Our approach goes beyond simply providing the components of the interaction energy; we are also able to provide visual representations of the changes in density that happen as a result of polarization and charge transfer, thus pinpointing the functional groups between the ligand and protein that participate in each kind of interaction. We also demonstrate with this approach that we can focus on studying parts (fragments) of ligands. The method is relatively insensitive to the protocol that is used to prepare the structures, and the results obtained are therefore robust. This is an application to a real protein drug target of a whole new capability where accurate DFT calculations can produce both energetic and visual descriptors of interactions. These descriptors can be used to provide insights for tailoring interactions, as needed for example in drug design.
Quality by Design in the development of hydrophilic interaction liquid chromatography method with gradient elution for the analysis of olanzapine.

PubMed

Tumpa, Anja; Stajić, Ana; Jančić-Stojanović, Biljana; Medenica, Mirjana

2017-02-05

This paper deals with the development of hydrophilic interaction liquid chromatography (HILIC) method with gradient elution, in accordance with Analytical Quality by Design (AQbD) methodology, for the first time. The method is developed for olanzapine and its seven related substances. Following step by step AQbD methodology, firstly as critical process parameters (CPPs) temperature, starting content of aqueous phase and duration of linear gradient are recognized, and as critical quality attributes (CQAs) separation criterion S of critical pairs of substances are investigated. Rechtschaffen design is used for the creation of models that describe the dependence between CPPs and CQAs. The design space that is obtained at the end is used for choosing the optimal conditions (set point). The method is fully validated at the end to verify the adequacy of the chosen optimal conditions and applied to real samples. Copyright © 2016 Elsevier B.V. All rights reserved.
Solving the Schroedinger Equation of Atoms and Molecules without Analytical Integration Based on the Free Iterative-Complement-Interaction Wave Function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nakatsuji, H.; Nakashima, H.; Department of Synthetic Chemistry and Biological Chemistry, Graduate School of Engineering, Kyoto University, Nishikyo-ku, Kyoto 615-8510

2007-12-14

A local Schroedinger equation (LSE) method is proposed for solving the Schroedinger equation (SE) of general atoms and molecules without doing analytic integrations over the complement functions of the free ICI (iterative-complement-interaction) wave functions. Since the free ICI wave function is potentially exact, we can assume a flatness of its local energy. The variational principle is not applicable because the analytic integrations over the free ICI complement functions are very difficult for general atoms and molecules. The LSE method is applied to several 2 to 5 electron atoms and molecules, giving an accuracy of 10{sup -5} Hartree in total energy.more » The potential energy curves of H{sub 2} and LiH molecules are calculated precisely with the free ICI LSE method. The results show the high potentiality of the free ICI LSE method for developing accurate predictive quantum chemistry with the solutions of the SE.« less
An extended micromechanics method for probing interphase properties in polymer nanocomposites [An extended micromechanics method for overlapping geometries with application to polymer nanocomposites

DOE PAGES

Liu, Zeliang; Moore, John A.; Liu, Wing Kam

2016-05-03

Inclusions comprised on filler particles and interphase regions commonly form complex morphologies in polymer nanocomposites. Addressing these morphologies as systems of overlapping simple shapes allows for the study of dilute particles, clustered particles, and interacting interphases all in one general modeling framework. To account for the material properties in these overlapping geometries, weighted-mean and additive overlapping conditions are introduced and the corresponding inclusion-wise integral equations are formulated. An extended micromechanics method based on these overlapping conditions for linear elastic and viscoelastic heterogeneous material is then developed. An important feature of the proposed approach is that the effect of both themore » geometric overlapping (clustered particles) and physical overlapping (interacting interphases) on the effective properties can be distinguished. Lastly, we apply the extended micromechanics method to a viscoelastic polymer nanocomposite with interphase regions, and estimate the properties and thickness of the interphase region based on experimental data for carbon-black filled styrene butadiene rubbers.« less
An extended micromechanics method for probing interphase properties in polymer nanocomposites [An extended micromechanics method for overlapping geometries with application to polymer nanocomposites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Zeliang; Moore, John A.; Liu, Wing Kam

Inclusions comprised on filler particles and interphase regions commonly form complex morphologies in polymer nanocomposites. Addressing these morphologies as systems of overlapping simple shapes allows for the study of dilute particles, clustered particles, and interacting interphases all in one general modeling framework. To account for the material properties in these overlapping geometries, weighted-mean and additive overlapping conditions are introduced and the corresponding inclusion-wise integral equations are formulated. An extended micromechanics method based on these overlapping conditions for linear elastic and viscoelastic heterogeneous material is then developed. An important feature of the proposed approach is that the effect of both themore » geometric overlapping (clustered particles) and physical overlapping (interacting interphases) on the effective properties can be distinguished. Lastly, we apply the extended micromechanics method to a viscoelastic polymer nanocomposite with interphase regions, and estimate the properties and thickness of the interphase region based on experimental data for carbon-black filled styrene butadiene rubbers.« less
Tactile objects based on an amplitude disturbed diffraction pattern method

NASA Astrophysics Data System (ADS)

Liu, Yuan; Nikolovski, Jean-Pierre; Mechbal, Nazih; Hafez, Moustapha; Vergé, Michel

2009-12-01

Tactile sensing is becoming widely used in human-computer interfaces. Recent advances in acoustic approaches demonstrated the possibilities to transform ordinary solid objects into interactive interfaces. This letter proposes a static finger contact localization process using an amplitude disturbed diffraction pattern method. The localization method is based on the following physical phenomenon: a finger contact modifies the energy distribution of acoustic wave in a solid; these variations depend on the wave frequency and the contact position. The presented method first consists of exciting the object with an acoustic signal with plural frequency components. In a second step, a measured acoustic signal is compared with prerecorded values to deduce the contact position. This position is then used for human-machine interaction (e.g., finger tracking on computer screen). The selection of excitation signals is discussed and a frequency choice criterion based on contrast value is proposed. Tests on a sandwich plate (liquid crystal display screen) prove the simplicity and easiness to apply the process in various solids.

Probing New Long-Range Interactions by Isotope Shift Spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berengut, Julian C.; Budker, Dmitry; Delaunay, Cédric

We explore a method to probe new long- and intermediate-range interactions using precision atomic isotope shift spectroscopy. We develop a formalism to interpret linear King plots as bounds on new physics with minimal theory inputs. We focus only on bounding the new physics contributions that can be calculated independently of the standard model nuclear effects. We apply our method to existing Ca + data and project its sensitivity to conjectured new bosons with spin-independent couplings to the electron and the neutron using narrow transitions in other atoms and ions, specifically, Sr and Yb. Future measurements are expected to improve themore » relative precision by 5 orders of magnitude, and they can potentially lead to an unprecedented sensitivity for bosons within the 0.3 to 10 MeV mass range.« less
Nuclear Emulsion Analysis Methods of Locating Neutrino Interactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Erickson, Carolyn Lee

2006-12-01

The Fermilab experiment 872 (DONUT) was the first to directly observe tau neutrinos in the charged current interactionV more » $$\\tau$$+N →$$\\tau$$ +X. The observation was made using a hybrid emulsion-spectrometer detector to identify the signature kink or trident decay of the tau particle. Although nuclear emulsion has the benefit of sub-micron resolution, its use incorporates difficulties such as significant distortions and a high density of data resulting from its continuously active state. Finding events and achieving sub-micron resolution in emulsion requires a multi-pronged strategy of tracking and vertex location to deal with these inherent difficulties. By applying the methods developed in this thesis, event location efficiency can be improved from a value of 58% to 87%.« less
Probing New Long-Range Interactions by Isotope Shift Spectroscopy.

PubMed

Berengut, Julian C; Budker, Dmitry; Delaunay, Cédric; Flambaum, Victor V; Frugiuele, Claudia; Fuchs, Elina; Grojean, Christophe; Harnik, Roni; Ozeri, Roee; Perez, Gilad; Soreq, Yotam

2018-03-02

We explore a method to probe new long- and intermediate-range interactions using precision atomic isotope shift spectroscopy. We develop a formalism to interpret linear King plots as bounds on new physics with minimal theory inputs. We focus only on bounding the new physics contributions that can be calculated independently of the standard model nuclear effects. We apply our method to existing Ca^{+} data and project its sensitivity to conjectured new bosons with spin-independent couplings to the electron and the neutron using narrow transitions in other atoms and ions, specifically, Sr and Yb. Future measurements are expected to improve the relative precision by 5 orders of magnitude, and they can potentially lead to an unprecedented sensitivity for bosons within the 0.3 to 10 MeV mass range.
The influence of the application of personal response systems on the effects of teaching and learning physics at the high school level

NASA Astrophysics Data System (ADS)

Binek, Sławomir; Kimla, Damian; Jarosz, Jerzy

2017-01-01

We report on the effectiveness of using interactive personal response systems in teaching physics in secondary schools. Our research were conducted over the period of 2013-2016 using the system called clickers. The idea is based on a reciprocal interaction allowing one to ask questions and receive immediate responses from all the students simultaneously. Our investigation has confirmed this method to be highly effective and powerful. In particular, students’ ability to acquire knowledge increased with the time spent using clickers. We have successfully applied the system also to entire physics courses. As a result, a positive feedback from students has been observed: not only did they learn more but also the teachers were able to improve their own methods.
Probing New Long-Range Interactions by Isotope Shift Spectroscopy

DOE PAGES

Berengut, Julian C.; Budker, Dmitry; Delaunay, Cédric; ...

2018-02-26

We explore a method to probe new long- and intermediate-range interactions using precision atomic isotope shift spectroscopy. We develop a formalism to interpret linear King plots as bounds on new physics with minimal theory inputs. We focus only on bounding the new physics contributions that can be calculated independently of the standard model nuclear effects. We apply our method to existing Ca + data and project its sensitivity to conjectured new bosons with spin-independent couplings to the electron and the neutron using narrow transitions in other atoms and ions, specifically, Sr and Yb. Future measurements are expected to improve themore » relative precision by 5 orders of magnitude, and they can potentially lead to an unprecedented sensitivity for bosons within the 0.3 to 10 MeV mass range.« less
Double-wavelet approach to study frequency and amplitude modulation in renal autoregulation

NASA Astrophysics Data System (ADS)

Sosnovtseva, O. V.; Pavlov, A. N.; Mosekilde, E.; Holstein-Rathlou, N.-H.; Marsh, D. J.

2004-09-01

Biological time series often display complex oscillations with several interacting rhythmic components. Renal autoregulation, for instance, involves at least two separate mechanisms both of which can produce oscillatory variations in the pressures and flows of the individual nephrons. Using double-wavelet analysis we propose a method to examine how the instantaneous frequency and amplitude of a fast mode is modulated by the presence of a slower mode. Our method is applied both to experimental data from normotensive and hypertensive rats showing different oscillatory patterns and to simulation results obtained from a physiologically based model of the nephron pressure and flow control. We reveal a nonlinear interaction between the two mechanisms that regulate the renal blood flow in the form of frequency and amplitude modulation of the myogenic oscillations.
Unsteady Cascade Aerodynamic Response Using a Multiphysics Simulation Code

NASA Technical Reports Server (NTRS)

Lawrence, C.; Reddy, T. S. R.; Spyropoulos, E.

2000-01-01

The multiphysics code Spectrum(TM) is applied to calculate the unsteady aerodynamic pressures of oscillating cascade of airfoils representing a blade row of a turbomachinery component. Multiphysics simulation is based on a single computational framework for the modeling of multiple interacting physical phenomena, in the present case being between fluids and structures. Interaction constraints are enforced in a fully coupled manner using the augmented-Lagrangian method. The arbitrary Lagrangian-Eulerian method is utilized to account for deformable fluid domains resulting from blade motions. Unsteady pressures are calculated for a cascade designated as the tenth standard, and undergoing plunging and pitching oscillations. The predicted unsteady pressures are compared with those obtained from an unsteady Euler co-de refer-red in the literature. The Spectrum(TM) code predictions showed good correlation for the cases considered.
Exploration of quantum phases transition in the XXZ model with Dzyaloshinskii-Moriya interaction using trance distance discord

NASA Astrophysics Data System (ADS)

Zhang, Ren-jie; Xu, Shuai; Shi, Jia-dong; Ma, Wen-chao; Ye, Liu

2015-11-01

In the paper, we researched the quantum phase transition (QPT) in the anisotropic spin XXZ model by exploiting the quantum renormalization group (QRG) method. The innovation point is that we adopt a new approach called trace distance discord to indicate the quantum correlation of the system. QPT after several iterations of renormalization in current system has been observed. Consequently, it opened the possibility of investigation of QPR in the geometric discord territory. While the anisotropy suppresses the correlation due to favoring of the alignment of spins, the DM interaction restores the spoiled correlation via creation of the quantum fluctuations. We also apply quantum renormalization group method to probe the thermodynamic limit of the model and emerging of nonanalytic behavior of the correlation.
Time-independent lattice Boltzmann method calculation of hydrodynamic interactions between two particles

NASA Astrophysics Data System (ADS)

Ding, E. J.

2015-06-01

The time-independent lattice Boltzmann algorithm (TILBA) is developed to calculate the hydrodynamic interactions between two particles in a Stokes flow. The TILBA is distinguished from the traditional lattice Boltzmann method in that a background matrix (BGM) is generated prior to the calculation. The BGM, once prepared, can be reused for calculations for different scenarios, and the computational cost for each such calculation will be significantly reduced. The advantage of the TILBA is that it is easy to code and can be applied to any particle shape without complicated implementation, and the computational cost is independent of the shape of the particle. The TILBA is validated and shown to be accurate by comparing calculation results obtained from the TILBA to analytical or numerical solutions for certain problems.
Self-interaction correction in multiple scattering theory: application to transition metal oxides

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daene, Markus W; Lueders, Martin; Ernst, Arthur

2009-01-01

We apply to transition metal monoxides the self-interaction corrected (SIC) local spin density (LSD) approximation, implemented locally in the multiple scattering theory within the Korringa-Kohn-Rostoker (KKR) band structure method. The calculated electronic structure and in particular magnetic moments and energy gaps are discussed in reference to the earlier SIC results obtained within the LMTO-ASA band structure method, involving transformations between Bloch and Wannier representations to solve the eigenvalue problem and calculate the SIC charge and potential. Since the KKR can be easily extended to treat disordered alloys, by invoking the coherent potential approximation (CPA), in this paper we compare themore » CPA approach and supercell calculations to study the electronic structure of NiO with cation vacancies.« less
Specific RNA-protein interactions detected with saturation transfer difference NMR.

PubMed

Harris, Kimberly A; Shekhtman, Alexander; Agris, Paul F

2013-08-01

RNA, at the forefront of biochemical research due to its central role in biology, is recognized by proteins through various mechanisms. Analysis of the RNA-protein interface provides insight into the recognition determinants and function. As such, there is a demand for developing new methods to characterize RNA-protein interactions. Saturation transfer difference (STD) NMR can identify binding ligands for proteins in a rather short period of time, with data acquisitions of just a few hours. Two RNA-protein systems involved in RNA modification were studied using STD NMR. The N (6)-threonylcarbamoyltransferase, YrdC, with nucleoside-specific recognition, was shown to bind the anticodon stem-loop of tRNA(Lys)UUU. The points of contact on the RNA were assigned and a binding interface was identified. STD NMR was also applied to the interaction of the archaeal ribosomal protein, L7Ae, with the box C/D K-turn RNA. The distinctiveness of the two RNA-protein interfaces was evident. Both RNAs exhibited strong STD signals indicative of direct contact with the respective protein, but reflected the nature of recognition. Characterization of nucleic acid recognition determinants traditionally involves cost and time prohibitive methods. This approach offers significant insight into interaction interfaces fairly rapidly, and complements existing structural methods.
Refining adverse drug reaction signals by incorporating interaction variables identified using emergent pattern mining.

PubMed

Reps, Jenna M; Aickelin, Uwe; Hubbard, Richard B

2016-02-01

To develop a framework for identifying and incorporating candidate confounding interaction terms into a regularised cox regression analysis to refine adverse drug reaction signals obtained via longitudinal observational data. We considered six drug families that are commonly associated with myocardial infarction in observational healthcare data, but where the causal relationship ground truth is known (adverse drug reaction or not). We applied emergent pattern mining to find itemsets of drugs and medical events that are associated with the development of myocardial infarction. These are the candidate confounding interaction terms. We then implemented a cohort study design using regularised cox regression that incorporated and accounted for the candidate confounding interaction terms. The methodology was able to account for signals generated due to confounding and a cox regression with elastic net regularisation correctly ranking the drug families known to be true adverse drug reactions above those that are not. This was not the case without the inclusion of the candidate confounding interaction terms, where confounding leads to a non-adverse drug reaction being ranked highest. The methodology is efficient, can identify high-order confounding interactions and does not require expert input to specify outcome specific confounders, so it can be applied for any outcome of interest to quickly refine its signals. The proposed method shows excellent potential to overcome some forms of confounding and therefore reduce the false positive rate for signal analysis using longitudinal data. Copyright © 2015 Elsevier Ltd. All rights reserved.
Weak hydrogen bonding interactions influence slip system activity and compaction behavior of pharmaceutical powders.

PubMed

Khomane, Kailas S; Bansal, Arvind K

2013-12-01

Markedly different mechanical behavior of powders of polymorphs, cocrystals, hydrate/anhydrate pairs, or structurally similar molecules has been attributed to the presence of active slip planes system in their crystal structures. Presence of slip planes in the crystal lattice allows easier slip under the applied compaction pressure. This allows greater plastic deformation of the powder and results into increased interparticulate bonding area and greater tensile strength of the compacts. Thus, based on this crystallographic feature, tableting performance of the active pharmaceutical ingredients can be predicted. Recently, we encountered a case where larger numbers of CH···O type interactions across the proposed slip planes hinder the slip and thus resist plastic deformation of the powder under the applied compaction pressure. Hence, attention must be given to these types of interactions while identifying slip planes by visualization method. Generally, slip planes are visualized as flat layers often strengthened by a two-dimensional hydrogen-bonding network within the layers or planes. No hydrogen bonding should exist between these layers to consider them as slip planes. Moreover, one should also check the presence of CH···O type interactions across these planes. Mercury software provides an option for visualization of these weak hydrogen bonding interactions. Hence, caution must be exercised while selecting appropriate solid form based on this crystallographic feature. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association.
Theoretical study of adsorption of nitrogen-containing environmental contaminants on kaolinite surfaces.

PubMed

Scott, Andrea Michalkova; Burns, Elizabeth A; Hill, Frances C

2014-08-01

The adsorption of nitrogen-containing compounds (NCCs) including 2,4,6-trinitrotoluene (TNT), 2,4-dinitrotoluene (DNT), 2,4-dinitroanisole (DNAN), and 3-nitro-1,2,4-triazol-5-one (NTO) on kaolinite surfaces was investigated. The M06-2X and M06-2X-D3 density functionals were applied with the cluster approximation. Several different positions of NCCs relative to the adsorption sites of kaolinite were examined, including NCCs in perpendicular and parallel orientation toward both surface models of kaolinite. The binding between the target molecules and kaolinite surfaces was analyzed and bond energies were calculated applying the atoms in molecules (AIM) method. All NCCs were found to prefer a parallel orientation toward both kaolinite surfaces, and were bound more strongly to the octahedral than to the tetrahedral site. TNT exhibited the strongest interaction with the octahedral surface and DNAN with the tetrahedral surface of kaolinite. Hydrogen bonding was shown to be the dominant non-covalent interaction for NCCs interacting with the octahedral surface of kaolinite with a small stabilizing effect of dispersion interactions. In the case of adsorption on the tetrahedral surface, kaolonite-NCC binding was shown to be governed by the balance between hydrogen bonds and dispersion forces. The presence of water as a solvent leads to a significant decrease in the adsorption strength for all studied NCCs interacting with both kaolinite surfaces.
Depth of interaction decoding of a continuous crystal detector module.

PubMed

Ling, T; Lewellen, T K; Miyaoka, R S

2007-04-21

We present a clustering method to extract the depth of interaction (DOI) information from an 8 mm thick crystal version of our continuous miniature crystal element (cMiCE) small animal PET detector. This clustering method, based on the maximum-likelihood (ML) method, can effectively build look-up tables (LUT) for different DOI regions. Combined with our statistics-based positioning (SBP) method, which uses a LUT searching algorithm based on the ML method and two-dimensional mean-variance LUTs of light responses from each photomultiplier channel with respect to different gamma ray interaction positions, the position of interaction and DOI can be estimated simultaneously. Data simulated using DETECT2000 were used to help validate our approach. An experiment using our cMiCE detector was designed to evaluate the performance. Two and four DOI region clustering were applied to the simulated data. Two DOI regions were used for the experimental data. The misclassification rate for simulated data is about 3.5% for two DOI regions and 10.2% for four DOI regions. For the experimental data, the rate is estimated to be approximately 25%. By using multi-DOI LUTs, we also observed improvement of the detector spatial resolution, especially for the corner region of the crystal. These results show that our ML clustering method is a consistent and reliable way to characterize DOI in a continuous crystal detector without requiring any modifications to the crystal or detector front end electronics. The ability to characterize the depth-dependent light response function from measured data is a major step forward in developing practical detectors with DOI positioning capability.
Efficient implementation of three-dimensional reference interaction site model self-consistent-field method: Application to solvatochromic shift calculations

NASA Astrophysics Data System (ADS)

Minezawa, Noriyuki; Kato, Shigeki

2007-02-01

The authors present an implementation of the three-dimensional reference interaction site model self-consistent-field (3D-RISM-SCF) method. First, they introduce a robust and efficient algorithm for solving the 3D-RISM equation. The algorithm is a hybrid of the Newton-Raphson and Picard methods. The Jacobian matrix is analytically expressed in a computationally useful form. Second, they discuss the solute-solvent electrostatic interaction. For the solute to solvent route, the electrostatic potential (ESP) map on a 3D grid is constructed directly from the electron density. The charge fitting procedure is not required to determine the ESP. For the solvent to solute route, the ESP acting on the solute molecule is derived from the solvent charge distribution obtained by solving the 3D-RISM equation. Matrix elements of the solute-solvent interaction are evaluated by the direct numerical integration. A remarkable reduction in the computational time is observed in both routes. Finally, the authors implement the first derivatives of the free energy with respect to the solute nuclear coordinates. They apply the present method to "solute" water and formaldehyde in aqueous solvent using the simple point charge model, and the results are compared with those from other methods: the six-dimensional molecular Ornstein-Zernike SCF, the one-dimensional site-site RISM-SCF, and the polarizable continuum model. The authors also calculate the solvatochromic shifts of acetone, benzonitrile, and nitrobenzene using the present method and compare them with the experimental and other theoretical results.
Efficient implementation of three-dimensional reference interaction site model self-consistent-field method: application to solvatochromic shift calculations.

PubMed

Minezawa, Noriyuki; Kato, Shigeki

2007-02-07

The authors present an implementation of the three-dimensional reference interaction site model self-consistent-field (3D-RISM-SCF) method. First, they introduce a robust and efficient algorithm for solving the 3D-RISM equation. The algorithm is a hybrid of the Newton-Raphson and Picard methods. The Jacobian matrix is analytically expressed in a computationally useful form. Second, they discuss the solute-solvent electrostatic interaction. For the solute to solvent route, the electrostatic potential (ESP) map on a 3D grid is constructed directly from the electron density. The charge fitting procedure is not required to determine the ESP. For the solvent to solute route, the ESP acting on the solute molecule is derived from the solvent charge distribution obtained by solving the 3D-RISM equation. Matrix elements of the solute-solvent interaction are evaluated by the direct numerical integration. A remarkable reduction in the computational time is observed in both routes. Finally, the authors implement the first derivatives of the free energy with respect to the solute nuclear coordinates. They apply the present method to "solute" water and formaldehyde in aqueous solvent using the simple point charge model, and the results are compared with those from other methods: the six-dimensional molecular Ornstein-Zernike SCF, the one-dimensional site-site RISM-SCF, and the polarizable continuum model. The authors also calculate the solvatochromic shifts of acetone, benzonitrile, and nitrobenzene using the present method and compare them with the experimental and other theoretical results.
A new strategic neurosurgical planning tool for brainstem cavernous malformations using interactive computer graphics with multimodal fusion images.

PubMed

Kin, Taichi; Nakatomi, Hirofumi; Shojima, Masaaki; Tanaka, Minoru; Ino, Kenji; Mori, Harushi; Kunimatsu, Akira; Oyama, Hiroshi; Saito, Nobuhito

2012-07-01

In this study, the authors used preoperative simulation employing 3D computer graphics (interactive computer graphics) to fuse all imaging data for brainstem cavernous malformations. The authors evaluated whether interactive computer graphics or 2D imaging correlated better with the actual operative field, particularly in identifying a developmental venous anomaly (DVA). The study population consisted of 10 patients scheduled for surgical treatment of brainstem cavernous malformations. Data from preoperative imaging (MRI, CT, and 3D rotational angiography) were automatically fused using a normalized mutual information method, and then reconstructed by a hybrid method combining surface rendering and volume rendering methods. With surface rendering, multimodality and multithreshold techniques for 1 tissue were applied. The completed interactive computer graphics were used for simulation of surgical approaches and assumed surgical fields. Preoperative diagnostic rates for a DVA associated with brainstem cavernous malformation were compared between conventional 2D imaging and interactive computer graphics employing receiver operating characteristic (ROC) analysis. The time required for reconstruction of 3D images was 3-6 hours for interactive computer graphics. Observation in interactive mode required approximately 15 minutes. Detailed anatomical information for operative procedures, from the craniotomy to microsurgical operations, could be visualized and simulated three-dimensionally as 1 computer graphic using interactive computer graphics. Virtual surgical views were consistent with actual operative views. This technique was very useful for examining various surgical approaches. Mean (±SEM) area under the ROC curve for rate of DVA diagnosis was significantly better for interactive computer graphics (1.000±0.000) than for 2D imaging (0.766±0.091; p<0.001, Mann-Whitney U-test). The authors report a new method for automatic registration of preoperative imaging data from CT, MRI, and 3D rotational angiography for reconstruction into 1 computer graphic. The diagnostic rate of DVA associated with brainstem cavernous malformation was significantly better using interactive computer graphics than with 2D images. Interactive computer graphics was also useful in helping to plan the surgical access corridor.
Systems and methods for knowledge discovery in spatial data

DOEpatents

Obradovic, Zoran; Fiez, Timothy E.; Vucetic, Slobodan; Lazarevic, Aleksandar; Pokrajac, Dragoljub; Hoskinson, Reed L.

2005-03-08

Systems and methods are provided for knowledge discovery in spatial data as well as to systems and methods for optimizing recipes used in spatial environments such as may be found in precision agriculture. A spatial data analysis and modeling module is provided which allows users to interactively and flexibly analyze and mine spatial data. The spatial data analysis and modeling module applies spatial data mining algorithms through a number of steps. The data loading and generation module obtains or generates spatial data and allows for basic partitioning. The inspection module provides basic statistical analysis. The preprocessing module smoothes and cleans the data and allows for basic manipulation of the data. The partitioning module provides for more advanced data partitioning. The prediction module applies regression and classification algorithms on the spatial data. The integration module enhances prediction methods by combining and integrating models. The recommendation module provides the user with site-specific recommendations as to how to optimize a recipe for a spatial environment such as a fertilizer recipe for an agricultural field.
Relation between scattering and production amplitude--Case of intermediate {sigma}-particle in {pi}{pi}-system--

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ishida, Muneyuki; Ishida, Shin; Ishida, Taku

1998-05-29

The relation between scattering and production amplitudes are investigated, using a simple field theoretical model, from the general viewpoint of unitarity and the applicability of final state interaction (FSI-) theorem. The IA-method and VMW-method, which are applied to our phenomenological analyses [2,3] suggesting the {sigma}-existence, are obtained as the physical state representations of scattering and production amplitudes, respectively. Moreover, the VMW-method is shown to be an effective method to obtain the resonance properties from general production processes, while the conventional analyses based on the 'universality' of {pi}{pi}-scattering amplitude are powerless for this purpose.

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