Structure-based design of combinatorial mutagenesis libraries.

PubMed

Verma, Deeptak; Grigoryan, Gevorg; Bailey-Kellogg, Chris

2015-05-01

The development of protein variants with improved properties (thermostability, binding affinity, catalytic activity, etc.) has greatly benefited from the application of high-throughput screens evaluating large, diverse combinatorial libraries. At the same time, since only a very limited portion of sequence space can be experimentally constructed and tested, an attractive possibility is to use computational protein design to focus libraries on a productive portion of the space. We present a general-purpose method, called "Structure-based Optimization of Combinatorial Mutagenesis" (SOCoM), which can optimize arbitrarily large combinatorial mutagenesis libraries directly based on structural energies of their constituents. SOCoM chooses both positions and substitutions, employing a combinatorial optimization framework based on library-averaged energy potentials in order to avoid explicitly modeling every variant in every possible library. In case study applications to green fluorescent protein, β-lactamase, and lipase A, SOCoM optimizes relatively small, focused libraries whose variants achieve energies comparable to or better than previous library design efforts, as well as larger libraries (previously not designable by structure-based methods) whose variants cover greater diversity while still maintaining substantially better energies than would be achieved by representative random library approaches. By allowing the creation of large-scale combinatorial libraries based on structural calculations, SOCoM promises to increase the scope of applicability of computational protein design and improve the hit rate of discovering beneficial variants. While designs presented here focus on variant stability (predicted by total energy), SOCoM can readily incorporate other structure-based assessments, such as the energy gap between alternative conformational or bound states. © 2015 The Protein Society.

Bifurcation-based approach reveals synergism and optimal combinatorial perturbation.

PubMed

Liu, Yanwei; Li, Shanshan; Liu, Zengrong; Wang, Ruiqi

2016-06-01

Cells accomplish the process of fate decisions and form terminal lineages through a series of binary choices in which cells switch stable states from one branch to another as the interacting strengths of regulatory factors continuously vary. Various combinatorial effects may occur because almost all regulatory processes are managed in a combinatorial fashion. Combinatorial regulation is crucial for cell fate decisions because it may effectively integrate many different signaling pathways to meet the higher regulation demand during cell development. However, whether the contribution of combinatorial regulation to the state transition is better than that of a single one and if so, what the optimal combination strategy is, seem to be significant issue from the point of view of both biology and mathematics. Using the approaches of combinatorial perturbations and bifurcation analysis, we provide a general framework for the quantitative analysis of synergism in molecular networks. Different from the known methods, the bifurcation-based approach depends only on stable state responses to stimuli because the state transition induced by combinatorial perturbations occurs between stable states. More importantly, an optimal combinatorial perturbation strategy can be determined by investigating the relationship between the bifurcation curve of a synergistic perturbation pair and the level set of a specific objective function. The approach is applied to two models, i.e., a theoretical multistable decision model and a biologically realistic CREB model, to show its validity, although the approach holds for a general class of biological systems.

Design of combinatorial libraries for the exploration of virtual hits from fragment space searches with LoFT.

PubMed

Lessel, Uta; Wellenzohn, Bernd; Fischer, J Robert; Rarey, Matthias

2012-02-27

A case study is presented illustrating the design of a focused CDK2 library. The scaffold of the library was detected by a feature trees search in a fragment space based on reactions from combinatorial chemistry. For the design the software LoFT (Library optimizer using Feature Trees) was used. The special feature called FTMatch was applied to restrict the parts of the queries where the reagents are permitted to match. This way a 3D scoring function could be simulated. Results were compared with alternative designs by GOLD docking and ROCS 3D alignments.

Multiobjective evolutionary algorithm with many tables for purely ab initio protein structure prediction.

PubMed

Brasil, Christiane Regina Soares; Delbem, Alexandre Claudio Botazzo; da Silva, Fernando Luís Barroso

2013-07-30

This article focuses on the development of an approach for ab initio protein structure prediction (PSP) without using any earlier knowledge from similar protein structures, as fragment-based statistics or inference of secondary structures. Such an approach is called purely ab initio prediction. The article shows that well-designed multiobjective evolutionary algorithms can predict relevant protein structures in a purely ab initio way. One challenge for purely ab initio PSP is the prediction of structures with β-sheets. To work with such proteins, this research has also developed procedures to efficiently estimate hydrogen bond and solvation contribution energies. Considering van der Waals, electrostatic, hydrogen bond, and solvation contribution energies, the PSP is a problem with four energetic terms to be minimized. Each interaction energy term can be considered an objective of an optimization method. Combinatorial problems with four objectives have been considered too complex for the available multiobjective optimization (MOO) methods. The proposed approach, called "Multiobjective evolutionary algorithms with many tables" (MEAMT), can efficiently deal with four objectives through the combination thereof, performing a more adequate sampling of the objective space. Therefore, this method can better map the promising regions in this space, predicting structures in a purely ab initio way. In other words, MEAMT is an efficient optimization method for MOO, which explores simultaneously the search space as well as the objective space. MEAMT can predict structures with one or two domains with RMSDs comparable to values obtained by recently developed ab initio methods (GAPFCG , I-PAES, and Quark) that use different levels of earlier knowledge. Copyright © 2013 Wiley Periodicals, Inc.

TARCMO: Theory and Algorithms for Robust, Combinatorial, Multicriteria Optimization

DTIC Science & Technology

2016-11-28

objective 9 4.6 On The Recoverable Robust Traveling Salesman Problem . . . . . 11 4.7 A Bicriteria Approach to Robust Optimization...be found. 4.6 On The Recoverable Robust Traveling Salesman Problem The traveling salesman problem (TSP) is a well-known combinatorial optimiza- tion...procedure for the robust traveling salesman problem . While this iterative algorithms results in an optimal solution to the robust TSP, computation

Segmental structure in banded mongoose calls.

PubMed

Fitch, W Tecumseh

2012-12-03

In complex animal vocalizations, such as bird or whale song, a great variety of songs can be produced via rearrangements of a smaller set of 'syllables', known as 'phonological syntax' or 'phonocoding' However, food or alarm calls, which function as referential signals, were previously thought to lack such combinatorial structure. A new study of calls in the banded mongoose Mungos mungo provides the first evidence of phonocoding at the level of single calls. The first portion of the call provides cues to the identity of the caller, and the second part encodes its current activity. This provides the first example known in animals of something akin to the consonants and vowels of human speech.

The construction of combinatorial manifolds with prescribed sets of links of vertices

NASA Astrophysics Data System (ADS)

Gaifullin, A. A.

2008-10-01

To every oriented closed combinatorial manifold we assign the set (with repetitions) of isomorphism classes of links of its vertices. The resulting transformation \\mathcal{L} is the main object of study in this paper. We pose an inversion problem for \\mathcal{L} and show that this problem is closely related to Steenrod's problem on the realization of cycles and to the Rokhlin-Schwartz-Thom construction of combinatorial Pontryagin classes. We obtain a necessary condition for a set of isomorphism classes of combinatorial spheres to belong to the image of \\mathcal{L}. (Sets satisfying this condition are said to be balanced.) We give an explicit construction showing that every balanced set of isomorphism classes of combinatorial spheres falls into the image of \\mathcal{L} after passing to a multiple set and adding several pairs of the form (Z,-Z), where -Z is the sphere Z with the orientation reversed. Given any singular simplicial cycle \\xi of a space X, this construction enables us to find explicitly a combinatorial manifold M and a map \\varphi\\colon M\\to X such that \\varphi_* \\lbrack M \\rbrack =r[\\xi] for some positive integer r. The construction is based on resolving singularities of \\xi. We give applications of the main construction to cobordisms of manifolds with singularities and cobordisms of simple cells. In particular, we prove that every rational additive invariant of cobordisms of manifolds with singularities admits a local formula. Another application is the construction of explicit (though inefficient) local combinatorial formulae for polynomials in the rational Pontryagin classes of combinatorial manifolds.

Balancing focused combinatorial libraries based on multiple GPCR ligands

NASA Astrophysics Data System (ADS)

Soltanshahi, Farhad; Mansley, Tamsin E.; Choi, Sun; Clark, Robert D.

2006-08-01

G-Protein coupled receptors (GPCRs) are important targets for drug discovery, and combinatorial chemistry is an important tool for pharmaceutical development. The absence of detailed structural information, however, limits the kinds of combinatorial design techniques that can be applied to GPCR targets. This is particularly problematic given the current emphasis on focused combinatorial libraries. By linking an incremental construction method (OptDesign) to the very fast shape-matching capability of ChemSpace, we have created an efficient method for designing targeted sublibraries that are topomerically similar to known actives. Multi-objective scoring allows consideration of multiple queries (actives) simultaneously. This can lead to a distribution of products skewed towards one particular query structure, however, particularly when the ligands of interest are quite dissimilar to one another. A novel pivoting technique is described which makes it possible to generate promising designs even under those circumstances. The approach is illustrated by application to some serotonergic agonists and chemokine antagonists.

Combinatorial clustering and Its Application to 3D Polygonal Traffic Sign Reconstruction From Multiple Images

NASA Astrophysics Data System (ADS)

Vallet, B.; Soheilian, B.; Brédif, M.

2014-08-01

The 3D reconstruction of similar 3D objects detected in 2D faces a major issue when it comes to grouping the 2D detections into clusters to be used to reconstruct the individual 3D objects. Simple clustering heuristics fail as soon as similar objects are close. This paper formulates a framework to use the geometric quality of the reconstruction as a hint to do a proper clustering. We present a methodology to solve the resulting combinatorial optimization problem with some simplifications and approximations in order to make it tractable. The proposed method is applied to the reconstruction of 3D traffic signs from their 2D detections to demonstrate its capacity to solve ambiguities.

Segmental structure in banded mongoose calls

PubMed Central

2012-01-01

In complex animal vocalizations, such as bird or whale song, a great variety of songs can be produced via rearrangements of a smaller set of 'syllables', known as 'phonological syntax' or 'phonocoding' However, food or alarm calls, which function as referential signals, were previously thought to lack such combinatorial structure. A new study of calls in the banded mongoose Mungos mungo provides the first evidence of phonocoding at the level of single calls. The first portion of the call provides cues to the identity of the caller, and the second part encodes its current activity. This provides the first example known in animals of something akin to the consonants and vowels of human speech. See research article http://www.biomedcentral.com/1741-7007/10/97 PMID:23206277

Staircase tableaux, the asymmetric exclusion process, and Askey-Wilson polynomials

PubMed Central

Corteel, Sylvie; Williams, Lauren K.

2010-01-01

We introduce some combinatorial objects called staircase tableaux, which have cardinality 4nn !, and connect them to both the asymmetric exclusion process (ASEP) and Askey-Wilson polynomials. The ASEP is a model from statistical mechanics introduced in the late 1960s, which describes a system of interacting particles hopping left and right on a one-dimensional lattice of n sites with open boundaries. It has been cited as a model for traffic flow and translation in protein synthesis. In its most general form, particles may enter and exit at the left with probabilities α and γ, and they may exit and enter at the right with probabilities β and δ. In the bulk, the probability of hopping left is q times the probability of hopping right. Our first result is a formula for the stationary distribution of the ASEP with all parameters general, in terms of staircase tableaux. Our second result is a formula for the moments of (the weight function of) Askey-Wilson polynomials, also in terms of staircase tableaux. Since the 1980s there has been a great deal of work giving combinatorial formulas for moments of classical orthogonal polynomials (e.g. Hermite, Charlier, Laguerre); among these polynomials, the Askey-Wilson polynomials are the most important, because they are at the top of the hierarchy of classical orthogonal polynomials. PMID:20348417

Staircase tableaux, the asymmetric exclusion process, and Askey-Wilson polynomials.

PubMed

Corteel, Sylvie; Williams, Lauren K

2010-04-13

We introduce some combinatorial objects called staircase tableaux, which have cardinality 4(n)n!, and connect them to both the asymmetric exclusion process (ASEP) and Askey-Wilson polynomials. The ASEP is a model from statistical mechanics introduced in the late 1960s, which describes a system of interacting particles hopping left and right on a one-dimensional lattice of n sites with open boundaries. It has been cited as a model for traffic flow and translation in protein synthesis. In its most general form, particles may enter and exit at the left with probabilities alpha and gamma, and they may exit and enter at the right with probabilities beta and delta. In the bulk, the probability of hopping left is q times the probability of hopping right. Our first result is a formula for the stationary distribution of the ASEP with all parameters general, in terms of staircase tableaux. Our second result is a formula for the moments of (the weight function of) Askey-Wilson polynomials, also in terms of staircase tableaux. Since the 1980s there has been a great deal of work giving combinatorial formulas for moments of classical orthogonal polynomials (e.g. Hermite, Charlier, Laguerre); among these polynomials, the Askey-Wilson polynomials are the most important, because they are at the top of the hierarchy of classical orthogonal polynomials.

Sequence-independent construction of ordered combinatorial libraries with predefined crossover points.

PubMed

Jézéquel, Laetitia; Loeper, Jacqueline; Pompon, Denis

2008-11-01

Combinatorial libraries coding for mosaic enzymes with predefined crossover points constitute useful tools to address and model structure-function relationships and for functional optimization of enzymes based on multivariate statistics. The presented method, called sequence-independent generation of a chimera-ordered library (SIGNAL), allows easy shuffling of any predefined amino acid segment between two or more proteins. This method is particularly well adapted to the exchange of protein structural modules. The procedure could also be well suited to generate ordered combinatorial libraries independent of sequence similarities in a robotized manner. Sequence segments to be recombined are first extracted by PCR from a single-stranded template coding for an enzyme of interest using a biotin-avidin-based method. This technique allows the reduction of parental template contamination in the final library. Specific PCR primers allow amplification of two complementary mosaic DNA fragments, overlapping in the region to be exchanged. Fragments are finally reassembled using a fusion PCR. The process is illustrated via the construction of a set of mosaic CYP2B enzymes using this highly modular approach.

Searching Remotely Sensed Images for Meaningful Nested Gestalten

NASA Astrophysics Data System (ADS)

Michaelsen, E.; Muench, D.; Arens, M.

2016-06-01

Even non-expert human observers sometimes still outperform automatic extraction of man-made objects from remotely sensed data. We conjecture that some of this remarkable capability can be explained by Gestalt mechanisms. Gestalt algebra gives a mathematical structure capturing such part-aggregate relations and the laws to form an aggregate called Gestalt. Primitive Gestalten are obtained from an input image and the space of all possible Gestalt algebra terms is searched for well-assessed instances. This can be a very challenging combinatorial effort. The contribution at hand gives some tools and structures unfolding a finite and comparably small subset of the possible combinations. Yet, the intended Gestalten still are contained and found with high probability and moderate efforts. Experiments are made with images obtained from a virtual globe system, and use the SIFT method for extraction of the primitive Gestalten. Comparison is made with manually extracted ground-truth Gestalten salient to human observers.

Crossover versus mutation: a comparative analysis of the evolutionary strategy of genetic algorithms applied to combinatorial optimization problems.

PubMed

Osaba, E; Carballedo, R; Diaz, F; Onieva, E; de la Iglesia, I; Perallos, A

2014-01-01

Since their first formulation, genetic algorithms (GAs) have been one of the most widely used techniques to solve combinatorial optimization problems. The basic structure of the GAs is known by the scientific community, and thanks to their easy application and good performance, GAs are the focus of a lot of research works annually. Although throughout history there have been many studies analyzing various concepts of GAs, in the literature there are few studies that analyze objectively the influence of using blind crossover operators for combinatorial optimization problems. For this reason, in this paper a deep study on the influence of using them is conducted. The study is based on a comparison of nine techniques applied to four well-known combinatorial optimization problems. Six of the techniques are GAs with different configurations, and the remaining three are evolutionary algorithms that focus exclusively on the mutation process. Finally, to perform a reliable comparison of these results, a statistical study of them is made, performing the normal distribution z-test.

Crossover versus Mutation: A Comparative Analysis of the Evolutionary Strategy of Genetic Algorithms Applied to Combinatorial Optimization Problems

PubMed Central

Osaba, E.; Carballedo, R.; Diaz, F.; Onieva, E.; de la Iglesia, I.; Perallos, A.

2014-01-01

Since their first formulation, genetic algorithms (GAs) have been one of the most widely used techniques to solve combinatorial optimization problems. The basic structure of the GAs is known by the scientific community, and thanks to their easy application and good performance, GAs are the focus of a lot of research works annually. Although throughout history there have been many studies analyzing various concepts of GAs, in the literature there are few studies that analyze objectively the influence of using blind crossover operators for combinatorial optimization problems. For this reason, in this paper a deep study on the influence of using them is conducted. The study is based on a comparison of nine techniques applied to four well-known combinatorial optimization problems. Six of the techniques are GAs with different configurations, and the remaining three are evolutionary algorithms that focus exclusively on the mutation process. Finally, to perform a reliable comparison of these results, a statistical study of them is made, performing the normal distribution z-test. PMID:25165731

When Gravity Fails: Local Search Topology

NASA Technical Reports Server (NTRS)

Frank, Jeremy; Cheeseman, Peter; Stutz, John; Lau, Sonie (Technical Monitor)

1997-01-01

Local search algorithms for combinatorial search problems frequently encounter a sequence of states in which it is impossible to improve the value of the objective function; moves through these regions, called {\\em plateau moves), dominate the time spent in local search. We analyze and characterize {\\em plateaus) for three different classes of randomly generated Boolean Satisfiability problems. We identify several interesting features of plateaus that impact the performance of local search algorithms. We show that local minima tend to be small but occasionally may be very large. We also show that local minima can be escaped without unsatisfying a large number of clauses, but that systematically searching for an escape route may be computationally expensive if the local minimum is large. We show that plateaus with exits, called benches, tend to be much larger than minima, and that some benches have very few exit states which local search can use to escape. We show that the solutions (i.e. global minima) of randomly generated problem instances form clusters, which behave similarly to local minima. We revisit several enhancements of local search algorithms and explain their performance in light of our results. Finally we discuss strategies for creating the next generation of local search algorithms.

Multiobjective optimization of combinatorial libraries.

PubMed

Agrafiotis, D K

2002-01-01

Combinatorial chemistry and high-throughput screening have caused a fundamental shift in the way chemists contemplate experiments. Designing a combinatorial library is a controversial art that involves a heterogeneous mix of chemistry, mathematics, economics, experience, and intuition. Although there seems to be little agreement as to what constitutes an ideal library, one thing is certain: only one property or measure seldom defines the quality of the design. In most real-world applications, a good experiment requires the simultaneous optimization of several, often conflicting, design objectives, some of which may be vague and uncertain. In this paper, we discuss a class of algorithms for subset selection rooted in the principles of multiobjective optimization. Our approach is to employ an objective function that encodes all of the desired selection criteria, and then use a simulated annealing or evolutionary approach to identify the optimal (or a nearly optimal) subset from among the vast number of possibilities. Many design criteria can be accommodated, including diversity, similarity to known actives, predicted activity and/or selectivity determined by quantitative structure-activity relationship (QSAR) models or receptor binding models, enforcement of certain property distributions, reagent cost and availability, and many others. The method is robust, convergent, and extensible, offers the user full control over the relative significance of the various objectives in the final design, and permits the simultaneous selection of compounds from multiple libraries in full- or sparse-array format.

Combinatorial Multiobjective Optimization Using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Crossley, William A.; Martin. Eric T.

2002-01-01

The research proposed in this document investigated multiobjective optimization approaches based upon the Genetic Algorithm (GA). Several versions of the GA have been adopted for multiobjective design, but, prior to this research, there had not been significant comparisons of the most popular strategies. The research effort first generalized the two-branch tournament genetic algorithm in to an N-branch genetic algorithm, then the N-branch GA was compared with a version of the popular Multi-Objective Genetic Algorithm (MOGA). Because the genetic algorithm is well suited to combinatorial (mixed discrete / continuous) optimization problems, the GA can be used in the conceptual phase of design to combine selection (discrete variable) and sizing (continuous variable) tasks. Using a multiobjective formulation for the design of a 50-passenger aircraft to meet the competing objectives of minimizing takeoff gross weight and minimizing trip time, the GA generated a range of tradeoff designs that illustrate which aircraft features change from a low-weight, slow trip-time aircraft design to a heavy-weight, short trip-time aircraft design. Given the objective formulation and analysis methods used, the results of this study identify where turboprop-powered aircraft and turbofan-powered aircraft become more desirable for the 50 seat passenger application. This aircraft design application also begins to suggest how a combinatorial multiobjective optimization technique could be used to assist in the design of morphing aircraft.

Combinatorial structure of genome rearrangements scenarios.

PubMed

Ouangraoua, Aïda; Bergeron, Anne

2010-09-01

In genome rearrangement theory, one of the elusive questions raised in recent years is the enumeration of rearrangement scenarios between two genomes. This problem is related to the uniform generation of rearrangement scenarios and the derivation of tests of statistical significance of the properties of these scenarios. Here we give an exact formula for the number of double-cut-and-join (DCJ) rearrangement scenarios between two genomes. We also construct effective bijections between the set of scenarios that sort a component as well studied combinatorial objects such as parking functions, labeled trees, and prüfer codes.

OPTIMIZING THROUGH CO-EVOLUTIONARY AVALANCHES

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

S. BOETTCHER; A. PERCUS

2000-08-01

We explore a new general-purpose heuristic for finding high-quality solutions to hard optimization problems. The method, called extremal optimization, is inspired by ''self-organized critically,'' a concept introduced to describe emergent complexity in many physical systems. In contrast to Genetic Algorithms which operate on an entire ''gene-pool'' of possible solutions, extremal optimization successively replaces extremely undesirable elements of a sub-optimal solution with new, random ones. Large fluctuations, called ''avalanches,'' ensue that efficiently explore many local optima. Drawing upon models used to simulate far-from-equilibrium dynamics, extremal optimization complements approximation methods inspired by equilibrium statistical physics, such as simulated annealing. With only onemore » adjustable parameter, its performance has proved competitive with more elaborate methods, especially near phase transitions. Those phase transitions are found in the parameter space of most optimization problems, and have recently been conjectured to be the origin of some of the hardest instances in computational complexity. We will demonstrate how extremal optimization can be implemented for a variety of combinatorial optimization problems. We believe that extremal optimization will be a useful tool in the investigation of phase transitions in combinatorial optimization problems, hence valuable in elucidating the origin of computational complexity.« less

The "p"-Median Model as a Tool for Clustering Psychological Data

ERIC Educational Resources Information Center

Kohn, Hans-Friedrich; Steinley, Douglas; Brusco, Michael J.

2010-01-01

The "p"-median clustering model represents a combinatorial approach to partition data sets into disjoint, nonhierarchical groups. Object classes are constructed around "exemplars", that is, manifest objects in the data set, with the remaining instances assigned to their closest cluster centers. Effective, state-of-the-art implementations of…

Template-based combinatorial enumeration of virtual compound libraries for lipids

PubMed Central

2012-01-01

A variety of software packages are available for the combinatorial enumeration of virtual libraries for small molecules, starting from specifications of core scaffolds with attachments points and lists of R-groups as SMILES or SD files. Although SD files include atomic coordinates for core scaffolds and R-groups, it is not possible to control 2-dimensional (2D) layout of the enumerated structures generated for virtual compound libraries because different packages generate different 2D representations for the same structure. We have developed a software package called LipidMapsTools for the template-based combinatorial enumeration of virtual compound libraries for lipids. Virtual libraries are enumerated for the specified lipid abbreviations using matching lists of pre-defined templates and chain abbreviations, instead of core scaffolds and lists of R-groups provided by the user. 2D structures of the enumerated lipids are drawn in a specific and consistent fashion adhering to the framework for representing lipid structures proposed by the LIPID MAPS consortium. LipidMapsTools is lightweight, relatively fast and contains no external dependencies. It is an open source package and freely available under the terms of the modified BSD license. PMID:23006594

Template-based combinatorial enumeration of virtual compound libraries for lipids.

PubMed

Sud, Manish; Fahy, Eoin; Subramaniam, Shankar

2012-09-25

A variety of software packages are available for the combinatorial enumeration of virtual libraries for small molecules, starting from specifications of core scaffolds with attachments points and lists of R-groups as SMILES or SD files. Although SD files include atomic coordinates for core scaffolds and R-groups, it is not possible to control 2-dimensional (2D) layout of the enumerated structures generated for virtual compound libraries because different packages generate different 2D representations for the same structure. We have developed a software package called LipidMapsTools for the template-based combinatorial enumeration of virtual compound libraries for lipids. Virtual libraries are enumerated for the specified lipid abbreviations using matching lists of pre-defined templates and chain abbreviations, instead of core scaffolds and lists of R-groups provided by the user. 2D structures of the enumerated lipids are drawn in a specific and consistent fashion adhering to the framework for representing lipid structures proposed by the LIPID MAPS consortium. LipidMapsTools is lightweight, relatively fast and contains no external dependencies. It is an open source package and freely available under the terms of the modified BSD license.

Combinatorial events of insertion sequences and ICE in Gram-negative bacteria.

PubMed

Toleman, Mark A; Walsh, Timothy R

2011-09-01

The emergence of antibiotic and antimicrobial resistance in Gram-negative bacteria is incremental and linked to genetic elements that function in a so-called 'one-ended transposition' manner, including ISEcp1, ISCR elements and Tn3-like transposons. The power of these elements lies in their inability to consistently recognize one of their own terminal sequences, while recognizing more genetically distant surrogate sequences. This has the effect of mobilizing the DNA sequence found adjacent to their initial location. In general, resistance in Gram-negatives is closely linked to a few one-off events. These include the capture of the class 1 integron by a Tn5090-like transposon; the formation of the 3' conserved segment (3'-CS); and the fusion of the ISCR1 element to the 3'-CS. The structures formed by these rare events have been massively amplified and disseminated in Gram-negative bacteria, but hitherto, are rarely found in Gram-positives. Such events dominate current resistance gene acquisition and are instrumental in the construction of large resistance gene islands on chromosomes and plasmids. Similar combinatorial events appear to have occurred between conjugative plasmids and phages constructing hybrid elements called integrative and conjugative elements or conjugative transposons. These elements are beginning to be closely linked to some of the more powerful resistance mechanisms such as the extended spectrum β-lactamases, metallo- and AmpC type β-lactamases. Antibiotic resistance in Gram-negative bacteria is dominated by unusual combinatorial mistakes of Insertion sequences and gene fusions which have been selected and amplified by antibiotic pressure enabling the formation of extended resistance islands. © 2011 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

Asymmetry of Neuronal Combinatorial Codes Arises from Minimizing Synaptic Weight Change.

PubMed

Leibold, Christian; Monsalve-Mercado, Mauro M

2016-08-01

Synaptic change is a costly resource, particularly for brain structures that have a high demand of synaptic plasticity. For example, building memories of object positions requires efficient use of plasticity resources since objects can easily change their location in space and yet we can memorize object locations. But how should a neural circuit ideally be set up to integrate two input streams (object location and identity) in case the overall synaptic changes should be minimized during ongoing learning? This letter provides a theoretical framework on how the two input pathways should ideally be specified. Generally the model predicts that the information-rich pathway should be plastic and encoded sparsely, whereas the pathway conveying less information should be encoded densely and undergo learning only if a neuronal representation of a novel object has to be established. As an example, we consider hippocampal area CA1, which combines place and object information. The model thereby provides a normative account of hippocampal rate remapping, that is, modulations of place field activity by changes of local cues. It may as well be applicable to other brain areas (such as neocortical layer V) that learn combinatorial codes from multiple input streams.

Combinatorial pulse position modulation for power-efficient free-space laser communications

NASA Technical Reports Server (NTRS)

Budinger, James M.; Vanderaar, M.; Wagner, P.; Bibyk, Steven

1993-01-01

A new modulation technique called combinatorial pulse position modulation (CPPM) is presented as a power-efficient alternative to quaternary pulse position modulation (QPPM) for direct-detection, free-space laser communications. The special case of 16C4PPM is compared to QPPM in terms of data throughput and bit error rate (BER) performance for similar laser power and pulse duty cycle requirements. The increased throughput from CPPM enables the use of forward error corrective (FEC) encoding for a net decrease in the amount of laser power required for a given data throughput compared to uncoded QPPM. A specific, practical case of coded CPPM is shown to reduce the amount of power required to transmit and receive a given data sequence by at least 4.7 dB. Hardware techniques for maximum likelihood detection and symbol timing recovery are presented.

PMD compensation in fiber-optic communication systems with direct detection using LDPC-coded OFDM.

PubMed

Djordjevic, Ivan B

2007-04-02

The possibility of polarization-mode dispersion (PMD) compensation in fiber-optic communication systems with direct detection using a simple channel estimation technique and low-density parity-check (LDPC)-coded orthogonal frequency division multiplexing (OFDM) is demonstrated. It is shown that even for differential group delay (DGD) of 4/BW (BW is the OFDM signal bandwidth), the degradation due to the first-order PMD can be completely compensated for. Two classes of LDPC codes designed based on two different combinatorial objects (difference systems and product of combinatorial designs) suitable for use in PMD compensation are introduced.

Fuel management optimization using genetic algorithms and code independence

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

DeChaine, M.D.; Feltus, M.A.

1994-12-31

Fuel management optimization is a hard problem for traditional optimization techniques. Loading pattern optimization is a large combinatorial problem without analytical derivative information. Therefore, methods designed for continuous functions, such as linear programming, do not always work well. Genetic algorithms (GAs) address these problems and, therefore, appear ideal for fuel management optimization. They do not require derivative information and work well with combinatorial. functions. The GAs are a stochastic method based on concepts from biological genetics. They take a group of candidate solutions, called the population, and use selection, crossover, and mutation operators to create the next generation of bettermore » solutions. The selection operator is a {open_quotes}survival-of-the-fittest{close_quotes} operation and chooses the solutions for the next generation. The crossover operator is analogous to biological mating, where children inherit a mixture of traits from their parents, and the mutation operator makes small random changes to the solutions.« less

Statistical significance of combinatorial regulations

PubMed Central

Terada, Aika; Okada-Hatakeyama, Mariko; Tsuda, Koji; Sese, Jun

2013-01-01

More than three transcription factors often work together to enable cells to respond to various signals. The detection of combinatorial regulation by multiple transcription factors, however, is not only computationally nontrivial but also extremely unlikely because of multiple testing correction. The exponential growth in the number of tests forces us to set a strict limit on the maximum arity. Here, we propose an efficient branch-and-bound algorithm called the “limitless arity multiple-testing procedure” (LAMP) to count the exact number of testable combinations and calibrate the Bonferroni factor to the smallest possible value. LAMP lists significant combinations without any limit, whereas the family-wise error rate is rigorously controlled under the threshold. In the human breast cancer transcriptome, LAMP discovered statistically significant combinations of as many as eight binding motifs. This method may contribute to uncover pathways regulated in a coordinated fashion and find hidden associations in heterogeneous data. PMID:23882073

Using Synchronous Boolean Networks to Model Several Phenomena of Collective Behavior

PubMed Central

Kochemazov, Stepan; Semenov, Alexander

2014-01-01

In this paper, we propose an approach for modeling and analysis of a number of phenomena of collective behavior. By collectives we mean multi-agent systems that transition from one state to another at discrete moments of time. The behavior of a member of a collective (agent) is called conforming if the opinion of this agent at current time moment conforms to the opinion of some other agents at the previous time moment. We presume that at each moment of time every agent makes a decision by choosing from the set (where 1-decision corresponds to action and 0-decision corresponds to inaction). In our approach we model collective behavior with synchronous Boolean networks. We presume that in a network there can be agents that act at every moment of time. Such agents are called instigators. Also there can be agents that never act. Such agents are called loyalists. Agents that are neither instigators nor loyalists are called simple agents. We study two combinatorial problems. The first problem is to find a disposition of instigators that in several time moments transforms a network from a state where the majority of simple agents are inactive to a state with the majority of active agents. The second problem is to find a disposition of loyalists that returns the network to a state with the majority of inactive agents. Similar problems are studied for networks in which simple agents demonstrate the contrary to conforming behavior that we call anticonforming. We obtained several theoretical results regarding the behavior of collectives of agents with conforming or anticonforming behavior. In computational experiments we solved the described problems for randomly generated networks with several hundred vertices. We reduced corresponding combinatorial problems to the Boolean satisfiability problem (SAT) and used modern SAT solvers to solve the instances obtained. PMID:25526612

Decoding the genome with an integrative analysis tool: combinatorial CRM Decoder.

PubMed

Kang, Keunsoo; Kim, Joomyeong; Chung, Jae Hoon; Lee, Daeyoup

2011-09-01

The identification of genome-wide cis-regulatory modules (CRMs) and characterization of their associated epigenetic features are fundamental steps toward the understanding of gene regulatory networks. Although integrative analysis of available genome-wide information can provide new biological insights, the lack of novel methodologies has become a major bottleneck. Here, we present a comprehensive analysis tool called combinatorial CRM decoder (CCD), which utilizes the publicly available information to identify and characterize genome-wide CRMs in a species of interest. CCD first defines a set of the epigenetic features which is significantly associated with a set of known CRMs as a code called 'trace code', and subsequently uses the trace code to pinpoint putative CRMs throughout the genome. Using 61 genome-wide data sets obtained from 17 independent mouse studies, CCD successfully catalogued ∼12 600 CRMs (five distinct classes) including polycomb repressive complex 2 target sites as well as imprinting control regions. Interestingly, we discovered that ∼4% of the identified CRMs belong to at least two different classes named 'multi-functional CRM', suggesting their functional importance for regulating spatiotemporal gene expression. From these examples, we show that CCD can be applied to any potential genome-wide datasets and therefore will shed light on unveiling genome-wide CRMs in various species.

Construction of a combinatorial pipeline using two somatic variant  calling  methods  for whole exome sequence data of gastric cancer.

PubMed

Kohmoto, Tomohiro; Masuda, Kiyoshi; Naruto, Takuya; Tange, Shoichiro; Shoda, Katsutoshi; Hamada, Junichi; Saito, Masako; Ichikawa, Daisuke; Tajima, Atsushi; Otsuji, Eigo; Imoto, Issei

2017-01-01

High-throughput next-generation sequencing is a powerful tool to identify the genotypic landscapes of somatic variants and therapeutic targets in various cancers including gastric cancer, forming the basis for personalized medicine in the clinical setting. Although the advent of many computational algorithms leads to higher accuracy in somatic variant calling, no standard method exists due to the limitations of each method. Here, we constructed a new pipeline. We combined two different somatic variant callers with different algorithms, Strelka and VarScan 2, and evaluated performance using whole exome sequencing data obtained from 19 Japanese cases with gastric cancer (GC); then, we characterized these tumors based on identified driver molecular alterations. More single nucleotide variants (SNVs) and small insertions/deletions were detected by Strelka and VarScan 2, respectively. SNVs detected by both tools showed higher accuracy for estimating somatic variants compared with those detected by only one of the two tools and accurately showed the mutation signature and mutations of driver genes reported for GC. Our combinatorial pipeline may have an advantage in detection of somatic mutations in GC and may be useful for further genomic characterization of Japanese patients with GC to improve the efficacy of GC treatments. J. Med. Invest. 64: 233-240, August, 2017.

Energy Landscapes for the Self-Assembly of Supramolecular Polyhedra

NASA Astrophysics Data System (ADS)

Russell, Emily R.; Menon, Govind

2016-06-01

We develop a mathematical model for the energy landscape of polyhedral supramolecular cages recently synthesized by self-assembly (Sun et al. in Science 328:1144-1147, 2010). Our model includes two essential features of the experiment: (1) geometry of the organic ligands and metallic ions; and (2) combinatorics. The molecular geometry is used to introduce an energy that favors square-planar vertices (modeling {Pd}^{2+} ions) and bent edges with one of two preferred opening angles (modeling boomerang-shaped ligands of two types). The combinatorics of the model involve two-colorings of edges of polyhedra with four-valent vertices. The set of such two-colorings, quotiented by the octahedral symmetry group, has a natural graph structure and is called the combinatorial configuration space. The energy landscape of our model is the energy of each state in the combinatorial configuration space. The challenge in the computation of the energy landscape is a combinatorial explosion in the number of two-colorings of edges. We describe sampling methods based on the symmetries of the configurations and connectivity of the configuration graph. When the two preferred opening angles encompass the geometrically ideal angle, the energy landscape exhibits a very low-energy minimum for the most symmetric configuration at equal mixing of the two angles, even when the average opening angle does not match the ideal angle.

Focusing on the golden ball metaheuristic: an extended study on a wider set of problems.

PubMed

Osaba, E; Diaz, F; Carballedo, R; Onieva, E; Perallos, A

2014-01-01

Nowadays, the development of new metaheuristics for solving optimization problems is a topic of interest in the scientific community. In the literature, a large number of techniques of this kind can be found. Anyway, there are many recently proposed techniques, such as the artificial bee colony and imperialist competitive algorithm. This paper is focused on one recently published technique, the one called Golden Ball (GB). The GB is a multiple-population metaheuristic based on soccer concepts. Although it was designed to solve combinatorial optimization problems, until now, it has only been tested with two simple routing problems: the traveling salesman problem and the capacitated vehicle routing problem. In this paper, the GB is applied to four different combinatorial optimization problems. Two of them are routing problems, which are more complex than the previously used ones: the asymmetric traveling salesman problem and the vehicle routing problem with backhauls. Additionally, one constraint satisfaction problem (the n-queen problem) and one combinatorial design problem (the one-dimensional bin packing problem) have also been used. The outcomes obtained by GB are compared with the ones got by two different genetic algorithms and two distributed genetic algorithms. Additionally, two statistical tests are conducted to compare these results.

Focusing on the Golden Ball Metaheuristic: An Extended Study on a Wider Set of Problems

PubMed Central

Osaba, E.; Diaz, F.; Carballedo, R.; Onieva, E.; Perallos, A.

2014-01-01

Nowadays, the development of new metaheuristics for solving optimization problems is a topic of interest in the scientific community. In the literature, a large number of techniques of this kind can be found. Anyway, there are many recently proposed techniques, such as the artificial bee colony and imperialist competitive algorithm. This paper is focused on one recently published technique, the one called Golden Ball (GB). The GB is a multiple-population metaheuristic based on soccer concepts. Although it was designed to solve combinatorial optimization problems, until now, it has only been tested with two simple routing problems: the traveling salesman problem and the capacitated vehicle routing problem. In this paper, the GB is applied to four different combinatorial optimization problems. Two of them are routing problems, which are more complex than the previously used ones: the asymmetric traveling salesman problem and the vehicle routing problem with backhauls. Additionally, one constraint satisfaction problem (the n-queen problem) and one combinatorial design problem (the one-dimensional bin packing problem) have also been used. The outcomes obtained by GB are compared with the ones got by two different genetic algorithms and two distributed genetic algorithms. Additionally, two statistical tests are conducted to compare these results. PMID:25165742

Pattern recognition with composite correlation filters designed with multi-object combinatorial optimization

DOE PAGES

Awwal, Abdul; Diaz-Ramirez, Victor H.; Cuevas, Andres; ...

2014-10-23

Composite correlation filters are used for solving a wide variety of pattern recognition problems. These filters are given by a combination of several training templates chosen by a designer in an ad hoc manner. In this work, we present a new approach for the design of composite filters based on multi-objective combinatorial optimization. Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria. Furthermore, by employing a suggested binary-search procedure a filter bank with a minimum number of filters can be constructed, formore » a prespecified trade-off of performance metrics. Computer simulation results obtained with the proposed method in recognizing geometrically distorted versions of a target in cluttered and noisy scenes are discussed and compared in terms of recognition performance and complexity with existing state-of-the-art filters.« less

Pattern recognition with composite correlation filters designed with multi-object combinatorial optimization

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

Awwal, Abdul; Diaz-Ramirez, Victor H.; Cuevas, Andres

Composite correlation filters are used for solving a wide variety of pattern recognition problems. These filters are given by a combination of several training templates chosen by a designer in an ad hoc manner. In this work, we present a new approach for the design of composite filters based on multi-objective combinatorial optimization. Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria. Furthermore, by employing a suggested binary-search procedure a filter bank with a minimum number of filters can be constructed, formore » a prespecified trade-off of performance metrics. Computer simulation results obtained with the proposed method in recognizing geometrically distorted versions of a target in cluttered and noisy scenes are discussed and compared in terms of recognition performance and complexity with existing state-of-the-art filters.« less

What Diagrams Argue in Late Imperial Chinese Combinatorial Texts.

PubMed

Bréard, Andrea

2015-01-01

Attitudes towards diagrammatic reasoning and visualization in mathematics were seldom spelled out in texts from pre-modern China, although illustrations figure prominently in mathematical literature since the eleventh century. Taking the sums of finite series and their combinatorial interpretation as a case study, this article investigates the epistemological function of illustrations from the eleventh to the nineteenth century that encode either the mathematical objects themselves or represent their related algorithms. It particularly focuses on the two illustrations given in Wang Lai's (1768-1813) Mathematical Principles of Sequential Combinations, arguing that they reflect a specific mode of nineteenth-century mathematical argumentative practice and served as a heuristic model for later authors.

Iconicity and the Emergence of Combinatorial Structure in Language.

PubMed

Verhoef, Tessa; Kirby, Simon; de Boer, Bart

2016-11-01

In language, recombination of a discrete set of meaningless building blocks forms an unlimited set of possible utterances. How such combinatorial structure emerged in the evolution of human language is increasingly being studied. It has been shown that it can emerge when languages culturally evolve and adapt to human cognitive biases. How the emergence of combinatorial structure interacts with the existence of holistic iconic form-meaning mappings in a language is still unknown. The experiment presented in this paper studies the role of iconicity and human cognitive learning biases in the emergence of combinatorial structure in artificial whistled languages. Participants learned and reproduced whistled words for novel objects with the use of a slide whistle. Their reproductions were used as input for the next participant, to create transmission chains and simulate cultural transmission. Two conditions were studied: one in which the persistence of iconic form-meaning mappings was possible and one in which this was experimentally made impossible. In both conditions, cultural transmission caused the whistled languages to become more learnable and more structured, but this process was slightly delayed in the first condition. Our findings help to gain insight into when and how words may lose their iconic origins when they become part of an organized linguistic system. Copyright © 2015 Cognitive Science Society, Inc.

Hopf-algebraic structure of combinatorial objects and differential operators

NASA Technical Reports Server (NTRS)

Grossman, Robert; Larson, Richard G.

1989-01-01

A Hopf-algebraic structure on a vector space which has as basis a family of trees is described. Some applications of this structure to combinatorics and to differential operators are surveyed. Some possible future directions for this work are indicated.

Quasi-symmetric designs and equiangular tight frames

NASA Astrophysics Data System (ADS)

Fickus, Matthew; Jasper, John; Mixon, Dustin; Peterson, Jesse

2015-08-01

An equiangular tight frame (ETF) is an M×N matrix which has orthogonal equal norm rows, equal norm columns, and the inner products of all pairs of columns have the same modulus. ETFs arise in numerous applications, including compressed sensing. They also seem to be rare: despite over a decade of active research by the community, only a few construction methods have been discovered. In this article we introduce a new construction of ETFs which uses a particular set of combinatorial designs called quasi-symmetric designs. For ETFs whose entries are contained in {+1;-1}, called real constant amplitude ETFs (RCAETFs), we see that this construction is reversible, giving new quasi-symmetric designs from the known constructions RCAETFs.

Effect of the Implicit Combinatorial Model on Combinatorial Reasoning in Secondary School Pupils.

ERIC Educational Resources Information Center

Batanero, Carmen; And Others

1997-01-01

Elementary combinatorial problems may be classified into three different combinatorial models: (1) selection; (2) partition; and (3) distribution. The main goal of this research was to determine the effect of the implicit combinatorial model on pupils' combinatorial reasoning before and after instruction. Gives an analysis of variance of the…

Quantitative Structure--Activity Relationship Modeling of Rat Acute Toxicity by Oral Exposure

EPA Science Inventory

Background: Few Quantitative Structure-Activity Relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity endpoints. Objective: In this study, a combinatorial QSAR approach has been employed for the creation of robust and predictive models of acute toxi...

Inhibition of Hepatitis C Virus Replication by Intracellular Delivery of Multiple siRNAs by Nanosomes

PubMed Central

Chandra, Partha K; Kundu, Anup K; Hazari, Sidhartha; Chandra, Sruti; Bao, Lili; Ooms, Tara; Morris, Gilbert F; Wu, Tong; Mandal, Tarun K; Dash, Srikanta

2012-01-01

Sustained antiviral responses of chronic hepatitis C virus (HCV) infection have improved recently by the use of direct-acting antiviral agents along with interferon (IFN)-α and ribavirin. However, the emergence of drug-resistant variants is expected to be a major problem. We describe here a novel combinatorial small interfering RNA (siRNA) nanosome-based antiviral approach to clear HCV infection. Multiple siRNAs targeted to the highly conserved 5′-untranslated region (UTR) of the HCV genome were synthesized and encapsulated into lipid nanoparticles called nanosomes. We show that siRNA can be repeatedly delivered to 100% of cells in culture using nanosomes without toxicity. Six siRNAs dramatically reduced HCV replication in both the replicon and infectious cell culture model. Repeated treatments with two siRNAs were better than a single siRNA treatment in minimizing the development of an escape mutant, resulting in rapid inhibition of viral replication. Systemic administration of combinatorial siRNA-nanosomes is well tolerated in BALB/c mice without liver injury or histological toxicity. As a proof-of-principle, we showed that systemic injections of siRNA nanosomes significantly reduced HCV replication in a liver tumor-xenotransplant mouse model of HCV. Our results indicate that systemic delivery of combinatorial siRNA nanosomes can be used to minimize the development of escape mutants and inhibition of HCV infection. PMID:22617108

The hypergraph regularity method and its applications

PubMed Central

Rödl, V.; Nagle, B.; Skokan, J.; Schacht, M.; Kohayakawa, Y.

2005-01-01

Szemerédi's regularity lemma asserts that every graph can be decomposed into relatively few random-like subgraphs. This random-like behavior enables one to find and enumerate subgraphs of a given isomorphism type, yielding the so-called counting lemma for graphs. The combined application of these two lemmas is known as the regularity method for graphs and has proved useful in graph theory, combinatorial geometry, combinatorial number theory, and theoretical computer science. Here, we report on recent advances in the regularity method for k-uniform hypergraphs, for arbitrary k ≥ 2. This method, purely combinatorial in nature, gives alternative proofs of density theorems originally due to E. Szemerédi, H. Furstenberg, and Y. Katznelson. Further results in extremal combinatorics also have been obtained with this approach. The two main components of the regularity method for k-uniform hypergraphs, the regularity lemma and the counting lemma, have been obtained recently: Rödl and Skokan (based on earlier work of Frankl and Rödl) generalized Szemerédi's regularity lemma to k-uniform hypergraphs, and Nagle, Rödl, and Schacht succeeded in proving a counting lemma accompanying the Rödl–Skokan hypergraph regularity lemma. The counting lemma is proved by reducing the counting problem to a simpler one previously investigated by Kohayakawa, Rödl, and Skokan. Similar results were obtained independently by W. T. Gowers, following a different approach. PMID:15919821

Dissection of combinatorial control by the Met4 transcriptional complex.

PubMed

Lee, Traci A; Jorgensen, Paul; Bognar, Andrew L; Peyraud, Caroline; Thomas, Dominique; Tyers, Mike

2010-02-01

Met4 is the transcriptional activator of the sulfur metabolic network in Saccharomyces cerevisiae. Lacking DNA-binding ability, Met4 must interact with proteins called Met4 cofactors to target promoters for transcription. Two types of DNA-binding cofactors (Cbf1 and Met31/Met32) recruit Met4 to promoters and one cofactor (Met28) stabilizes the DNA-bound Met4 complexes. To dissect this combinatorial system, we systematically deleted each category of cofactor(s) and analyzed Met4-activated transcription on a genome-wide scale. We defined a core regulon for Met4, consisting of 45 target genes. Deletion of both Met31 and Met32 eliminated activation of the core regulon, whereas loss of Met28 or Cbf1 interfered with only a subset of targets that map to distinct sectors of the sulfur metabolic network. These transcriptional dependencies roughly correlated with the presence of Cbf1 promoter motifs. Quantitative analysis of in vivo promoter binding properties indicated varying levels of cooperativity and interdependency exists between members of this combinatorial system. Cbf1 was the only cofactor to remain fully bound to target promoters under all conditions, whereas other factors exhibited different degrees of regulated binding in a promoter-specific fashion. Taken together, Met4 cofactors use a variety of mechanisms to allow differential transcription of target genes in response to various cues.

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

Applications of Evolutionary Technology to Manufacturing and Logistics Systems : State-of-the Art Survey

NASA Astrophysics Data System (ADS)

Gen, Mitsuo; Lin, Lin

Many combinatorial optimization problems from industrial engineering and operations research in real-world are very complex in nature and quite hard to solve them by conventional techniques. Since the 1960s, there has been an increasing interest in imitating living beings to solve such kinds of hard combinatorial optimization problems. Simulating the natural evolutionary process of human beings results in stochastic optimization techniques called evolutionary algorithms (EAs), which can often outperform conventional optimization methods when applied to difficult real-world problems. In this survey paper, we provide a comprehensive survey of the current state-of-the-art in the use of EA in manufacturing and logistics systems. In order to demonstrate the EAs which are powerful and broadly applicable stochastic search and optimization techniques, we deal with the following engineering design problems: transportation planning models, layout design models and two-stage logistics models in logistics systems; job-shop scheduling, resource constrained project scheduling in manufacturing system.

The Building Game: From Enumerative Combinatorics to Conformational Diffusion

NASA Astrophysics Data System (ADS)

Johnson-Chyzhykov, Daniel; Menon, Govind

2016-08-01

We study a discrete attachment model for the self-assembly of polyhedra called the building game. We investigate two distinct aspects of the model: (i) enumerative combinatorics of the intermediate states and (ii) a notion of Brownian motion for the polyhedral linkage defined by each intermediate that we term conformational diffusion. The combinatorial configuration space of the model is computed for the Platonic, Archimedean, and Catalan solids of up to 30 faces, and several novel enumerative results are generated. These represent the most exhaustive computations of this nature to date. We further extend the building game to include geometric information. The combinatorial structure of each intermediate yields a systems of constraints specifying a polyhedral linkage and its moduli space. We use a random walk to simulate a reflected Brownian motion in each moduli space. Empirical statistics of the random walk may be used to define the rates of transition for a Markov process modeling the process of self-assembly.

The Great Emch Closure Theorem and a combinatorial proof of Poncelet's Theorem

NASA Astrophysics Data System (ADS)

Avksentyev, E. A.

2015-11-01

The relations between the classical closure theorems (Poncelet's, Steiner's, Emch's, and the zigzag theorems) and some of their generalizations are discussed. It is known that Emch's Theorem is the most general of these, while the others follow as special cases. A generalization of Emch's Theorem to pencils of circles is proved, which (by analogy with the Great Poncelet Theorem) can be called the Great Emch Theorem. It is shown that the Great Emch and Great Poncelet Theorems are equivalent and can be derived one from the other using elementary geometry, and also that both hold in the Lobachevsky plane as well. A new closure theorem is also obtained, in which the construction of closure is slightly more involved: closure occurs on a variable circle which is tangent to a fixed pair of circles. In conclusion, a combinatorial proof of Poncelet's Theorem is given, which deduces the closure principle for an arbitrary number of steps from the principle for three steps using combinatorics and number theory. Bibliography: 20 titles.

Quantitative Tracking of Combinatorially Engineered Populations with Multiplexed Binary Assemblies.

PubMed

Zeitoun, Ramsey I; Pines, Gur; Grau, Willliam C; Gill, Ryan T

2017-04-21

Advances in synthetic biology and genomics have enabled full-scale genome engineering efforts on laboratory time scales. However, the absence of sufficient approaches for mapping engineered genomes at system-wide scales onto performance has limited the adoption of more sophisticated algorithms for engineering complex biological systems. Here we report on the development and application of a robust approach to quantitatively map combinatorially engineered populations at scales up to several dozen target sites. This approach works by assembling genome engineered sites with cell-specific barcodes into a format compatible with high-throughput sequencing technologies. This approach, called barcoded-TRACE (bTRACE) was applied to assess E. coli populations engineered by recursive multiplex recombineering across both 6-target sites and 31-target sites. The 31-target library was then tracked throughout growth selections in the presence and absence of isopentenol (a potential next-generation biofuel). We also use the resolution of bTRACE to compare the influence of technical and biological noise on genome engineering efforts.

A review and experimental study on the application of classifiers and evolutionary algorithms in EEG-based brain-machine interface systems

NASA Astrophysics Data System (ADS)

Tahernezhad-Javazm, Farajollah; Azimirad, Vahid; Shoaran, Maryam

2018-04-01

Objective. Considering the importance and the near-future development of noninvasive brain-machine interface (BMI) systems, this paper presents a comprehensive theoretical-experimental survey on the classification and evolutionary methods for BMI-based systems in which EEG signals are used. Approach. The paper is divided into two main parts. In the first part, a wide range of different types of the base and combinatorial classifiers including boosting and bagging classifiers and evolutionary algorithms are reviewed and investigated. In the second part, these classifiers and evolutionary algorithms are assessed and compared based on two types of relatively widely used BMI systems, sensory motor rhythm-BMI and event-related potentials-BMI. Moreover, in the second part, some of the improved evolutionary algorithms as well as bi-objective algorithms are experimentally assessed and compared. Main results. In this study two databases are used, and cross-validation accuracy (CVA) and stability to data volume (SDV) are considered as the evaluation criteria for the classifiers. According to the experimental results on both databases, regarding the base classifiers, linear discriminant analysis and support vector machines with respect to CVA evaluation metric, and naive Bayes with respect to SDV demonstrated the best performances. Among the combinatorial classifiers, four classifiers, Bagg-DT (bagging decision tree), LogitBoost, and GentleBoost with respect to CVA, and Bagging-LR (bagging logistic regression) and AdaBoost (adaptive boosting) with respect to SDV had the best performances. Finally, regarding the evolutionary algorithms, single-objective invasive weed optimization (IWO) and bi-objective nondominated sorting IWO algorithms demonstrated the best performances. Significance. We present a general survey on the base and the combinatorial classification methods for EEG signals (sensory motor rhythm and event-related potentials) as well as their optimization methods through the evolutionary algorithms. In addition, experimental and statistical significance tests are carried out to study the applicability and effectiveness of the reviewed methods.

Integration of language and sensor information

NASA Astrophysics Data System (ADS)

Perlovsky, Leonid I.; Weijers, Bertus

2003-04-01

The talk describes the development of basic technologies of intelligent systems fusing data from multiple domains and leading to automated computational techniques for understanding data contents. Understanding involves inferring appropriate decisions and recommending proper actions, which in turn requires fusion of data and knowledge about objects, situations, and actions. Data might include sensory data, verbal reports, intelligence intercepts, or public records, whereas knowledge ought to encompass the whole range of objects, situations, people and their behavior, and knowledge of languages. In the past, a fundamental difficulty in combining knowledge with data was the combinatorial complexity of computations, too many combinations of data and knowledge pieces had to be evaluated. Recent progress in understanding of natural intelligent systems, including the human mind, leads to the development of neurophysiologically motivated architectures for solving these challenging problems, in particular the role of emotional neural signals in overcoming combinatorial complexity of old logic-based approaches. Whereas past approaches based on logic tended to identify logic with language and thinking, recent studies in cognitive linguistics have led to appreciation of more complicated nature of linguistic models. Little is known about the details of the brain mechanisms integrating language and thinking. Understanding and fusion of linguistic information with sensory data represent a novel challenging aspect of the development of integrated fusion systems. The presentation will describe a non-combinatorial approach to this problem and outline techniques that can be used for fusing diverse and uncertain knowledge with sensory and linguistic data.

An improved ChIP-seq peak detection system for simultaneously identifying post-translational modified transcription factors by combinatorial fusion, using SUMOylation as an example.

PubMed

Cheng, Chia-Yang; Chu, Chia-Han; Hsu, Hung-Wei; Hsu, Fang-Rong; Tang, Chung Yi; Wang, Wen-Ching; Kung, Hsing-Jien; Chang, Pei-Ching

2014-01-01

Post-translational modification (PTM) of transcriptional factors and chromatin remodelling proteins is recognized as a major mechanism by which transcriptional regulation occurs. Chromatin immunoprecipitation (ChIP) in combination with high-throughput sequencing (ChIP-seq) is being applied as a gold standard when studying the genome-wide binding sites of transcription factor (TFs). This has greatly improved our understanding of protein-DNA interactions on a genomic-wide scale. However, current ChIP-seq peak calling tools are not sufficiently sensitive and are unable to simultaneously identify post-translational modified TFs based on ChIP-seq analysis; this is largely due to the wide-spread presence of multiple modified TFs. Using SUMO-1 modification as an example; we describe here an improved approach that allows the simultaneous identification of the particular genomic binding regions of all TFs with SUMO-1 modification. Traditional peak calling methods are inadequate when identifying multiple TF binding sites that involve long genomic regions and therefore we designed a ChIP-seq processing pipeline for the detection of peaks via a combinatorial fusion method. Then, we annotate the peaks with known transcription factor binding sites (TFBS) using the Transfac Matrix Database (v7.0), which predicts potential SUMOylated TFs. Next, the peak calling result was further analyzed based on the promoter proximity, TFBS annotation, a literature review, and was validated by ChIP-real-time quantitative PCR (qPCR) and ChIP-reChIP real-time qPCR. The results show clearly that SUMOylated TFs are able to be pinpointed using our pipeline. A methodology is presented that analyzes SUMO-1 ChIP-seq patterns and predicts related TFs. Our analysis uses three peak calling tools. The fusion of these different tools increases the precision of the peak calling results. TFBS annotation method is able to predict potential SUMOylated TFs. Here, we offer a new approach that enhances ChIP-seq data analysis and allows the identification of multiple SUMOylated TF binding sites simultaneously, which can then be utilized for other functional PTM binding site prediction in future.

The disadvantage of combinatorial communication.

PubMed Central

Lachmann, Michael; Bergstrom, Carl T.

2004-01-01

Combinatorial communication allows rapid and efficient transfer of detailed information, yet combinatorial communication is used by few, if any, non-human species. To complement recent studies illustrating the advantages of combinatorial communication, we highlight a critical disadvantage. We use the concept of information value to show that deception poses a greater and qualitatively different threat to combinatorial signalling than to non-combinatorial systems. This additional potential for deception may represent a strategic barrier that has prevented widespread evolution of combinatorial communication. Our approach has the additional benefit of drawing clear distinctions among several types of deception that can occur in communication systems. PMID:15556886

The disadvantage of combinatorial communication.

PubMed

Lachmann, Michael; Bergstrom, Carl T

2004-11-22

Combinatorial communication allows rapid and efficient transfer of detailed information, yet combinatorial communication is used by few, if any, non-human species. To complement recent studies illustrating the advantages of combinatorial communication, we highlight a critical disadvantage. We use the concept of information value to show that deception poses a greater and qualitatively different threat to combinatorial signalling than to non-combinatorial systems. This additional potential for deception may represent a strategic barrier that has prevented widespread evolution of combinatorial communication. Our approach has the additional benefit of drawing clear distinctions among several types of deception that can occur in communication systems.

Final Technical Report for GO15052 Intematix: Combinatorial Synthesis and High Throughput Screening of Effective Catalysts for Chemical Hydrides

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

Melman, Jonathan

The objectives of this project are: to discover cost-effective catalysts for release of hydrogen from chemical hydrogen storage systems; and to discover cost-effective catalysts for the regeneration of spent chemical hydrogen storage materials.

Computation of Hypersonic Shock Wave Flows of Multi-Component Reactive Gas Mixtures Using the Generalized Boltzmann Equation

DTIC Science & Technology

2009-03-27

ones like the Lennard - Jones potential with established parameters for each gas (e.g. N2 and 02), and for inelastic collisions DSMC method employs...solution of the collision integral. Lennard - Jones potential with two free parameters is used to obtain the elastic cross-section of the gas molecules...and the so called "combinatory relations" are used to obtain parameters of Lennard - Jones potential for an interaction of molecule A with molecule B

High Temperature Monotonic and Cyclic Deformation in a Directionally Solidified Nickel-Base Superalloy.

DTIC Science & Technology

1986-05-01

was conducted in air, using a SATEC Systems computer-controlled servohydraulic testing machine. This machine uses a minicomputer (Digital PDP 11/34...overall test program) was run. This test was performed using a feature of the SATEC machine called combinatorial feedback, which allowed a user-defined...Rn) l/T + (in Es /A)/n (4.3) Q can be calculated from 0*: b Q=n (4.4) Creep data for DS MAR-M246, containing no Hafnium, from Reference 99 was used to

Quantum Dilogarithms and Partition q-Series

NASA Astrophysics Data System (ADS)

Kato, Akishi; Terashima, Yuji

2015-08-01

In our previous work (Kato and Terashima, Commun Math Phys. arXiv:1403.6569, 2014), we introduced the partition q-series for mutation loop γ—a loop in exchange quiver. In this paper, we show that for a certain class of mutation sequences, called reddening sequences, the graded version of partition q-series essentially coincides with the ordered product of quantum dilogarithm associated with each mutation; the partition q-series provides a state-sum description of combinatorial Donaldson-Thomas invariants introduced by Keller.

On k-ary n-cubes: Theory and applications

NASA Technical Reports Server (NTRS)

Mao, Weizhen; Nicol, David M.

1994-01-01

Many parallel processing networks can be viewed as graphs called k-ary n-cubes, whose special cases include rings, hypercubes and toruses. In this paper, combinatorial properties of k-ary n-cubes are explored. In particular, the problem of characterizing the subgraph of a given number of nodes with the maximum edge count is studied. These theoretical results are then used to compute a lower bounding function in branch-and-bound partitioning algorithms and to establish the optimality of some irregular partitions.

Why is combinatorial communication rare in the natural world, and why is language an exception to this trend?

PubMed

Scott-Phillips, Thomas C; Blythe, Richard A

2013-11-06

In a combinatorial communication system, some signals consist of the combinations of other signals. Such systems are more efficient than equivalent, non-combinatorial systems, yet despite this they are rare in nature. Why? Previous explanations have focused on the adaptive limits of combinatorial communication, or on its purported cognitive difficulties, but neither of these explains the full distribution of combinatorial communication in the natural world. Here, we present a nonlinear dynamical model of the emergence of combinatorial communication that, unlike previous models, considers how initially non-communicative behaviour evolves to take on a communicative function. We derive three basic principles about the emergence of combinatorial communication. We hence show that the interdependence of signals and responses places significant constraints on the historical pathways by which combinatorial signals might emerge, to the extent that anything other than the most simple form of combinatorial communication is extremely unlikely. We also argue that these constraints can be bypassed if individuals have the socio-cognitive capacity to engage in ostensive communication. Humans, but probably no other species, have this ability. This may explain why language, which is massively combinatorial, is such an extreme exception to nature's general trend for non-combinatorial communication.

Anticlockwise or Clockwise? A Dynamic Perception-Action-Laterality Model for Directionality Bias in Visuospatial Functioning

PubMed Central

Karim, A.K.M. Rezaul; Proulx, Michael J.; Likova, Lora T.

2016-01-01

Reviewing the relevant literature in visual psychophysics and visual neuroscience we propose a three-stage model of directionality bias in visuospatial functioning. We call this model the ‘Perception-Action-Laterality’ (PAL) hypothesis. We analyzed the research findings for a wide range of visuospatial tasks, showing that there are two major directionality trends: clockwise versus anticlockwise. It appears these preferences are combinatorial, such that a majority of people fall in the first category demonstrating a preference for stimuli/objects arranged from left-to-right rather than from right-to-left, while people in the second category show an opposite trend. These perceptual biases can guide sensorimotor integration and action, creating two corresponding turner groups in the population. In support of PAL, we propose another model explaining the origins of the biases– how the neurogenetic factors and the cultural factors interact in a biased competition framework to determine the direction and extent of biases. This dynamic model can explain not only the two major categories of biases, but also the unbiased, unreliably biased or mildly biased cases in visuosptial functioning. PMID:27350096

A mathematical function to evaluate surgical complexity of cleft lip and palate.

PubMed

Ortiz-Posadas, M R; Vega-Alvarado, L; Toni, B

2009-06-01

The objective of this work is to show the modeling of a similarity function adapted to the medical environment using the logical-combinatorial approach of pattern recognition theory, and its application comparing the condition of patients with congenital malformations in the lip and/or palate, which are called cleft-primary palate and/or cleft-secondary palate, respectively. The similarity function is defined by the comparison criteria determined for each variable, taking into account their type (qualitative or quantitative), their domain and their initial space representation. In all, we defined 18 variables, with their domains and six different comparison criteria (fuzzy and absolute difference type). The model includes, further, the importance of every variable as well as a weight which reflects the surgical complexity of the cleft. Likewise, the usefulness of this function is shown by calculating the similarity among three patients. This work was developed jointly with the Cleft Palate Team at the Reconstructive Surgery Service of the Pediatric Hospital of Tacubaya, which belongs to the Health Institute of the Federal District in Mexico City.

Fuzzy connectedness and object definition

NASA Astrophysics Data System (ADS)

Udupa, Jayaram K.; Samarasekera, Supun

1995-04-01

Approaches to object information extraction from images should attempt to use the fact that images are fuzzy. In past image segmentation research, the notion of `hanging togetherness' of image elements specified by their fuzzy connectedness has been lacking. We present a theory of fuzzy objects for n-dimensional digital spaces based on a notion of fuzzy connectedness of image elements. Although our definitions lead to problems of enormous combinatorial complexity, the theoretical results allow us to reduce this dramatically. We demonstrate the utility of the theory and algorithms in image segmentation based on several practical examples.

Asessing for Structural Understanding in Childrens' Combinatorial Problem Solving.

ERIC Educational Resources Information Center

English, Lyn

1999-01-01

Assesses children's structural understanding of combinatorial problems when presented in a variety of task situations. Provides an explanatory model of students' combinatorial understandings that informs teaching and assessment. Addresses several components of children's structural understanding of elementary combinatorial problems. (Contains 50…

The Symmetry Group of the Permutahedron

ERIC Educational Resources Information Center

Crisman, Karl-Dieter

2011-01-01

Although it can be visualized fairly easily and its symmetry group is easy to calculate, the permutahedron is a somewhat neglected combinatorial object. We propose it as a useful case study in abstract algebra. It supplies concrete examples of group actions, the difference between right and left actions, and how geometry and algebra can work…

Molecular computational elements encode large populations of small objects

NASA Astrophysics Data System (ADS)

Prasanna de Silva, A.; James, Mark R.; McKinney, Bernadine O. F.; Pears, David A.; Weir, Sheenagh M.

2006-10-01

Since the introduction of molecular computation, experimental molecular computational elements have grown to encompass small-scale integration, arithmetic and games, among others. However, the need for a practical application has been pressing. Here we present molecular computational identification (MCID), a demonstration that molecular logic and computation can be applied to a widely relevant issue. Examples of populations that need encoding in the microscopic world are cells in diagnostics or beads in combinatorial chemistry (tags). Taking advantage of the small size (about 1nm) and large `on/off' output ratios of molecular logic gates and using the great variety of logic types, input chemical combinations, switching thresholds and even gate arrays in addition to colours, we produce unique identifiers for members of populations of small polymer beads (about 100μm) used for synthesis of combinatorial libraries. Many millions of distinguishable tags become available. This method should be extensible to far smaller objects, with the only requirement being a `wash and watch' protocol. Our focus on converting molecular science into technology concerning analog sensors, turns to digital logic devices in the present work.

Molecular computational elements encode large populations of small objects.

PubMed

de Silva, A Prasanna; James, Mark R; McKinney, Bernadine O F; Pears, David A; Weir, Sheenagh M

2006-10-01

Since the introduction of molecular computation, experimental molecular computational elements have grown to encompass small-scale integration, arithmetic and games, among others. However, the need for a practical application has been pressing. Here we present molecular computational identification (MCID), a demonstration that molecular logic and computation can be applied to a widely relevant issue. Examples of populations that need encoding in the microscopic world are cells in diagnostics or beads in combinatorial chemistry (tags). Taking advantage of the small size (about 1 nm) and large 'on/off' output ratios of molecular logic gates and using the great variety of logic types, input chemical combinations, switching thresholds and even gate arrays in addition to colours, we produce unique identifiers for members of populations of small polymer beads (about 100 microm) used for synthesis of combinatorial libraries. Many millions of distinguishable tags become available. This method should be extensible to far smaller objects, with the only requirement being a 'wash and watch' protocol. Our focus on converting molecular science into technology concerning analog sensors, turns to digital logic devices in the present work.

Hypergraph-Based Combinatorial Optimization of Matrix-Vector Multiplication

ERIC Educational Resources Information Center

Wolf, Michael Maclean

2009-01-01

Combinatorial scientific computing plays an important enabling role in computational science, particularly in high performance scientific computing. In this thesis, we will describe our work on optimizing matrix-vector multiplication using combinatorial techniques. Our research has focused on two different problems in combinatorial scientific…

Combinatorial structures to modeling simple games and applications

NASA Astrophysics Data System (ADS)

Molinero, Xavier

2017-09-01

We connect three different topics: combinatorial structures, game theory and chemistry. In particular, we establish the bases to represent some simple games, defined as influence games, and molecules, defined from atoms, by using combinatorial structures. First, we characterize simple games as influence games using influence graphs. It let us to modeling simple games as combinatorial structures (from the viewpoint of structures or graphs). Second, we formally define molecules as combinations of atoms. It let us to modeling molecules as combinatorial structures (from the viewpoint of combinations). It is open to generate such combinatorial structures using some specific techniques as genetic algorithms, (meta-)heuristics algorithms and parallel programming, among others.

PROBABILISTIC CROSS-IDENTIFICATION IN CROWDED FIELDS AS AN ASSIGNMENT PROBLEM

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

Budavári, Tamás; Basu, Amitabh, E-mail: budavari@jhu.edu, E-mail: basu.amitabh@jhu.edu

2016-10-01

One of the outstanding challenges of cross-identification is multiplicity: detections in crowded regions of the sky are often linked to more than one candidate associations of similar likelihoods. We map the resulting maximum likelihood partitioning to the fundamental assignment problem of discrete mathematics and efficiently solve the two-way catalog-level matching in the realm of combinatorial optimization using the so-called Hungarian algorithm. We introduce the method, demonstrate its performance in a mock universe where the true associations are known, and discuss the applicability of the new procedure to large surveys.

Probabilistic Cross-identification in Crowded Fields as an Assignment Problem

NASA Astrophysics Data System (ADS)

Budavári, Tamás; Basu, Amitabh

2016-10-01

One of the outstanding challenges of cross-identification is multiplicity: detections in crowded regions of the sky are often linked to more than one candidate associations of similar likelihoods. We map the resulting maximum likelihood partitioning to the fundamental assignment problem of discrete mathematics and efficiently solve the two-way catalog-level matching in the realm of combinatorial optimization using the so-called Hungarian algorithm. We introduce the method, demonstrate its performance in a mock universe where the true associations are known, and discuss the applicability of the new procedure to large surveys.

Spectral statistics of the uni-modular ensemble

NASA Astrophysics Data System (ADS)

Joyner, Christopher H.; Smilansky, Uzy; Weidenmüller, Hans A.

2017-09-01

We investigate the spectral statistics of Hermitian matrices in which the elements are chosen uniformly from U(1) , called the uni-modular ensemble (UME), in the limit of large matrix size. Using three complimentary methods; a supersymmetric integration method, a combinatorial graph-theoretical analysis and a Brownian motion approach, we are able to derive expressions for 1 / N corrections to the mean spectral moments and also analyse the fluctuations about this mean. By addressing the same ensemble from three different point of view, we can critically compare their relative advantages and derive some new results.

Fast Combinatorial Algorithm for the Solution of Linearly Constrained Least Squares Problems

DOEpatents

Van Benthem, Mark H.; Keenan, Michael R.

2008-11-11

A fast combinatorial algorithm can significantly reduce the computational burden when solving general equality and inequality constrained least squares problems with large numbers of observation vectors. The combinatorial algorithm provides a mathematically rigorous solution and operates at great speed by reorganizing the calculations to take advantage of the combinatorial nature of the problems to be solved. The combinatorial algorithm exploits the structure that exists in large-scale problems in order to minimize the number of arithmetic operations required to obtain a solution.

Unrewarded Object Combinations in Captive Parrots

PubMed Central

Auersperg, Alice Marie Isabel; Oswald, Natalie; Domanegg, Markus; Gajdon, Gyula Koppany; Bugnyar, Thomas

2015-01-01

In primates, complex object combinations during play are often regarded as precursors of functional behavior. Here we investigate combinatory behaviors during unrewarded object manipulation in seven parrot species, including kea, African grey parrots and Goffin cockatoos, three species previously used as model species for technical problem solving. We further examine a habitually tool using species, the black palm cockatoo. Moreover, we incorporate three neotropical species, the yellow- and the black-billed Amazon and the burrowing parakeet. Paralleling previous studies on primates and corvids, free object-object combinations and complex object-substrate combinations such as inserting objects into tubes/holes or stacking rings onto poles prevailed in the species previously linked to advanced physical cognition and tool use. In addition, free object-object combinations were intrinsically structured in Goffin cockatoos and in kea. PMID:25984564

A New Approach for Proving or Generating Combinatorial Identities

ERIC Educational Resources Information Center

Gonzalez, Luis

2010-01-01

A new method for proving, in an immediate way, many combinatorial identities is presented. The method is based on a simple recursive combinatorial formula involving n + 1 arbitrary real parameters. Moreover, this formula enables one not only to prove, but also generate many different combinatorial identities (not being required to know them "a…

Approximation algorithms for a genetic diagnostics problem.

PubMed

Kosaraju, S R; Schäffer, A A; Biesecker, L G

1998-01-01

We define and study a combinatorial problem called WEIGHTED DIAGNOSTIC COVER (WDC) that models the use of a laboratory technique called genotyping in the diagnosis of an important class of chromosomal aberrations. An optimal solution to WDC would enable us to define a genetic assay that maximizes the diagnostic power for a specified cost of laboratory work. We develop approximation algorithms for WDC by making use of the well-known problem SET COVER for which the greedy heuristic has been extensively studied. We prove worst-case performance bounds on the greedy heuristic for WDC and for another heuristic we call directional greedy. We implemented both heuristics. We also implemented a local search heuristic that takes the solutions obtained by greedy and dir-greedy and applies swaps until they are locally optimal. We report their performance on a real data set that is representative of the options that a clinical geneticist faces for the real diagnostic problem. Many open problems related to WDC remain, both of theoretical interest and practical importance.

Combinatorial techniques to efficiently investigate and optimize organic thin film processing and properties.

PubMed

Wieberger, Florian; Kolb, Tristan; Neuber, Christian; Ober, Christopher K; Schmidt, Hans-Werner

2013-04-08

In this article we present several developed and improved combinatorial techniques to optimize processing conditions and material properties of organic thin films. The combinatorial approach allows investigations of multi-variable dependencies and is the perfect tool to investigate organic thin films regarding their high performance purposes. In this context we develop and establish the reliable preparation of gradients of material composition, temperature, exposure, and immersion time. Furthermore we demonstrate the smart application of combinations of composition and processing gradients to create combinatorial libraries. First a binary combinatorial library is created by applying two gradients perpendicular to each other. A third gradient is carried out in very small areas and arranged matrix-like over the entire binary combinatorial library resulting in a ternary combinatorial library. Ternary combinatorial libraries allow identifying precise trends for the optimization of multi-variable dependent processes which is demonstrated on the lithographic patterning process. Here we verify conclusively the strong interaction and thus the interdependency of variables in the preparation and properties of complex organic thin film systems. The established gradient preparation techniques are not limited to lithographic patterning. It is possible to utilize and transfer the reported combinatorial techniques to other multi-variable dependent processes and to investigate and optimize thin film layers and devices for optical, electro-optical, and electronic applications.

CAMELOT: Computational-Analytical Multi-fidElity Low-thrust Optimisation Toolbox

NASA Astrophysics Data System (ADS)

Di Carlo, Marilena; Romero Martin, Juan Manuel; Vasile, Massimiliano

2018-03-01

Computational-Analytical Multi-fidElity Low-thrust Optimisation Toolbox (CAMELOT) is a toolbox for the fast preliminary design and optimisation of low-thrust trajectories. It solves highly complex combinatorial problems to plan multi-target missions characterised by long spirals including different perturbations. To do so, CAMELOT implements a novel multi-fidelity approach combining analytical surrogate modelling and accurate computational estimations of the mission cost. Decisions are then made using two optimisation engines included in the toolbox, a single-objective global optimiser, and a combinatorial optimisation algorithm. CAMELOT has been applied to a variety of case studies: from the design of interplanetary trajectories to the optimal de-orbiting of space debris and from the deployment of constellations to on-orbit servicing. In this paper, the main elements of CAMELOT are described and two examples, solved using the toolbox, are presented.

Dynamic combinatorial libraries: new opportunities in systems chemistry.

PubMed

Hunt, Rosemary A R; Otto, Sijbren

2011-01-21

Combinatorial chemistry is a tool for selecting molecules with special properties. Dynamic combinatorial chemistry started off aiming to be just that. However, unlike ordinary combinatorial chemistry, the interconnectedness of dynamic libraries gives them an extra dimension. An understanding of these molecular networks at systems level is essential for their use as a selection tool and creates exciting new opportunities in systems chemistry. In this feature article we discuss selected examples and considerations related to the advanced exploitation of dynamic combinatorial libraries for their originally conceived purpose of identifying strong binding interactions. Also reviewed are examples illustrating a trend towards increasing complexity in terms of network behaviour and reversible chemistry. Finally, new applications of dynamic combinatorial chemistry in self-assembly, transport and self-replication are discussed.

Unified method of knowledge representation in the evolutionary artificial intelligence systems

NASA Astrophysics Data System (ADS)

Bykov, Nickolay M.; Bykova, Katherina N.

2003-03-01

The evolution of artificial intelligence systems called by complicating of their operation topics and science perfecting has resulted in a diversification of the methods both the algorithms of knowledge representation and usage in these systems. Often by this reason it is very difficult to design the effective methods of knowledge discovering and operation for such systems. In the given activity the authors offer a method of unitized representation of the systems knowledge about objects of an external world by rank transformation of their descriptions, made in the different features spaces: deterministic, probabilistic, fuzzy and other. The proof of a sufficiency of the information about the rank configuration of the object states in the features space for decision making is presented. It is shown that the geometrical and combinatorial model of the rank configurations set introduce their by group of some system of incidence, that allows to store the information on them in a convolute kind. The method of the rank configuration description by the DRP - code (distance rank preserving code) is offered. The problems of its completeness, information capacity, noise immunity and privacy are reviewed. It is shown, that the capacity of a transmission channel for such submission of the information is more than unit, as the code words contain the information both about the object states, and about the distance ranks between them. The effective algorithm of the data clustering for the object states identification, founded on the given code usage, is described. The knowledge representation with the help of the rank configurations allows to unitize and to simplify algorithms of the decision making by fulfillment of logic operations above the DRP - code words. Examples of the proposed clustering techniques operation on the given samples set, the rank configuration of resulted clusters and its DRP-codes are presented.

Cooperative quantum-behaved particle swarm optimization with dynamic varying search areas and Lévy flight disturbance.

PubMed

Li, Desheng

2014-01-01

This paper proposes a novel variant of cooperative quantum-behaved particle swarm optimization (CQPSO) algorithm with two mechanisms to reduce the search space and avoid the stagnation, called CQPSO-DVSA-LFD. One mechanism is called Dynamic Varying Search Area (DVSA), which takes charge of limiting the ranges of particles' activity into a reduced area. On the other hand, in order to escape the local optima, Lévy flights are used to generate the stochastic disturbance in the movement of particles. To test the performance of CQPSO-DVSA-LFD, numerical experiments are conducted to compare the proposed algorithm with different variants of PSO. According to the experimental results, the proposed method performs better than other variants of PSO on both benchmark test functions and the combinatorial optimization issue, that is, the job-shop scheduling problem.

cDREM: inferring dynamic combinatorial gene regulation.

PubMed

Wise, Aaron; Bar-Joseph, Ziv

2015-04-01

Genes are often combinatorially regulated by multiple transcription factors (TFs). Such combinatorial regulation plays an important role in development and facilitates the ability of cells to respond to different stresses. While a number of approaches have utilized sequence and ChIP-based datasets to study combinational regulation, these have often ignored the combinational logic and the dynamics associated with such regulation. Here we present cDREM, a new method for reconstructing dynamic models of combinatorial regulation. cDREM integrates time series gene expression data with (static) protein interaction data. The method is based on a hidden Markov model and utilizes the sparse group Lasso to identify small subsets of combinatorially active TFs, their time of activation, and the logical function they implement. We tested cDREM on yeast and human data sets. Using yeast we show that the predicted combinatorial sets agree with other high throughput genomic datasets and improve upon prior methods developed to infer combinatorial regulation. Applying cDREM to study human response to flu, we were able to identify several combinatorial TF sets, some of which were known to regulate immune response while others represent novel combinations of important TFs.

Scaffold architecture and pharmacophoric properties of natural products and trade drugs: application in the design of natural product-based combinatorial libraries.

PubMed

Lee, M L; Schneider, G

2001-01-01

Natural products were analyzed to determine whether they contain appealing novel scaffold architectures for potential use in combinatorial chemistry. Ring systems were extracted and clustered on the basis of structural similarity. Several such potential scaffolds for combinatorial chemistry were identified that are not present in current trade drugs. For one of these scaffolds a virtual combinatorial library was generated. Pharmacophoric properties of natural products, trade drugs, and the virtual combinatorial library were assessed using a self-organizing map. Obviously, current trade drugs and natural products have several topological pharmacophore patterns in common. These features can be systematically explored with selected combinatorial libraries based on a combination of natural product-derived and synthetic molecular building blocks.

Use of combinatorial chemistry to speed drug discovery.

PubMed

Rádl, S

1998-10-01

IBC's International Conference on Integrating Combinatorial Chemistry into the Discovery Pipeline was held September 14-15, 1998. The program started with a pre-conference workshop on High-Throughput Compound Characterization and Purification. The agenda of the main conference was divided into sessions of Synthesis, Automation and Unique Chemistries; Integrating Combinatorial Chemistry, Medicinal Chemistry and Screening; Combinatorial Chemistry Applications for Drug Discovery; and Information and Data Management. This meeting was an excellent opportunity to see how big pharma, biotech and service companies are addressing the current bottlenecks in combinatorial chemistry to speed drug discovery. (c) 1998 Prous Science. All rights reserved.

Structural Validation of Nursing Terminologies

PubMed Central

Hardiker, Nicholas R.; Rector, Alan L.

2001-01-01

Objective: The purpose of the study is twofold: 1) to explore the applicability of combinatorial terminologies as the basis for building enumerated classifications, and 2) to investigate the usefulness of formal terminological systems for performing such classification and for assisting in the refinement of both combinatorial terminologies and enumerated classifications. Design: A formal model of the beta version of the International Classification for Nursing Practice (ICNP) was constructed in the compositional terminological language GRAIL (GALEN Representation and Integration Language). Terms drawn from the North American Nursing Diagnosis Association Taxonomy I (NANDA taxonomy) were mapped into the model and classified automatically using GALEN technology. Measurements: The resulting generated hierarchy was compared with the NANDA taxonomy to assess coverage and accuracy of classification. Results: In terms of coverage, in this study ICNP was able to capture 77 percent of NANDA terms using concepts drawn from five of its eight axes. Three axes—Body Site, Topology, and Frequency—were not needed. In terms of accuracy, where hierarchic relationships existed in the generated hierarchy or the NANDA taxonomy, or both, 6 were identical, 19 existed in the generated hierarchy alone (2 of these were considered suitable for incorporation into the NANDA taxonomy and 17 were considered inaccurate), and 23 appeared in the NANDA taxonomy alone (8 of these were considered suitable for incorporation into ICNP, 9 were considered inaccurate, and 6 reflected different, equally valid perspectives). Sixty terms appeared at the top level, with no indenting, in both the generated hierarchy and the NANDA taxonomy. Conclusions: With appropriate refinement, combinatorial terminologies such as ICNP have the potential to provide a useful foundation for representing enumerated classifications such as NANDA. Technologies such as GALEN make possible the process of building automatically enumerated classifications while providing a useful means of validating and refining both combinatorial terminologies and enumerated classifications. PMID:11320066

GALAXY: A new hybrid MOEA for the optimal design of Water Distribution Systems

NASA Astrophysics Data System (ADS)

Wang, Q.; Savić, D. A.; Kapelan, Z.

2017-03-01

A new hybrid optimizer, called genetically adaptive leaping algorithm for approximation and diversity (GALAXY), is proposed for dealing with the discrete, combinatorial, multiobjective design of Water Distribution Systems (WDSs), which is NP-hard and computationally intensive. The merit of GALAXY is its ability to alleviate to a great extent the parameterization issue and the high computational overhead. It follows the generational framework of Multiobjective Evolutionary Algorithms (MOEAs) and includes six search operators and several important strategies. These operators are selected based on their leaping ability in the objective space from the global and local search perspectives. These strategies steer the optimization and balance the exploration and exploitation aspects simultaneously. A highlighted feature of GALAXY lies in the fact that it eliminates majority of parameters, thus being robust and easy-to-use. The comparative studies between GALAXY and three representative MOEAs on five benchmark WDS design problems confirm its competitiveness. GALAXY can identify better converged and distributed boundary solutions efficiently and consistently, indicating a much more balanced capability between the global and local search. Moreover, its advantages over other MOEAs become more substantial as the complexity of the design problem increases.

Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection

DOEpatents

Paiton, Dylan M.; Kenyon, Garrett T.; Brumby, Steven P.; Schultz, Peter F.; George, John S.

2015-07-28

An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using a combinatorial algorithm.

Microbatteries for Combinatorial Studies of Conventional Lithium-Ion Batteries

NASA Technical Reports Server (NTRS)

West, William; Whitacre, Jay; Bugga, Ratnakumar

2003-01-01

Integrated arrays of microscopic solid-state batteries have been demonstrated in a continuing effort to develop microscopic sources of power and of voltage reference circuits to be incorporated into low-power integrated circuits. Perhaps even more importantly, arrays of microscopic batteries can be fabricated and tested in combinatorial experiments directed toward optimization and discovery of battery materials. The value of the combinatorial approach to optimization and discovery has been proven in the optoelectronic, pharmaceutical, and bioengineering industries. Depending on the specific application, the combinatorial approach can involve the investigation of hundreds or even thousands of different combinations; hence, it is time-consuming and expensive to attempt to implement the combinatorial approach by building and testing full-size, discrete cells and batteries. The conception of microbattery arrays makes it practical to bring the advantages of the combinatorial approach to the development of batteries.

Graphene Microcapsule Arrays for Combinatorial Electron Microscopy and Spectroscopy in Liquids

DOE PAGES

Yulaev, Alexander; Guo, Hongxuan; Strelcov, Evgheni; ...

2017-04-27

Atomic-scale thickness, molecular impermeability, low atomic number, and mechanical strength make graphene an ideal electron-transparent membrane for material characterization in liquids and gases with scanning electron microscopy and spectroscopy. Here in this paper, we present a novel sample platform made of an array of thousands of identical isolated graphene-capped microchannels with high aspect ratio. A combination of a global wide field of view with high resolution local imaging of the array allows for high throughput in situ studies as well as for combinatorial screening of solutions, liquid interfaces, and immersed samples. We demonstrate the capabilities of this platform by studyingmore » a pure water sample in comparison with alkali halide solutions, a model electrochemical plating process, and beam-induced crystal growth in liquid electrolyte. Spectroscopic characterization of liquid interfaces and immersed objects with Auger and X-ray fluorescence analysis through the graphene membrane are also demonstrated.« less

Neural Meta-Memes Framework for Combinatorial Optimization

NASA Astrophysics Data System (ADS)

Song, Li Qin; Lim, Meng Hiot; Ong, Yew Soon

In this paper, we present a Neural Meta-Memes Framework (NMMF) for combinatorial optimization. NMMF is a framework which models basic optimization algorithms as memes and manages them dynamically when solving combinatorial problems. NMMF encompasses neural networks which serve as the overall planner/coordinator to balance the workload between memes. We show the efficacy of the proposed NMMF through empirical study on a class of combinatorial problem, the quadratic assignment problem (QAP).

Campbell's monkeys concatenate vocalizations into context-specific call sequences

PubMed Central

Ouattara, Karim; Lemasson, Alban; Zuberbühler, Klaus

2009-01-01

Primate vocal behavior is often considered irrelevant in modeling human language evolution, mainly because of the caller's limited vocal control and apparent lack of intentional signaling. Here, we present the results of a long-term study on Campbell's monkeys, which has revealed an unrivaled degree of vocal complexity. Adult males produced six different loud call types, which they combined into various sequences in highly context-specific ways. We found stereotyped sequences that were strongly associated with cohesion and travel, falling trees, neighboring groups, nonpredatory animals, unspecific predatory threat, and specific predator classes. Within the responses to predators, we found that crowned eagles triggered four and leopards three different sequences, depending on how the caller learned about their presence. Callers followed a number of principles when concatenating sequences, such as nonrandom transition probabilities of call types, addition of specific calls into an existing sequence to form a different one, or recombination of two sequences to form a third one. We conclude that these primates have overcome some of the constraints of limited vocal control by combinatorial organization. As the different sequences were so tightly linked to specific external events, the Campbell's monkey call system may be the most complex example of ‘proto-syntax’ in animal communication known to date. PMID:20007377

2D photonic crystal complete band gap search using a cyclic cellular automaton refination

NASA Astrophysics Data System (ADS)

González-García, R.; Castañón, G.; Hernández-Figueroa, H. E.

2014-11-01

We present a refination method based on a cyclic cellular automaton (CCA) that simulates a crystallization-like process, aided with a heuristic evolutionary method called differential evolution (DE) used to perform an ordered search of full photonic band gaps (FPBGs) in a 2D photonic crystal (PC). The solution is proposed as a combinatorial optimization of the elements in a binary array. These elements represent the existence or absence of a dielectric material surrounded by air, thus representing a general geometry whose search space is defined by the number of elements in such array. A block-iterative frequency-domain method was used to compute the FPBGs on a PC, when present. DE has proved to be useful in combinatorial problems and we also present an implementation feature that takes advantage of the periodic nature of PCs to enhance the convergence of this algorithm. Finally, we used this methodology to find a PC structure with a 19% bandgap-to-midgap ratio without requiring previous information of suboptimal configurations and we made a statistical study of how it is affected by disorder in the borders of the structure compared with a previous work that uses a genetic algorithm.

Expediting Combinatorial Data Set Analysis by Combining Human and Algorithmic Analysis.

PubMed

Stein, Helge Sören; Jiao, Sally; Ludwig, Alfred

2017-01-09

A challenge in combinatorial materials science remains the efficient analysis of X-ray diffraction (XRD) data and its correlation to functional properties. Rapid identification of phase-regions and proper assignment of corresponding crystal structures is necessary to keep pace with the improved methods for synthesizing and characterizing materials libraries. Therefore, a new modular software called htAx (high-throughput analysis of X-ray and functional properties data) is presented that couples human intelligence tasks used for "ground-truth" phase-region identification with subsequent unbiased verification by an algorithm to efficiently analyze which phases are present in a materials library. Identified phases and phase-regions may then be correlated to functional properties in an expedited manner. For the functionality of htAx to be proven, two previously published XRD benchmark data sets of the materials systems Al-Cr-Fe-O and Ni-Ti-Cu are analyzed by htAx. The analysis of ∼1000 XRD patterns takes less than 1 day with htAx. The proposed method reliably identifies phase-region boundaries and robustly identifies multiphase structures. The method also addresses the problem of identifying regions with previously unpublished crystal structures using a special daisy ternary plot.

Spectral monodromy of non-self-adjoint operators

NASA Astrophysics Data System (ADS)

Phan, Quang Sang

2014-01-01

In the present paper, we build a combinatorial invariant, called the "spectral monodromy" from the spectrum of a single (non-self-adjoint) h-pseudodifferential operator with two degrees of freedom in the semi-classical limit. Our inspiration comes from the quantum monodromy defined for the joint spectrum of an integrable system of n commuting self-adjoint h-pseudodifferential operators, given by S. Vu Ngoc ["Quantum monodromy in integrable systems," Commun. Math. Phys. 203(2), 465-479 (1999)]. The first simple case that we treat in this work is a normal operator. In this case, the discrete spectrum can be identified with the joint spectrum of an integrable quantum system. The second more complex case we propose is a small perturbation of a self-adjoint operator with a classical integrability property. We show that the discrete spectrum (in a small band around the real axis) also has a combinatorial monodromy. The main difficulty in this case is that we do not know the description of the spectrum everywhere, but only in a Cantor type set. In addition, we also show that the corresponding monodromy can be identified with the classical monodromy, defined by J. Duistermaat ["On global action-angle coordinates," Commun. Pure Appl. Math. 33(6), 687-706 (1980)].

Combining local search with co-evolution in a remarkably simple way

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

Boettcher, S.; Percus, A.

2000-05-01

The authors explore a new general-purpose heuristic for finding high-quality solutions to hard optimization problem. The method, called extremal optimization, is inspired by self-organized criticality, a concept introduced to describe emergent complexity in physical systems. In contrast to genetic algorithms, which operate on an entire gene-pool of possible solutions, extremal optimization successively replaces extremely undesirable elements of a single sub-optimal solution with new, random ones. Large fluctuations, or avalanches, ensue that efficiently explore many local optima. Drawing upon models used to simulate far-from-equilibrium dynamics, extremal optimization complements heuristics inspired by equilibrium statistical physics, such as simulated annealing. With only onemore » adjustable parameter, its performance has proved competitive with more elaborate methods, especially near phase transitions. Phase transitions are found in many combinatorial optimization problems, and have been conjectured to occur in the region of parameter space containing the hardest instances. We demonstrate how extremal optimization can be implemented for a variety of hard optimization problems. We believe that this will be a useful tool in the investigation of phase transitions in combinatorial optimization, thereby helping to elucidate the origin of computational complexity.« less

Combinatorial Codes and Labeled Lines: How Insects Use Olfactory Cues to Find and Judge Food, Mates, and Oviposition Sites in Complex Environments

PubMed Central

Haverkamp, Alexander; Hansson, Bill S.; Knaden, Markus

2018-01-01

Insects, including those which provide vital ecosystems services as well as those which are devastating pests or disease vectors, locate their resources mainly based on olfaction. Understanding insect olfaction not only from a neurobiological but also from an ecological perspective is therefore crucial to balance insect control and conservation. However, among all sensory stimuli olfaction is particularly hard to grasp. Our chemical environment is made up of thousands of different compounds, which might again be detected by our nose in multiple ways. Due to this complexity, researchers have only recently begun to explore the chemosensory ecology of model organisms such as Drosophila, linking the tools of chemical ecology to those of neurogenetics. This cross-disciplinary approach has enabled several studies that range from single odors and their ecological relevance, via olfactory receptor genes and neuronal processing, up to the insects' behavior. We learned that the insect olfactory system employs strategies of combinatorial coding to process general odors as well as labeled lines for specific compounds that call for an immediate response. These studies opened new doors to the olfactory world in which insects feed, oviposit, and mate. PMID:29449815

A ripple-spreading genetic algorithm for the aircraft sequencing problem.

PubMed

Hu, Xiao-Bing; Di Paolo, Ezequiel A

2011-01-01

When genetic algorithms (GAs) are applied to combinatorial problems, permutation representations are usually adopted. As a result, such GAs are often confronted with feasibility and memory-efficiency problems. With the aircraft sequencing problem (ASP) as a study case, this paper reports on a novel binary-representation-based GA scheme for combinatorial problems. Unlike existing GAs for the ASP, which typically use permutation representations based on aircraft landing order, the new GA introduces a novel ripple-spreading model which transforms the original landing-order-based ASP solutions into value-based ones. In the new scheme, arriving aircraft are projected as points into an artificial space. A deterministic method inspired by the natural phenomenon of ripple-spreading on liquid surfaces is developed, which uses a few parameters as input to connect points on this space to form a landing sequence. A traditional GA, free of feasibility and memory-efficiency problems, can then be used to evolve the ripple-spreading related parameters in order to find an optimal sequence. Since the ripple-spreading model is the centerpiece of the new algorithm, it is called the ripple-spreading GA (RSGA). The advantages of the proposed RSGA are illustrated by extensive comparative studies for the case of the ASP.

On the combinatorics of sparsification.

PubMed

Huang, Fenix Wd; Reidys, Christian M

2012-10-22

We study the sparsification of dynamic programming based on folding algorithms of RNA structures. Sparsification is a method that improves significantly the computation of minimum free energy (mfe) RNA structures. We provide a quantitative analysis of the sparsification of a particular decomposition rule, Λ∗. This rule splits an interval of RNA secondary and pseudoknot structures of fixed topological genus. Key for quantifying sparsifications is the size of the so called candidate sets. Here we assume mfe-structures to be specifically distributed (see Assumption 1) within arbitrary and irreducible RNA secondary and pseudoknot structures of fixed topological genus. We then present a combinatorial framework which allows by means of probabilities of irreducible sub-structures to obtain the expectation of the Λ∗-candidate set w.r.t. a uniformly random input sequence. We compute these expectations for arc-based energy models via energy-filtered generating functions (GF) in case of RNA secondary structures as well as RNA pseudoknot structures. Furthermore, for RNA secondary structures we also analyze a simplified loop-based energy model. Our combinatorial analysis is then compared to the expected number of Λ∗-candidates obtained from the folding mfe-structures. In case of the mfe-folding of RNA secondary structures with a simplified loop-based energy model our results imply that sparsification provides a significant, constant improvement of 91% (theory) to be compared to an 96% (experimental, simplified arc-based model) reduction. However, we do not observe a linear factor improvement. Finally, in case of the "full" loop-energy model we can report a reduction of 98% (experiment). Sparsification was initially attributed a linear factor improvement. This conclusion was based on the so called polymer-zeta property, which stems from interpreting polymer chains as self-avoiding walks. Subsequent findings however reveal that the O(n) improvement is not correct. The combinatorial analysis presented here shows that, assuming a specific distribution (see Assumption 1), of mfe-structures within irreducible and arbitrary structures, the expected number of Λ∗-candidates is Θ(n2). However, the constant reduction is quite significant, being in the range of 96%. We furthermore show an analogous result for the sparsification of the Λ∗-decomposition rule for RNA pseudoknotted structures of genus one. Finally we observe that the effect of sparsification is sensitive to the employed energy model.

Trichostatin A Enhances the Apoptotic Potential of Palladium Nanoparticles in Human Cervical Cancer Cells.

PubMed

Zhang, Xi-Feng; Yan, Qi; Shen, Wei; Gurunathan, Sangiliyandi

2016-08-19

Cervical cancer ranks seventh overall among all types of cancer in women. Although several treatments, including radiation, surgery and chemotherapy, are available to eradicate or reduce the size of cancer, many cancers eventually relapse. Thus, it is essential to identify possible alternative therapeutic approaches for cancer. We sought to identify alternative and effective therapeutic approaches, by first synthesizing palladium nanoparticles (PdNPs), using a novel biomolecule called saponin. The synthesized PdNPs were characterized by several analytical techniques. They were significantly spherical in shape, with an average size of 5 nm. Recently, PdNPs gained much interest in various therapies of cancer cells. Similarly, histone deacetylase inhibitors are known to play a vital role in anti-proliferative activity, gene expression, cell cycle arrest, differentiation and apoptosis in various cancer cells. Therefore, we selected trichostatin A (TSA) and PdNPs and studied their combined effect on apoptosis in cervical cancer cells. Cells treated with either TSA or PdNPs showed a dose-dependent effect on cell viability. The combinatorial effect, tested with 50 nM TSA and 50 nMPdNPs, had a more dramatic inhibitory effect on cell viability, than either TSA or PdNPs alone. The combination of TSA and PdNPs had a more pronounced effect on cytotoxicity, oxidative stress, mitochondrial membrane potential (MMP), caspase-3/9 activity and expression of pro- and anti-apoptotic genes. Our data show a strong synergistic interaction between TSA and PdNPs in cervical cancer cells. The combinatorial treatment increased the therapeutic potential and demonstrated relevant targeted therapy for cervical cancer. Furthermore, we provide the first evidence for the combinatory effect and cytotoxicity mechanism of TSA and PdNPs in cervical cancer cells.

Trichostatin A Enhances the Apoptotic Potential of Palladium Nanoparticles in Human Cervical Cancer Cells

PubMed Central

Zhang, Xi-Feng; Yan, Qi; Shen, Wei; Gurunathan, Sangiliyandi

2016-01-01

Cervical cancer ranks seventh overall among all types of cancer in women. Although several treatments, including radiation, surgery and chemotherapy, are available to eradicate or reduce the size of cancer, many cancers eventually relapse. Thus, it is essential to identify possible alternative therapeutic approaches for cancer. We sought to identify alternative and effective therapeutic approaches, by first synthesizing palladium nanoparticles (PdNPs), using a novel biomolecule called saponin. The synthesized PdNPs were characterized by several analytical techniques. They were significantly spherical in shape, with an average size of 5 nm. Recently, PdNPs gained much interest in various therapies of cancer cells. Similarly, histone deacetylase inhibitors are known to play a vital role in anti-proliferative activity, gene expression, cell cycle arrest, differentiation and apoptosis in various cancer cells. Therefore, we selected trichostatin A (TSA) and PdNPs and studied their combined effect on apoptosis in cervical cancer cells. Cells treated with either TSA or PdNPs showed a dose-dependent effect on cell viability. The combinatorial effect, tested with 50 nM TSA and 50 nMPdNPs, had a more dramatic inhibitory effect on cell viability, than either TSA or PdNPs alone. The combination of TSA and PdNPs had a more pronounced effect on cytotoxicity, oxidative stress, mitochondrial membrane potential (MMP), caspase-3/9 activity and expression of pro- and anti-apoptotic genes. Our data show a strong synergistic interaction between TSA and PdNPs in cervical cancer cells. The combinatorial treatment increased the therapeutic potential and demonstrated relevant targeted therapy for cervical cancer. Furthermore, we provide the first evidence for the combinatory effect and cytotoxicity mechanism of TSA and PdNPs in cervical cancer cells. PMID:27548148

FOREWORD: Focus on Combinatorial Materials Science Focus on Combinatorial Materials Science

NASA Astrophysics Data System (ADS)

Chikyo, Toyohiro

2011-10-01

About 15 years have passed since the introduction of modern combinatorial synthesis and high-throughput techniques for the development of novel inorganic materials; however, similar methods existed before. The most famous was reported in 1970 by Hanak who prepared composition-spread films of metal alloys by sputtering mixed-material targets. Although this method was innovative, it was rarely used because of the large amount of data to be processed. This problem is solved in the modern combinatorial material research, which is strongly related to computer data analysis and robotics. This field is still at the developing stage and may be enriched by new methods. Nevertheless, given the progress in measurement equipment and procedures, we believe the combinatorial approach will become a major and standard tool of materials screening and development. The first article of this journal, published in 2000, was titled 'Combinatorial solid state materials science and technology', and this focus issue aims to reintroduce this topic to the Science and Technology of Advanced Materials audience. It covers recent progress in combinatorial materials research describing new results in catalysis, phosphors, polymers and metal alloys for shape memory materials. Sophisticated high-throughput characterization schemes and innovative synthesis tools are also presented, such as spray deposition using nanoparticles or ion plating. On a technical note, data handling systems are introduced to familiarize researchers with the combinatorial methodology. We hope that through this focus issue a wide audience of materials scientists can learn about recent and future trends in combinatorial materials science and high-throughput experimentation.

Cooperative Quantum-Behaved Particle Swarm Optimization with Dynamic Varying Search Areas and Lévy Flight Disturbance

PubMed Central

Li, Desheng

2014-01-01

This paper proposes a novel variant of cooperative quantum-behaved particle swarm optimization (CQPSO) algorithm with two mechanisms to reduce the search space and avoid the stagnation, called CQPSO-DVSA-LFD. One mechanism is called Dynamic Varying Search Area (DVSA), which takes charge of limiting the ranges of particles' activity into a reduced area. On the other hand, in order to escape the local optima, Lévy flights are used to generate the stochastic disturbance in the movement of particles. To test the performance of CQPSO-DVSA-LFD, numerical experiments are conducted to compare the proposed algorithm with different variants of PSO. According to the experimental results, the proposed method performs better than other variants of PSO on both benchmark test functions and the combinatorial optimization issue, that is, the job-shop scheduling problem. PMID:24851085

Evaluation of the Optimum Composition of Low-Temperature Fuel Cell Electrocatalysts for Methanol Oxidation by Combinatorial Screening.

PubMed

Antolini, Ermete

2017-02-13

Combinatorial chemistry and high-throughput screening represent an innovative and rapid tool to prepare and evaluate a large number of new materials, saving time and expense for research and development. Considering that the activity and selectivity of catalysts depend on complex kinetic phenomena, making their development largely empirical in practice, they are prime candidates for combinatorial discovery and optimization. This review presents an overview of recent results of combinatorial screening of low-temperature fuel cell electrocatalysts for methanol oxidation. Optimum catalyst compositions obtained by combinatorial screening were compared with those of bulk catalysts, and the effect of the library geometry on the screening of catalyst composition is highlighted.

Combinatorial computational chemistry approach for materials design: applications in deNOx catalysis, Fischer-Tropsch synthesis, lanthanoid complex, and lithium ion secondary battery.

PubMed

Koyama, Michihisa; Tsuboi, Hideyuki; Endou, Akira; Takaba, Hiromitsu; Kubo, Momoji; Del Carpio, Carlos A; Miyamoto, Akira

2007-02-01

Computational chemistry can provide fundamental knowledge regarding various aspects of materials. While its impact in scientific research is greatly increasing, its contributions to industrially important issues are far from satisfactory. In order to realize industrial innovation by computational chemistry, a new concept "combinatorial computational chemistry" has been proposed by introducing the concept of combinatorial chemistry to computational chemistry. This combinatorial computational chemistry approach enables theoretical high-throughput screening for materials design. In this manuscript, we review the successful applications of combinatorial computational chemistry to deNO(x) catalysts, Fischer-Tropsch catalysts, lanthanoid complex catalysts, and cathodes of the lithium ion secondary battery.

Further Results on Constructions of Generalized Bent Boolean Functions

DTIC Science & Technology

2016-03-01

China; 2Naval Postgraduate School, Applied Mathematics Department, Monterey, CA 93943, USA; 3Science and Technology on Communication Security...in 1976 as an interesting combinatorial object with the important property of having op- timal nonlinearity [1]. Since bent functions have many...77–94 10 Zhao Y, Li H L. On bent functions with some symmet- ric properties. Discret Appl Math, 2006, 154: 2537– 2543

Chemoinformatic Analysis of Combinatorial Libraries, Drugs, Natural Products and Molecular Libraries Small Molecule Repository

PubMed Central

Singh, Narender; Guha, Rajarshi; Giulianotti, Marc; Pinilla, Clemencia; Houghten, Richard; Medina-Franco, Jose L.

2009-01-01

A multiple criteria approach is presented, that is used to perform a comparative analysis of four recently developed combinatorial libraries to drugs, Molecular Libraries Small Molecule Repository (MLSMR) and natural products. The compound databases were assessed in terms of physicochemical properties, scaffolds and fingerprints. The approach enables the analysis of property space coverage, degree of overlap between collections, scaffold and structural diversity and overall structural novelty. The degree of overlap between combinatorial libraries and drugs was assessed using the R-NN curve methodology, which measures the density of chemical space around a query molecule embedded in the chemical space of a target collection. The combinatorial libraries studied in this work exhibit scaffolds that were not observed in the drug, MLSMR and natural products collections. The fingerprint-based comparisons indicate that these combinatorial libraries are structurally different to current drugs. The R-NN curve methodology revealed that a proportion of molecules in the combinatorial libraries are located within the property space of the drugs. However, the R-NN analysis also showed that there are a significant number of molecules in several combinatorial libraries that are located in sparse regions of the drug space. PMID:19301827

Smooth Constrained Heuristic Optimization of a Combinatorial Chemical Space

DTIC Science & Technology

2015-05-01

ARL-TR-7294•MAY 2015 US Army Research Laboratory Smooth ConstrainedHeuristic Optimization of a Combinatorial Chemical Space by Berend Christopher...7294•MAY 2015 US Army Research Laboratory Smooth ConstrainedHeuristic Optimization of a Combinatorial Chemical Space by Berend Christopher...

Preparation of cherry-picked combinatorial libraries by string synthesis.

PubMed

Furka, Arpád; Dibó, Gábor; Gombosuren, Naran

2005-03-01

String synthesis [1-3] is an efficient and cheap manual method for preparation of combinatorial libraries by using macroscopic solid support units. Sorting the units between two synthetic steps is an important operation of the procedure. The software developed to guide sorting can be used only when complete combinatorial libraries are prepared. Since very often only selected components of the full libraries are needed, new software was constructed that guides sorting in preparation of non-complete combinatorial libraries. Application of the software is described in details.

Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection

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

Paiton, Dylan M.; Kenyon, Garrett T.; Brumby, Steven P.

An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using amore » combinatorial algorithm.« less

Validation of an Instrument and Testing Protocol for Measuring the Combinatorial Analysis Schema.

ERIC Educational Resources Information Center

Staver, John R.; Harty, Harold

1979-01-01

Designs a testing situation to examine the presence of combinatorial analysis, to establish construct validity in the use of an instrument, Combinatorial Analysis Behavior Observation Scheme (CABOS), and to investigate the presence of the schema in young adolescents. (Author/GA)

Large N Limits in Tensor Models: Towards More Universality Classes of Colored Triangulations in Dimension d≥2

NASA Astrophysics Data System (ADS)

Bonzom, Valentin

2016-07-01

We review an approach which aims at studying discrete (pseudo-)manifolds in dimension d≥ 2 and called random tensor models. More specifically, we insist on generalizing the two-dimensional notion of p-angulations to higher dimensions. To do so, we consider families of triangulations built out of simplices with colored faces. Those simplices can be glued to form new building blocks, called bubbles which are pseudo-manifolds with boundaries. Bubbles can in turn be glued together to form triangulations. The main challenge is to classify the triangulations built from a given set of bubbles with respect to their numbers of bubbles and simplices of codimension two. While the colored triangulations which maximize the number of simplices of codimension two at fixed number of simplices are series-parallel objects called melonic triangulations, this is not always true anymore when restricting attention to colored triangulations built from specific bubbles. This opens up the possibility of new universality classes of colored triangulations. We present three existing strategies to find those universality classes. The first two strategies consist in building new bubbles from old ones for which the problem can be solved. The third strategy is a bijection between those colored triangulations and stuffed, edge-colored maps, which are some sort of hypermaps whose hyperedges are replaced with edge-colored maps. We then show that the present approach can lead to enumeration results and identification of universality classes, by working out the example of quartic tensor models. They feature a tree-like phase, a planar phase similar to two-dimensional quantum gravity and a phase transition between them which is interpreted as a proliferation of baby universes. While this work is written in the context of random tensors, it is almost exclusively of combinatorial nature and we hope it is accessible to interested readers who are not familiar with random matrices, tensors and quantum field theory.

Combinatorial enzyme technology for the conversion of agricultural fibers to functional properties

USDA-ARS?s Scientific Manuscript database

The concept of combinatorial chemistry has received little attention in agriculture and food research, although its applications in this area were described more than fifteen years ago (1, 2). More recently, interest in the use of combinatorial chemistry in agrochemical discovery has been revitalize...

An Investigation into Post-Secondary Students' Understanding of Combinatorial Questions

ERIC Educational Resources Information Center

Bulone, Vincent William

2017-01-01

The purpose of this dissertation was to study aspects of how post-secondary students understand combinatorial problems. Within this dissertation, I considered understanding through two different lenses: i) student connections to previous problems; and ii) common combinatorial distinctions such as ordered versus unordered and repetitive versus…

Aspects of job scheduling

NASA Technical Reports Server (NTRS)

Phillips, K.

1976-01-01

A mathematical model for job scheduling in a specified context is presented. The model uses both linear programming and combinatorial methods. While designed with a view toward optimization of scheduling of facility and plant operations at the Deep Space Communications Complex, the context is sufficiently general to be widely applicable. The general scheduling problem including options for scheduling objectives is discussed and fundamental parameters identified. Mathematical algorithms for partitioning problems germane to scheduling are presented.

Stereo Reconstruction Study

DTIC Science & Technology

1983-06-01

be registered on the agenda. At each step or analysis, the action with the highest score is executed and the database is changed. The agenda controls...activation of production rules according to changes in the database . The agenda is updated whenever the database is changed. Each time, the number of...views of an object. Total prediction has combinatorial complexity. For a polyhedron with n distinct faces, there are 2" views. Instead, ACRONYM predicts

Construction of some hypergroups from combinatorial structures.

PubMed

Ashrafi, Ali Reza; Eslami-Harandi, Ahmad Reza

2003-01-01

Jajcay's studies (1993; 1994) on the automorphism groups of Cayley maps yielded a new product of groups, which he called, rotary product. Using this product, we define a hyperoperation [symbol: see text] on the group Syme(G), the stabilizer of the identity e [symbol: see text] G in the group Sym(G). We prove that (Syme(G), [symbol: see text]) is a hypergroup and characterize the subhypergroups of this hypergroup. Finally, we show that the set of all subhypergroups of Syme(G) constitute a lattice under ordinary join and meet and that the minimal elements of order two of this lattice is a subgroup of Aut(G).

Melonic Phase Transition in Group Field Theory

NASA Astrophysics Data System (ADS)

Baratin, Aristide; Carrozza, Sylvain; Oriti, Daniele; Ryan, James; Smerlak, Matteo

2014-08-01

Group field theories have recently been shown to admit a 1/N expansion dominated by so-called `melonic graphs', dual to triangulated spheres. In this note, we deepen the analysis of this melonic sector. We obtain a combinatorial formula for the melonic amplitudes in terms of a graph polynomial related to a higher-dimensional generalization of the Kirchhoff tree-matrix theorem. Simple bounds on these amplitudes show the existence of a phase transition driven by melonic interaction processes. We restrict our study to the Boulatov-Ooguri models, which describe topological BF theories and are the basis for the construction of 4-dimensional models of quantum gravity.

Optimizing Sensor and Actuator Arrays for ASAC Noise Control

NASA Technical Reports Server (NTRS)

Palumbo, Dan; Cabell, Ran

2000-01-01

This paper summarizes the development of an approach to optimizing the locations for arrays of sensors and actuators in active noise control systems. A type of directed combinatorial search, called Tabu Search, is used to select an optimal configuration from a much larger set of candidate locations. The benefit of using an optimized set is demonstrated. The importance of limiting actuator forces to realistic levels when evaluating the cost function is discussed. Results of flight testing an optimized system are presented. Although the technique has been applied primarily to Active Structural Acoustic Control systems, it can be adapted for use in other active noise control implementations.

cGRNB: a web server for building combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets.

PubMed

Xu, Huayong; Yu, Hui; Tu, Kang; Shi, Qianqian; Wei, Chaochun; Li, Yuan-Yuan; Li, Yi-Xue

2013-01-01

We are witnessing rapid progress in the development of methodologies for building the combinatorial gene regulatory networks involving both TFs (Transcription Factors) and miRNAs (microRNAs). There are a few tools available to do these jobs but most of them are not easy to use and not accessible online. A web server is especially needed in order to allow users to upload experimental expression datasets and build combinatorial regulatory networks corresponding to their particular contexts. In this work, we compiled putative TF-gene, miRNA-gene and TF-miRNA regulatory relationships from forward-engineering pipelines and curated them as built-in data libraries. We streamlined the R codes of our two separate forward-and-reverse engineering algorithms for combinatorial gene regulatory network construction and formalized them as two major functional modules. As a result, we released the cGRNB (combinatorial Gene Regulatory Networks Builder): a web server for constructing combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets. The cGRNB enables two major network-building modules, one for MPGE (miRNA-perturbed gene expression) datasets and the other for parallel miRNA/mRNA expression datasets. A miRNA-centered two-layer combinatorial regulatory cascade is the output of the first module and a comprehensive genome-wide network involving all three types of combinatorial regulations (TF-gene, TF-miRNA, and miRNA-gene) are the output of the second module. In this article we propose cGRNB, a web server for building combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets. Since parallel miRNA/mRNA expression datasets are rapidly accumulated by the advance of next-generation sequencing techniques, cGRNB will be very useful tool for researchers to build combinatorial gene regulatory networks based on expression datasets. The cGRNB web-server is free and available online at http://www.scbit.org/cgrnb.

Combinatorial effects on clumped isotopes and their significance in biogeochemistry

NASA Astrophysics Data System (ADS)

Yeung, Laurence Y.

2016-01-01

The arrangement of isotopes within a collection of molecules records their physical and chemical histories. Clumped-isotope analysis interrogates these arrangements, i.e., how often rare isotopes are bound together, which in many cases can be explained by equilibrium and/or kinetic isotope fractionation. However, purely combinatorial effects, rooted in the statistics of pairing atoms in a closed system, are also relevant, and not well understood. Here, I show that combinatorial isotope effects are most important when two identical atoms are neighbors on the same molecule (e.g., O2, N2, and D-D clumping in CH4). When the two halves of an atom pair are either assembled with different isotopic preferences or drawn from different reservoirs, combinatorial effects cause depletions in clumped-isotope abundance that are most likely between zero and -1‰, although they could potentially be -10‰ or larger for D-D pairs. These depletions are of similar magnitude, but of opposite sign, to low-temperature equilibrium clumped-isotope effects for many small molecules. Enzymatic isotope-pairing reactions, which can have site-specific isotopic fractionation factors and atom reservoirs, should express this class of combinatorial isotope effect, although it is not limited to biological reactions. Chemical-kinetic isotope effects, which are related to a bond-forming transition state, arise independently and express second-order combinatorial effects related to the abundance of the rare isotope. Heteronuclear moeties (e.g., Csbnd O and Csbnd H), are insensitive to direct combinatorial influences, but secondary combinatorial influences are evident. In general, both combinatorial and chemical-kinetic factors are important for calculating and interpreting clumped-isotope signatures of kinetically controlled reactions. I apply this analytical framework to isotope-pairing reactions relevant to geochemical oxygen, carbon, and nitrogen cycling that may be influenced by combinatorial clumped-isotope effects. These isotopic signatures, manifest as either directly bound isotope ;clumps; or as features of a molecule's isotopic anatomy, are linked to molecular mechanisms and may eventually provide additional information about biogeochemical cycling on environmentally relevant spatial scales.

Training and Transfer in Combinatorial Problem Solving: The Development of Formal Reasoning During Early Adolescence

ERIC Educational Resources Information Center

Barratt, Barnaby B.

1975-01-01

This study investigated the emergence of combinatorial competence in early adolescence and the effectiveness of a programmed discovery training procedure. Significant increases in combinatorial skill with age were shown; it was found that the expression of this skill was significantly facilitated if problems involved concrete material of low…

Invention as a combinatorial process: evidence from US patents

PubMed Central

Youn, Hyejin; Strumsky, Deborah; Bettencourt, Luis M. A.; Lobo, José

2015-01-01

Invention has been commonly conceptualized as a search over a space of combinatorial possibilities. Despite the existence of a rich literature, spanning a variety of disciplines, elaborating on the recombinant nature of invention, we lack a formal and quantitative characterization of the combinatorial process underpinning inventive activity. Here, we use US patent records dating from 1790 to 2010 to formally characterize invention as a combinatorial process. To do this, we treat patented inventions as carriers of technologies and avail ourselves of the elaborate system of technology codes used by the United States Patent and Trademark Office to classify the technologies responsible for an invention's novelty. We find that the combinatorial inventive process exhibits an invariant rate of ‘exploitation’ (refinements of existing combinations of technologies) and ‘exploration’ (the development of new technological combinations). This combinatorial dynamic contrasts sharply with the creation of new technological capabilities—the building blocks to be combined—that has significantly slowed down. We also find that, notwithstanding the very reduced rate at which new technologies are introduced, the generation of novel technological combinations engenders a practically infinite space of technological configurations. PMID:25904530

Combinatorial application of two aldehyde oxidoreductases on isobutanol production in the presence of furfural.

PubMed

Seo, Hyung-Min; Jeon, Jong-Min; Lee, Ju Hee; Song, Hun-Suk; Joo, Han-Byul; Park, Sung-Hee; Choi, Kwon-Young; Kim, Yong Hyun; Park, Kyungmoon; Ahn, Jungoh; Lee, Hongweon; Yang, Yung-Hun

2016-01-01

Furfural is a toxic by-product formulated from pretreatment processes of lignocellulosic biomass. In order to utilize the lignocellulosic biomass on isobutanol production, inhibitory effect of the furfural on isobutanol production was investigated and combinatorial application of two oxidoreductases, FucO and YqhD, was suggested as an alternative strategy. Furfural decreased cell growth and isobutanol production when only YqhD or FucO was employed as an isobutyraldehyde oxidoreductase. However, combinatorial overexpression of FucO and YqhD could overcome the inhibitory effect of furfural giving higher isobutanol production by 110% compared with overexpression of YqhD. The combinatorial oxidoreductases increased furfural detoxification rate 2.1-fold and also accelerated glucose consumption 1.4-fold. When it compares to another known system increasing furfural tolerance, membrane-bound transhydrogenase (pntAB), the combinatorial aldehyde oxidoreductases were better on cell growth and production. Thus, to control oxidoreductases is important to produce isobutanol using furfural-containing biomass and the combinatorial overexpression of FucO and YqhD can be an alternative strategy.

Combinatorial Methods for Exploring Complex Materials

NASA Astrophysics Data System (ADS)

Amis, Eric J.

2004-03-01

Combinatorial and high-throughput methods have changed the paradigm of pharmaceutical synthesis and have begun to have a similar impact on materials science research. Already there are examples of combinatorial methods used for inorganic materials, catalysts, and polymer synthesis. For many investigations the primary goal has been discovery of new material compositions that optimize properties such as phosphorescence or catalytic activity. In the midst of the excitement generated to "make things", another opportunity arises for materials science to "understand things" by using the efficiency of combinatorial methods. We have shown that combinatorial methods hold potential for rapid and systematic generation of experimental data over the multi-parameter space typical of investigations in polymer physics. We have applied the combinatorial approach to studies of polymer thin films, biomaterials, polymer blends, filled polymers, and semicrystalline polymers. By combining library fabrication, high-throughput measurements, informatics, and modeling we can demonstrate validation of the methodology, new observations, and developments toward predictive models. This talk will present some of our latest work with applications to coating stability, multi-component formulations, and nanostructure assembly.

Tumor-targeting peptides from combinatorial libraries*

PubMed Central

Liu, Ruiwu; Li, Xiaocen; Xiao, Wenwu; Lam, Kit S.

2018-01-01

Cancer is one of the major and leading causes of death worldwide. Two of the greatest challenges infighting cancer are early detection and effective treatments with no or minimum side effects. Widespread use of targeted therapies and molecular imaging in clinics requires high affinity, tumor-specific agents as effective targeting vehicles to deliver therapeutics and imaging probes to the primary or metastatic tumor sites. Combinatorial libraries such as phage-display and one-bead one-compound (OBOC) peptide libraries are powerful approaches in discovering tumor-targeting peptides. This review gives an overview of different combinatorial library technologies that have been used for the discovery of tumor-targeting peptides. Examples of tumor-targeting peptides identified from each combinatorial library method will be discussed. Published tumor-targeting peptide ligands and their applications will also be summarized by the combinatorial library methods and their corresponding binding receptors. PMID:27210583

Identification of combinatorial drug regimens for treatment of Huntington's disease using Drosophila

NASA Astrophysics Data System (ADS)

Agrawal, Namita; Pallos, Judit; Slepko, Natalia; Apostol, Barbara L.; Bodai, Laszlo; Chang, Ling-Wen; Chiang, Ann-Shyn; Michels Thompson, Leslie; Marsh, J. Lawrence

2005-03-01

We explore the hypothesis that pathology of Huntington's disease involves multiple cellular mechanisms whose contributions to disease are incrementally additive or synergistic. We provide evidence that the photoreceptor neuron degeneration seen in flies expressing mutant human huntingtin correlates with widespread degenerative events in the Drosophila CNS. We use a Drosophila Huntington's disease model to establish dose regimens and protocols to assess the effectiveness of drug combinations used at low threshold concentrations. These proof of principle studies identify at least two potential combinatorial treatment options and illustrate a rapid and cost-effective paradigm for testing and optimizing combinatorial drug therapies while reducing side effects for patients with neurodegenerative disease. The potential for using prescreening in Drosophila to inform combinatorial therapies that are most likely to be effective for testing in mammals is discussed. combinatorial treatments | neurodegeneration

Nonparametric Combinatorial Sequence Models

NASA Astrophysics Data System (ADS)

Wauthier, Fabian L.; Jordan, Michael I.; Jojic, Nebojsa

This work considers biological sequences that exhibit combinatorial structures in their composition: groups of positions of the aligned sequences are "linked" and covary as one unit across sequences. If multiple such groups exist, complex interactions can emerge between them. Sequences of this kind arise frequently in biology but methodologies for analyzing them are still being developed. This paper presents a nonparametric prior on sequences which allows combinatorial structures to emerge and which induces a posterior distribution over factorized sequence representations. We carry out experiments on three sequence datasets which indicate that combinatorial structures are indeed present and that combinatorial sequence models can more succinctly describe them than simpler mixture models. We conclude with an application to MHC binding prediction which highlights the utility of the posterior distribution induced by the prior. By integrating out the posterior our method compares favorably to leading binding predictors.

Dynamic combinatorial libraries: from exploring molecular recognition to systems chemistry.

PubMed

Li, Jianwei; Nowak, Piotr; Otto, Sijbren

2013-06-26

Dynamic combinatorial chemistry (DCC) is a subset of combinatorial chemistry where the library members interconvert continuously by exchanging building blocks with each other. Dynamic combinatorial libraries (DCLs) are powerful tools for discovering the unexpected and have given rise to many fascinating molecules, ranging from interlocked structures to self-replicators. Furthermore, dynamic combinatorial molecular networks can produce emergent properties at systems level, which provide exciting new opportunities in systems chemistry. In this perspective we will highlight some new methodologies in this field and analyze selected examples of DCLs that are under thermodynamic control, leading to synthetic receptors, catalytic systems, and complex self-assembled supramolecular architectures. Also reviewed are extensions of the principles of DCC to systems that are not at equilibrium and may therefore harbor richer functional behavior. Examples include self-replication and molecular machines.

Solar Proton Transport Within an ICRU Sphere Surrounded by a Complex Shield: Ray-trace Geometry

NASA Technical Reports Server (NTRS)

Slaba, Tony C.; Wilson, John W.; Badavi, Francis F.; Reddell, Brandon D.; Bahadori, Amir A.

2015-01-01

A computationally efficient 3DHZETRN code with enhanced neutron and light ion (Z is less than or equal to 2) propagation was recently developed for complex, inhomogeneous shield geometry described by combinatorial objects. Comparisons were made between 3DHZETRN results and Monte Carlo (MC) simulations at locations within the combinatorial geometry, and it was shown that 3DHZETRN agrees with the MC codes to the extent they agree with each other. In the present report, the 3DHZETRN code is extended to enable analysis in ray-trace geometry. This latest extension enables the code to be used within current engineering design practices utilizing fully detailed vehicle and habitat geometries. Through convergence testing, it is shown that fidelity in an actual shield geometry can be maintained in the discrete ray-trace description by systematically increasing the number of discrete rays used. It is also shown that this fidelity is carried into transport procedures and resulting exposure quantities without sacrificing computational efficiency.

Solar proton exposure of an ICRU sphere within a complex structure part II: Ray-trace geometry.

PubMed

Slaba, Tony C; Wilson, John W; Badavi, Francis F; Reddell, Brandon D; Bahadori, Amir A

2016-06-01

A computationally efficient 3DHZETRN code with enhanced neutron and light ion (Z ≤ 2) propagation was recently developed for complex, inhomogeneous shield geometry described by combinatorial objects. Comparisons were made between 3DHZETRN results and Monte Carlo (MC) simulations at locations within the combinatorial geometry, and it was shown that 3DHZETRN agrees with the MC codes to the extent they agree with each other. In the present report, the 3DHZETRN code is extended to enable analysis in ray-trace geometry. This latest extension enables the code to be used within current engineering design practices utilizing fully detailed vehicle and habitat geometries. Through convergence testing, it is shown that fidelity in an actual shield geometry can be maintained in the discrete ray-trace description by systematically increasing the number of discrete rays used. It is also shown that this fidelity is carried into transport procedures and resulting exposure quantities without sacrificing computational efficiency. Published by Elsevier Ltd.

Combinatorial anticancer effects of curcumin and sorafenib towards thyroid cancer cells via PI3K/Akt and ERK pathways.

PubMed

Zhang, Junjia; Yu, Jichun; Xie, Rong; Chen, Wanzhi; Lv, Yunxia

2016-08-01

The objective of this study was to examine the in vitro combinatorial anticancer effects of curcumin and sorafenib towards thyroid cancer cells FTC133 using a MTT cytotoxicity assay, and to test whether the mechanism involves induction of apoptosis. The present results demonstrated that curcumin at 15-25 μM dose-dependently suppressed the proliferation of FTC133. Combined treatment (curcumin (25 μM) and sorafenib (2 μM)) resulted in a reduction in cell colony formation and significantly decreased the invasion and migration of FTC133 cells compared with that treated with individual drugs. Western blot showed that the levels of p-ERK and p-Akt proteins were significantly reduced (p < 0.01) in the medicine-treated FTC133 cells. The curcumin was found to dose-dependently inhibit the apoptosis of FTC133 cells possibly via PI3K/Akt and ERK pathways. There is a synergetic antitumour effect between curcumin and sorafenib.

QAPgrid: A Two Level QAP-Based Approach for Large-Scale Data Analysis and Visualization

PubMed Central

Inostroza-Ponta, Mario; Berretta, Regina; Moscato, Pablo

2011-01-01

Background The visualization of large volumes of data is a computationally challenging task that often promises rewarding new insights. There is great potential in the application of new algorithms and models from combinatorial optimisation. Datasets often contain “hidden regularities” and a combined identification and visualization method should reveal these structures and present them in a way that helps analysis. While several methodologies exist, including those that use non-linear optimization algorithms, severe limitations exist even when working with only a few hundred objects. Methodology/Principal Findings We present a new data visualization approach (QAPgrid) that reveals patterns of similarities and differences in large datasets of objects for which a similarity measure can be computed. Objects are assigned to positions on an underlying square grid in a two-dimensional space. We use the Quadratic Assignment Problem (QAP) as a mathematical model to provide an objective function for assignment of objects to positions on the grid. We employ a Memetic Algorithm (a powerful metaheuristic) to tackle the large instances of this NP-hard combinatorial optimization problem, and we show its performance on the visualization of real data sets. Conclusions/Significance Overall, the results show that QAPgrid algorithm is able to produce a layout that represents the relationships between objects in the data set. Furthermore, it also represents the relationships between clusters that are feed into the algorithm. We apply the QAPgrid on the 84 Indo-European languages instance, producing a near-optimal layout. Next, we produce a layout of 470 world universities with an observed high degree of correlation with the score used by the Academic Ranking of World Universities compiled in the The Shanghai Jiao Tong University Academic Ranking of World Universities without the need of an ad hoc weighting of attributes. Finally, our Gene Ontology-based study on Saccharomyces cerevisiae fully demonstrates the scalability and precision of our method as a novel alternative tool for functional genomics. PMID:21267077

QAPgrid: a two level QAP-based approach for large-scale data analysis and visualization.

PubMed

Inostroza-Ponta, Mario; Berretta, Regina; Moscato, Pablo

2011-01-18

The visualization of large volumes of data is a computationally challenging task that often promises rewarding new insights. There is great potential in the application of new algorithms and models from combinatorial optimisation. Datasets often contain "hidden regularities" and a combined identification and visualization method should reveal these structures and present them in a way that helps analysis. While several methodologies exist, including those that use non-linear optimization algorithms, severe limitations exist even when working with only a few hundred objects. We present a new data visualization approach (QAPgrid) that reveals patterns of similarities and differences in large datasets of objects for which a similarity measure can be computed. Objects are assigned to positions on an underlying square grid in a two-dimensional space. We use the Quadratic Assignment Problem (QAP) as a mathematical model to provide an objective function for assignment of objects to positions on the grid. We employ a Memetic Algorithm (a powerful metaheuristic) to tackle the large instances of this NP-hard combinatorial optimization problem, and we show its performance on the visualization of real data sets. Overall, the results show that QAPgrid algorithm is able to produce a layout that represents the relationships between objects in the data set. Furthermore, it also represents the relationships between clusters that are feed into the algorithm. We apply the QAPgrid on the 84 Indo-European languages instance, producing a near-optimal layout. Next, we produce a layout of 470 world universities with an observed high degree of correlation with the score used by the Academic Ranking of World Universities compiled in the The Shanghai Jiao Tong University Academic Ranking of World Universities without the need of an ad hoc weighting of attributes. Finally, our Gene Ontology-based study on Saccharomyces cerevisiae fully demonstrates the scalability and precision of our method as a novel alternative tool for functional genomics.

Synergistic Effect of Combinatorial Treatment with Curcumin and Mitomycin C on the Induction of Apoptosis of Breast Cancer Cells: A cDNA Microarray Analysis

PubMed Central

Zhou, Qian-Mei; Chen, Qi-Long; Du, Jia; Wang, Xiu-Feng; Lu, Yi-Yu; Zhang, Hui; Su, Shi-Bing

2014-01-01

In order to explore the synergistic mechanisms of combinatorial treatment using curcumin and mitomycin C (MMC) for breast cancer, MCF-7 breast cancer xenografts were conducted to observe the synergistic effect of combinatorial treatment using curcumin and MMC at various dosages. The synergistic mechanisms of combinatorial treatment using curcumin and MMC on the inhibition of tumor growth were explored by differential gene expression profile, gene ontology (GO), ingenuity pathway analysis (IPA) and Signal–Net network analysis. The expression levels of selected genes identified by cDNA microarray expression profiling were validated by quantitative RT-PCR (qRT-PCR) and Western blot analysis. Effect of combinatorial treatment on the inhibition of cell growth was observed by MTT assay. Apoptosis was detected by flow cytometric analysis and Hoechst 33258 staining. The combinatorial treatment of 100 mg/kg curcumin and 1.5 mg/kg MMC revealed synergistic inhibition on tumor growth. Among 1501 differentially expressed genes, the expression of 25 genes exhibited an obvious change and a significant difference in 27 signal pathways was observed (p < 0.05). In addition, Mapk1 (ERK) and Mapk14 (MAPK p38) had more cross-interactions with other genes and revealed an increase in expression by 8.14- and 11.84-fold, respectively during the combinatorial treatment by curcumin and MMC when compared with the control. Moreover, curcumin can synergistically improve tumoricidal effect of MMC in another human breast cancer MDA-MB-231 cells. Apoptosis was significantly induced by the combinatorial treatment (p < 0.05) and significantly inhibited by ERK inhibitor (PD98059) in MCF-7 cells (p < 0.05). The synergistic effect of combinatorial treatment by curcumin and MMC on the induction of apoptosis in breast cancer cells may be via the ERK pathway. PMID:25226537

Identifiability of tree-child phylogenetic networks under a probabilistic recombination-mutation model of evolution.

PubMed

Francis, Andrew; Moulton, Vincent

2018-06-07

Phylogenetic networks are an extension of phylogenetic trees which are used to represent evolutionary histories in which reticulation events (such as recombination and hybridization) have occurred. A central question for such networks is that of identifiability, which essentially asks under what circumstances can we reliably identify the phylogenetic network that gave rise to the observed data? Recently, identifiability results have appeared for networks relative to a model of sequence evolution that generalizes the standard Markov models used for phylogenetic trees. However, these results are quite limited in terms of the complexity of the networks that are considered. In this paper, by introducing an alternative probabilistic model for evolution along a network that is based on some ground-breaking work by Thatte for pedigrees, we are able to obtain an identifiability result for a much larger class of phylogenetic networks (essentially the class of so-called tree-child networks). To prove our main theorem, we derive some new results for identifying tree-child networks combinatorially, and then adapt some techniques developed by Thatte for pedigrees to show that our combinatorial results imply identifiability in the probabilistic setting. We hope that the introduction of our new model for networks could lead to new approaches to reliably construct phylogenetic networks. Copyright © 2018 Elsevier Ltd. All rights reserved.

Combinatorial theory of Macdonald polynomials I: proof of Haglund's formula.

PubMed

Haglund, J; Haiman, M; Loehr, N

2005-02-22

Haglund recently proposed a combinatorial interpretation of the modified Macdonald polynomials H(mu). We give a combinatorial proof of this conjecture, which establishes the existence and integrality of H(mu). As corollaries, we obtain the cocharge formula of Lascoux and Schutzenberger for Hall-Littlewood polynomials, a formula of Sahi and Knop for Jack's symmetric functions, a generalization of this result to the integral Macdonald polynomials J(mu), a formula for H(mu) in terms of Lascoux-Leclerc-Thibon polynomials, and combinatorial expressions for the Kostka-Macdonald coefficients K(lambda,mu) when mu is a two-column shape.

Anticlockwise or clockwise? A dynamic Perception-Action-Laterality model for directionality bias in visuospatial functioning.

PubMed

Karim, A K M Rezaul; Proulx, Michael J; Likova, Lora T

2016-09-01

Orientation bias and directionality bias are two fundamental functional characteristics of the visual system. Reviewing the relevant literature in visual psychophysics and visual neuroscience we propose here a three-stage model of directionality bias in visuospatial functioning. We call this model the 'Perception-Action-Laterality' (PAL) hypothesis. We analyzed the research findings for a wide range of visuospatial tasks, showing that there are two major directionality trends in perceptual preference: clockwise versus anticlockwise. It appears these preferences are combinatorial, such that a majority of people fall in the first category demonstrating a preference for stimuli/objects arranged from left-to-right rather than from right-to-left, while people in the second category show an opposite trend. These perceptual biases can guide sensorimotor integration and action, creating two corresponding turner groups in the population. In support of PAL, we propose another model explaining the origins of the biases - how the neurogenetic factors and the cultural factors interact in a biased competition framework to determine the direction and extent of biases. This dynamic model can explain not only the two major categories of biases in terms of direction and strength, but also the unbiased, unreliably biased or mildly biased cases in visuosptial functioning. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Hybridization of decomposition and local search for multiobjective optimization.

PubMed

Ke, Liangjun; Zhang, Qingfu; Battiti, Roberto

2014-10-01

Combining ideas from evolutionary algorithms, decomposition approaches, and Pareto local search, this paper suggests a simple yet efficient memetic algorithm for combinatorial multiobjective optimization problems: memetic algorithm based on decomposition (MOMAD). It decomposes a combinatorial multiobjective problem into a number of single objective optimization problems using an aggregation method. MOMAD evolves three populations: 1) population P(L) for recording the current solution to each subproblem; 2) population P(P) for storing starting solutions for Pareto local search; and 3) an external population P(E) for maintaining all the nondominated solutions found so far during the search. A problem-specific single objective heuristic can be applied to these subproblems to initialize the three populations. At each generation, a Pareto local search method is first applied to search a neighborhood of each solution in P(P) to update P(L) and P(E). Then a single objective local search is applied to each perturbed solution in P(L) for improving P(L) and P(E), and reinitializing P(P). The procedure is repeated until a stopping condition is met. MOMAD provides a generic hybrid multiobjective algorithmic framework in which problem specific knowledge, well developed single objective local search and heuristics and Pareto local search methods can be hybridized. It is a population based iterative method and thus an anytime algorithm. Extensive experiments have been conducted in this paper to study MOMAD and compare it with some other state-of-the-art algorithms on the multiobjective traveling salesman problem and the multiobjective knapsack problem. The experimental results show that our proposed algorithm outperforms or performs similarly to the best so far heuristics on these two problems.

Signal dimensionality and the emergence of combinatorial structure.

PubMed

Little, Hannah; Eryılmaz, Kerem; de Boer, Bart

2017-11-01

In language, a small number of meaningless building blocks can be combined into an unlimited set of meaningful utterances. This is known as combinatorial structure. One hypothesis for the initial emergence of combinatorial structure in language is that recombining elements of signals solves the problem of overcrowding in a signal space. Another hypothesis is that iconicity may impede the emergence of combinatorial structure. However, how these two hypotheses relate to each other is not often discussed. In this paper, we explore how signal space dimensionality relates to both overcrowding in the signal space and iconicity. We use an artificial signalling experiment to test whether a signal space and a meaning space having similar topologies will generate an iconic system and whether, when the topologies differ, the emergence of combinatorially structured signals is facilitated. In our experiments, signals are created from participants' hand movements, which are measured using an infrared sensor. We found that participants take advantage of iconic signal-meaning mappings where possible. Further, we use trajectory predictability, measures of variance, and Hidden Markov Models to measure the use of structure within the signals produced and found that when topologies do not match, then there is more evidence of combinatorial structure. The results from these experiments are interpreted in the context of the differences between the emergence of combinatorial structure in different linguistic modalities (speech and sign). Copyright © 2017 Elsevier B.V. All rights reserved.

To Think without Thinking: The Implications of Combinatory Play and the Creative Process for Neuroaesthetics

ERIC Educational Resources Information Center

Stevens, Victoria

2014-01-01

The author considers combinatory play as an intersection between creativity, play, and neuroaesthetics. She discusses combinatory play as vital to the creative process in art and science, particularly with regard to the incubation of new ideas. She reviews findings from current neurobiological research and outlines the way that the brain activates…

Heterogeneous Catalysis: Understanding for Designing, and Designing for Applications.

PubMed

Corma, Avelino

2016-05-17

"… Despite the introduction of high-throughput and combinatorial methods that certainly can be useful in the process of catalysts optimization, it is recognized that the generation of fundamental knowledge at the molecular level is key for the development of new concepts and for reaching the final objective of solid catalysts by design …" Read more in the Editorial by Avelino Corma. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Investigation and Implementation of Matrix Permanent Algorithms for Identity Resolution

DTIC Science & Technology

2014-12-01

calculation of the permanent of a matrix whose dimension is a function of target count [21]. However, the optimal approach for computing the permanent is...presently unclear. The primary objective of this project was to determine the optimal computing strategy(-ies) for the matrix permanent in tactical and...solving various combinatorial problems (see [16] for details and appli- cations to a wide variety of problems) and thus can be applied to compute a

Combinatorial genetic perturbation to refine metabolic circuits for producing biofuels and biochemicals.

PubMed

Kim, Hyo Jin; Turner, Timothy Lee; Jin, Yong-Su

2013-11-01

Recent advances in metabolic engineering have enabled microbial factories to compete with conventional processes for producing fuels and chemicals. Both rational and combinatorial approaches coupled with synthetic and systematic tools play central roles in metabolic engineering to create and improve a selected microbial phenotype. Compared to knowledge-based rational approaches, combinatorial approaches exploiting biological diversity and high-throughput screening have been demonstrated as more effective tools for improving various phenotypes of interest. In particular, identification of unprecedented targets to rewire metabolic circuits for maximizing yield and productivity of a target chemical has been made possible. This review highlights general principles and the features of the combinatorial approaches using various libraries to implement desired phenotypes for strain improvement. In addition, recent applications that harnessed the combinatorial approaches to produce biofuels and biochemicals will be discussed. Copyright © 2013 Elsevier Inc. All rights reserved.

Tumor-targeting peptides from combinatorial libraries.

PubMed

Liu, Ruiwu; Li, Xiaocen; Xiao, Wenwu; Lam, Kit S

2017-02-01

Cancer is one of the major and leading causes of death worldwide. Two of the greatest challenges in fighting cancer are early detection and effective treatments with no or minimum side effects. Widespread use of targeted therapies and molecular imaging in clinics requires high affinity, tumor-specific agents as effective targeting vehicles to deliver therapeutics and imaging probes to the primary or metastatic tumor sites. Combinatorial libraries such as phage-display and one-bead one-compound (OBOC) peptide libraries are powerful approaches in discovering tumor-targeting peptides. This review gives an overview of different combinatorial library technologies that have been used for the discovery of tumor-targeting peptides. Examples of tumor-targeting peptides identified from each combinatorial library method will be discussed. Published tumor-targeting peptide ligands and their applications will also be summarized by the combinatorial library methods and their corresponding binding receptors. Copyright © 2017. Published by Elsevier B.V.

Morphological Constraints on Cerebellar Granule Cell Combinatorial Diversity.

PubMed

Gilmer, Jesse I; Person, Abigail L

2017-12-13

Combinatorial expansion by the cerebellar granule cell layer (GCL) is fundamental to theories of cerebellar contributions to motor control and learning. Granule cells (GrCs) sample approximately four mossy fiber inputs and are thought to form a combinatorial code useful for pattern separation and learning. We constructed a spatially realistic model of the cerebellar GCL and examined how GCL architecture contributes to GrC combinatorial diversity. We found that GrC combinatorial diversity saturates quickly as mossy fiber input diversity increases, and that this saturation is in part a consequence of short dendrites, which limit access to diverse inputs and favor dense sampling of local inputs. This local sampling also produced GrCs that were combinatorially redundant, even when input diversity was extremely high. In addition, we found that mossy fiber clustering, which is a common anatomical pattern, also led to increased redundancy of GrC input combinations. We related this redundancy to hypothesized roles of temporal expansion of GrC information encoding in service of learned timing, and we show that GCL architecture produces GrC populations that support both temporal and combinatorial expansion. Finally, we used novel anatomical measurements from mice of either sex to inform modeling of sparse and filopodia-bearing mossy fibers, finding that these circuit features uniquely contribute to enhancing GrC diversification and redundancy. Our results complement information theoretic studies of granule layer structure and provide insight into the contributions of granule layer anatomical features to afferent mixing. SIGNIFICANCE STATEMENT Cerebellar granule cells are among the simplest neurons, with tiny somata and, on average, just four dendrites. These characteristics, along with their dense organization, inspired influential theoretical work on the granule cell layer as a combinatorial expander, where each granule cell represents a unique combination of inputs. Despite the centrality of these theories to cerebellar physiology, the degree of expansion supported by anatomically realistic patterns of inputs is unknown. Using modeling and anatomy, we show that realistic input patterns constrain combinatorial diversity by producing redundant combinations, which nevertheless could support temporal diversification of like combinations, suitable for learned timing. Our study suggests a neural substrate for producing high levels of both combinatorial and temporal diversity in the granule cell layer. Copyright © 2017 the authors 0270-6474/17/3712153-14$15.00/0.

Application of computer assisted combinatorial chemistry in antivirial, antimalarial and anticancer agents design

NASA Astrophysics Data System (ADS)

Burello, E.; Bologa, C.; Frecer, V.; Miertus, S.

Combinatorial chemistry and technologies have been developed to a stage where synthetic schemes are available for generation of a large variety of organic molecules. The innovative concept of combinatorial design assumes that screening of a large and diverse library of compounds will increase the probability of finding an active analogue among the compounds tested. Since the rate at which libraries are screened for activity currently constitutes a limitation to the use of combinatorial technologies, it is important to be selective about the number of compounds to be synthesized. Early experience with combinatorial chemistry indicated that chemical diversity alone did not result in a significant increase in the number of generated lead compounds. Emphasis has therefore been increasingly put on the use of computer assisted combinatorial chemical techniques. Computational methods are valuable in the design of virtual libraries of molecular models. Selection strategies based on computed physicochemical properties of the models or of a target compound are introduced to reduce the time and costs of library synthesis and screening. In addition, computational structure-based library focusing methods can be used to perform in silico screening of the activity of compounds against a target receptor by docking the ligands into the receptor model. Three case studies are discussed dealing with the design of targeted combinatorial libraries of inhibitors of HIV-1 protease, P. falciparum plasmepsin and human urokinase as potential antivirial, antimalarial and anticancer drugs. These illustrate library focusing strategies.

Amoeba-inspired nanoarchitectonic computing implemented using electrical Brownian ratchets.

PubMed

Aono, M; Kasai, S; Kim, S-J; Wakabayashi, M; Miwa, H; Naruse, M

2015-06-12

In this study, we extracted the essential spatiotemporal dynamics that allow an amoeboid organism to solve a computationally demanding problem and adapt to its environment, thereby proposing a nature-inspired nanoarchitectonic computing system, which we implemented using a network of nanowire devices called 'electrical Brownian ratchets (EBRs)'. By utilizing the fluctuations generated from thermal energy in nanowire devices, we used our system to solve the satisfiability problem, which is a highly complex combinatorial problem related to a wide variety of practical applications. We evaluated the dependency of the solution search speed on its exploration parameter, which characterizes the fluctuation intensity of EBRs, using a simulation model of our system called 'AmoebaSAT-Brownian'. We found that AmoebaSAT-Brownian enhanced the solution searching speed dramatically when we imposed some constraints on the fluctuations in its time series and it outperformed a well-known stochastic local search method. These results suggest a new computing paradigm, which may allow high-speed problem solving to be implemented by interacting nanoscale devices with low power consumption.

MDTS: automatic complex materials design using Monte Carlo tree search.

PubMed

M Dieb, Thaer; Ju, Shenghong; Yoshizoe, Kazuki; Hou, Zhufeng; Shiomi, Junichiro; Tsuda, Koji

2017-01-01

Complex materials design is often represented as a black-box combinatorial optimization problem. In this paper, we present a novel python library called MDTS (Materials Design using Tree Search). Our algorithm employs a Monte Carlo tree search approach, which has shown exceptional performance in computer Go game. Unlike evolutionary algorithms that require user intervention to set parameters appropriately, MDTS has no tuning parameters and works autonomously in various problems. In comparison to a Bayesian optimization package, our algorithm showed competitive search efficiency and superior scalability. We succeeded in designing large Silicon-Germanium (Si-Ge) alloy structures that Bayesian optimization could not deal with due to excessive computational cost. MDTS is available at https://github.com/tsudalab/MDTS.

MDTS: automatic complex materials design using Monte Carlo tree search

NASA Astrophysics Data System (ADS)

Dieb, Thaer M.; Ju, Shenghong; Yoshizoe, Kazuki; Hou, Zhufeng; Shiomi, Junichiro; Tsuda, Koji

2017-12-01

Complex materials design is often represented as a black-box combinatorial optimization problem. In this paper, we present a novel python library called MDTS (Materials Design using Tree Search). Our algorithm employs a Monte Carlo tree search approach, which has shown exceptional performance in computer Go game. Unlike evolutionary algorithms that require user intervention to set parameters appropriately, MDTS has no tuning parameters and works autonomously in various problems. In comparison to a Bayesian optimization package, our algorithm showed competitive search efficiency and superior scalability. We succeeded in designing large Silicon-Germanium (Si-Ge) alloy structures that Bayesian optimization could not deal with due to excessive computational cost. MDTS is available at https://github.com/tsudalab/MDTS.

Microscopic description of pair transfer between two superfluid Fermi systems: Combining phase-space averaging and combinatorial techniques

NASA Astrophysics Data System (ADS)

Regnier, David; Lacroix, Denis; Scamps, Guillaume; Hashimoto, Yukio

2018-03-01

In a mean-field description of superfluidity, particle number and gauge angle are treated as quasiclassical conjugated variables. This level of description was recently used to describe nuclear reactions around the Coulomb barrier. Important effects of the relative gauge angle between two identical superfluid nuclei (symmetric collisions) on transfer probabilities and fusion barrier have been uncovered. A theory making contact with experiments should at least average over different initial relative gauge-angles. In the present work, we propose a new approach to obtain the multiple pair transfer probabilities between superfluid systems. This method, called phase-space combinatorial (PSC) technique, relies both on phase-space averaging and combinatorial arguments to infer the full pair transfer probability distribution at the cost of multiple mean-field calculations only. After benchmarking this approach in a schematic model, we apply it to the collision 20O+20O at various energies below the Coulomb barrier. The predictions for one pair transfer are similar to results obtained with an approximated projection method, whereas significant differences are found for two pairs transfer. Finally, we investigated the applicability of the PSC method to the contact between nonidentical superfluid systems. A generalization of the method is proposed and applied to the schematic model showing that the pair transfer probabilities are reasonably reproduced. The applicability of the PSC method to asymmetric nuclear collisions is investigated for the 14O+20O collision and it turns out that unrealistically small single- and multiple pair transfer probabilities are obtained. This is explained by the fact that relative gauge angle play in this case a minor role in the particle transfer process compared to other mechanisms, such as equilibration of the charge/mass ratio. We conclude that the best ground for probing gauge-angle effects in nuclear reaction and/or for applying the proposed PSC approach on pair transfer is the collisions of identical open-shell spherical nuclei.

δ-Similar Elimination to Enhance Search Performance of Multiobjective Evolutionary Algorithms

NASA Astrophysics Data System (ADS)

Aguirre, Hernán; Sato, Masahiko; Tanaka, Kiyoshi

In this paper, we propose δ-similar elimination to improve the search performance of multiobjective evolutionary algorithms in combinatorial optimization problems. This method eliminates similar individuals in objective space to fairly distribute selection among the different regions of the instantaneous Pareto front. We investigate four eliminating methods analyzing their effects using NSGA-II. In addition, we compare the search performance of NSGA-II enhanced by our method and NSGA-II enhanced by controlled elitism.

Metronidazole as a protector of cells from electromagnetic radiation of extremely high frequencies

NASA Astrophysics Data System (ADS)

Kuznetsov, Pavel E.; Malinina, Ulia A.; Popyhova, Era B.; Rogacheva, Svetlana M.; Somov, Alexander U.

2006-08-01

It is well known that weak electromagnetic fields of extremely high frequencies cause significant modification of the functional status of biological objects of different levels of organization. The aim of the work was to study the combinatory effect of metronidazole - the drug form of 1-(2'hydroxiethil)-2-methil-5-nitroimidazole - and electromagnetic radiation of extremely high frequencies (52...75 GHz) on the hemolytic stability of erythrocytes and hemotaxis activity of Infusoria Paramecium caudatum.

Inferring the Why in Images

DTIC Science & Technology

2014-01-01

model. We combinatorially replaced tokens with words from our vocabulary to score the relationships be- tween concepts. The second-order queries (not...is the action, y3 is an object, and y4 is the scene. Language Potentials: We captialize on state-of-the-art natural language models to score the rela...model estimated on billions of web-pages [4, 10] to form each L(·). Scoring Function: Given the image x, we score a possible labeling configuration y of

Combinatorial chemistry has matured in the last three decades: dedicated to Professor Árpád Furka on the occasion of his 80th birthday.

PubMed

Dibó, Gábor

2012-02-01

Combinatorial chemistry was introduced in the 1980s. It provided the possibility to produce new compounds in practically unlimited number. New strategies and technologies have also been developed that made it possible to screen very large number of compounds and to identify useful components in mixtures containing millions of different substances. This dramatically changed the drug discovery process and the way of thinking of synthetic chemists. In addition, combinatorial strategies became useful in areas such as pharmaceutical research, agrochemistry, catalyst design, and materials research. Prof. Árpád Furka is one of the pioneers of combinatorial chemistry.

Construction of a virtual combinatorial library using SMILES strings to discover potential structure-diverse PPAR modulators.

PubMed

Liao, Chenzhong; Liu, Bing; Shi, Leming; Zhou, Jiaju; Lu, Xian-Ping

2005-07-01

Based on the structural characters of PPAR modulators, a virtual combinatorial library containing 1226,625 compounds was constructed using SMILES strings. Selected ADME filters were employed to compel compounds having poor drug-like properties from this library. This library was converted to sdf and mol2 files by CONCORD 4.0, and was then docked to PPARgamma by DOCK 4.0 to identify new chemical entities that may be potential drug leads against type 2 diabetes and other metabolic diseases. The method to construct virtual combinatorial library using SMILES strings was further visualized by Visual Basic.net that can facilitate the needs of generating other type virtual combinatorial libraries.

Meaningful call combinations and compositional processing in the southern pied babbler

PubMed Central

Engesser, Sabrina; Ridley, Amanda R.; Townsend, Simon W.

2016-01-01

Language’s expressive power is largely attributable to its compositionality: meaningful words are combined into larger/higher-order structures with derived meaning. Despite its importance, little is known regarding the evolutionary origins and emergence of this syntactic ability. Although previous research has shown a rudimentary capability to combine meaningful calls in primates, because of a scarcity of comparative data, it is unclear to what extent analog forms might also exist outside of primates. Here, we address this ambiguity and provide evidence for rudimentary compositionality in the discrete vocal system of a social passerine, the pied babbler (Turdoides bicolor). Natural observations and predator presentations revealed that babblers produce acoustically distinct alert calls in response to close, low-urgency threats and recruitment calls when recruiting group members during locomotion. On encountering terrestrial predators, both vocalizations are combined into a “mobbing sequence,” potentially to recruit group members in a dangerous situation. To investigate whether babblers process the sequence in a compositional way, we conducted systematic experiments, playing back the individual calls in isolation as well as naturally occurring and artificial sequences. Babblers reacted most strongly to mobbing sequence playbacks, showing a greater attentiveness and a quicker approach to the loudspeaker, compared with individual calls or control sequences. We conclude that the sequence constitutes a compositional structure, communicating information on both the context and the requested action. Our work supports previous research suggesting combinatoriality as a viable mechanism to increase communicative output and indicates that the ability to combine and process meaningful vocal structures, a basic syntax, may be more widespread than previously thought. PMID:27155011

Meaningful call combinations and compositional processing in the southern pied babbler.

PubMed

Engesser, Sabrina; Ridley, Amanda R; Townsend, Simon W

2016-05-24

Language's expressive power is largely attributable to its compositionality: meaningful words are combined into larger/higher-order structures with derived meaning. Despite its importance, little is known regarding the evolutionary origins and emergence of this syntactic ability. Although previous research has shown a rudimentary capability to combine meaningful calls in primates, because of a scarcity of comparative data, it is unclear to what extent analog forms might also exist outside of primates. Here, we address this ambiguity and provide evidence for rudimentary compositionality in the discrete vocal system of a social passerine, the pied babbler (Turdoides bicolor). Natural observations and predator presentations revealed that babblers produce acoustically distinct alert calls in response to close, low-urgency threats and recruitment calls when recruiting group members during locomotion. On encountering terrestrial predators, both vocalizations are combined into a "mobbing sequence," potentially to recruit group members in a dangerous situation. To investigate whether babblers process the sequence in a compositional way, we conducted systematic experiments, playing back the individual calls in isolation as well as naturally occurring and artificial sequences. Babblers reacted most strongly to mobbing sequence playbacks, showing a greater attentiveness and a quicker approach to the loudspeaker, compared with individual calls or control sequences. We conclude that the sequence constitutes a compositional structure, communicating information on both the context and the requested action. Our work supports previous research suggesting combinatoriality as a viable mechanism to increase communicative output and indicates that the ability to combine and process meaningful vocal structures, a basic syntax, may be more widespread than previously thought.

Systematic Identification of Combinatorial Drivers and Targets in Cancer Cell Lines

PubMed Central

Tabchy, Adel; Eltonsy, Nevine; Housman, David E.; Mills, Gordon B.

2013-01-01

There is an urgent need to elicit and validate highly efficacious targets for combinatorial intervention from large scale ongoing molecular characterization efforts of tumors. We established an in silico bioinformatic platform in concert with a high throughput screening platform evaluating 37 novel targeted agents in 669 extensively characterized cancer cell lines reflecting the genomic and tissue-type diversity of human cancers, to systematically identify combinatorial biomarkers of response and co-actionable targets in cancer. Genomic biomarkers discovered in a 141 cell line training set were validated in an independent 359 cell line test set. We identified co-occurring and mutually exclusive genomic events that represent potential drivers and combinatorial targets in cancer. We demonstrate multiple cooperating genomic events that predict sensitivity to drug intervention independent of tumor lineage. The coupling of scalable in silico and biologic high throughput cancer cell line platforms for the identification of co-events in cancer delivers rational combinatorial targets for synthetic lethal approaches with a high potential to pre-empt the emergence of resistance. PMID:23577104

Systematic identification of combinatorial drivers and targets in cancer cell lines.

PubMed

Tabchy, Adel; Eltonsy, Nevine; Housman, David E; Mills, Gordon B

2013-01-01

There is an urgent need to elicit and validate highly efficacious targets for combinatorial intervention from large scale ongoing molecular characterization efforts of tumors. We established an in silico bioinformatic platform in concert with a high throughput screening platform evaluating 37 novel targeted agents in 669 extensively characterized cancer cell lines reflecting the genomic and tissue-type diversity of human cancers, to systematically identify combinatorial biomarkers of response and co-actionable targets in cancer. Genomic biomarkers discovered in a 141 cell line training set were validated in an independent 359 cell line test set. We identified co-occurring and mutually exclusive genomic events that represent potential drivers and combinatorial targets in cancer. We demonstrate multiple cooperating genomic events that predict sensitivity to drug intervention independent of tumor lineage. The coupling of scalable in silico and biologic high throughput cancer cell line platforms for the identification of co-events in cancer delivers rational combinatorial targets for synthetic lethal approaches with a high potential to pre-empt the emergence of resistance.

An evaluation of methods for estimating the number of local optima in combinatorial optimization problems.

PubMed

Hernando, Leticia; Mendiburu, Alexander; Lozano, Jose A

2013-01-01

The solution of many combinatorial optimization problems is carried out by metaheuristics, which generally make use of local search algorithms. These algorithms use some kind of neighborhood structure over the search space. The performance of the algorithms strongly depends on the properties that the neighborhood imposes on the search space. One of these properties is the number of local optima. Given an instance of a combinatorial optimization problem and a neighborhood, the estimation of the number of local optima can help not only to measure the complexity of the instance, but also to choose the most convenient neighborhood to solve it. In this paper we review and evaluate several methods to estimate the number of local optima in combinatorial optimization problems. The methods reviewed not only come from the combinatorial optimization literature, but also from the statistical literature. A thorough evaluation in synthetic as well as real problems is given. We conclude by providing recommendations of methods for several scenarios.

Combinatorial materials approach to accelerate materials discovery for transportation (Conference Presentation)

NASA Astrophysics Data System (ADS)

Tong, Wei

2017-04-01

Combinatorial material research offers fast and efficient solutions to identify promising and advanced materials. It has revolutionized the pharmaceutical industry and now is being applied to accelerate the discovery of other new compounds, e.g. superconductors, luminescent materials, catalysts etc. Differing from the traditional trial-and-error process, this approach allows for the synthesis of a large number of compositionally diverse compounds by varying the combinations of the components and adjusting the ratios. It largely reduces the cost of single-sample synthesis/characterization, along with the turnaround time in the material discovery process, therefore, could dramatically change the existing paradigm for discovering and commercializing new materials. This talk outlines the use of combinatorial materials approach in the material discovery in transportation sector. It covers the general introduction to the combinatorial material concept, state of art for its application in energy-related research. At the end, LBNL capabilities in combinatorial materials synthesis and high throughput characterization that are applicable for material discovery research will be highlighted.

Discovery of the leinamycin family of natural products by mining actinobacterial genomes

PubMed Central

Xu, Zhengren; Guo, Zhikai; Hindra; Ma, Ming; Zhou, Hao; Gansemans, Yannick; Zhu, Xiangcheng; Huang, Yong; Zhao, Li-Xing; Jiang, Yi; Cheng, Jinhua; Van Nieuwerburgh, Filip; Suh, Joo-Won; Duan, Yanwen

2017-01-01

Nature’s ability to generate diverse natural products from simple building blocks has inspired combinatorial biosynthesis. The knowledge-based approach to combinatorial biosynthesis has allowed the production of designer analogs by rational metabolic pathway engineering. While successful, structural alterations are limited, with designer analogs often produced in compromised titers. The discovery-based approach to combinatorial biosynthesis complements the knowledge-based approach by exploring the vast combinatorial biosynthesis repertoire found in Nature. Here we showcase the discovery-based approach to combinatorial biosynthesis by targeting the domain of unknown function and cysteine lyase domain (DUF–SH) didomain, specific for sulfur incorporation from the leinamycin (LNM) biosynthetic machinery, to discover the LNM family of natural products. By mining bacterial genomes from public databases and the actinomycetes strain collection at The Scripps Research Institute, we discovered 49 potential producers that could be grouped into 18 distinct clades based on phylogenetic analysis of the DUF–SH didomains. Further analysis of the representative genomes from each of the clades identified 28 lnm-type gene clusters. Structural diversities encoded by the LNM-type biosynthetic machineries were predicted based on bioinformatics and confirmed by in vitro characterization of selected adenylation proteins and isolation and structural elucidation of the guangnanmycins and weishanmycins. These findings demonstrate the power of the discovery-based approach to combinatorial biosynthesis for natural product discovery and structural diversity and highlight Nature’s rich biosynthetic repertoire. Comparative analysis of the LNM-type biosynthetic machineries provides outstanding opportunities to dissect Nature’s biosynthetic strategies and apply these findings to combinatorial biosynthesis for natural product discovery and structural diversity. PMID:29229819

Discovery of the leinamycin family of natural products by mining actinobacterial genomes.

PubMed

Pan, Guohui; Xu, Zhengren; Guo, Zhikai; Hindra; Ma, Ming; Yang, Dong; Zhou, Hao; Gansemans, Yannick; Zhu, Xiangcheng; Huang, Yong; Zhao, Li-Xing; Jiang, Yi; Cheng, Jinhua; Van Nieuwerburgh, Filip; Suh, Joo-Won; Duan, Yanwen; Shen, Ben

2017-12-26

Nature's ability to generate diverse natural products from simple building blocks has inspired combinatorial biosynthesis. The knowledge-based approach to combinatorial biosynthesis has allowed the production of designer analogs by rational metabolic pathway engineering. While successful, structural alterations are limited, with designer analogs often produced in compromised titers. The discovery-based approach to combinatorial biosynthesis complements the knowledge-based approach by exploring the vast combinatorial biosynthesis repertoire found in Nature. Here we showcase the discovery-based approach to combinatorial biosynthesis by targeting the domain of unknown function and cysteine lyase domain (DUF-SH) didomain, specific for sulfur incorporation from the leinamycin (LNM) biosynthetic machinery, to discover the LNM family of natural products. By mining bacterial genomes from public databases and the actinomycetes strain collection at The Scripps Research Institute, we discovered 49 potential producers that could be grouped into 18 distinct clades based on phylogenetic analysis of the DUF-SH didomains. Further analysis of the representative genomes from each of the clades identified 28 lnm -type gene clusters. Structural diversities encoded by the LNM-type biosynthetic machineries were predicted based on bioinformatics and confirmed by in vitro characterization of selected adenylation proteins and isolation and structural elucidation of the guangnanmycins and weishanmycins. These findings demonstrate the power of the discovery-based approach to combinatorial biosynthesis for natural product discovery and structural diversity and highlight Nature's rich biosynthetic repertoire. Comparative analysis of the LNM-type biosynthetic machineries provides outstanding opportunities to dissect Nature's biosynthetic strategies and apply these findings to combinatorial biosynthesis for natural product discovery and structural diversity.

Combinatorial pretreatment and fermentation optimization enabled a record yield on lignin bioconversion.

PubMed

Liu, Zhi-Hua; Xie, Shangxian; Lin, Furong; Jin, Mingjie; Yuan, Joshua S

2018-01-01

Lignin valorization has recently been considered to be an essential process for sustainable and cost-effective biorefineries. Lignin represents a potential new feedstock for value-added products. Oleaginous bacteria such as Rhodococcus opacus can produce intracellular lipids from biodegradation of aromatic substrates. These lipids can be used for biofuel production, which can potentially replace petroleum-derived chemicals. However, the low reactivity of lignin produced from pretreatment and the underdeveloped fermentation technology hindered lignin bioconversion to lipids. In this study, combinatorial pretreatment with an optimized fermentation strategy was evaluated to improve lignin valorization into lipids using R. opacus PD630. As opposed to single pretreatment, combinatorial pretreatment produced a 12.8-75.6% higher lipid concentration in fermentation using lignin as the carbon source. Gas chromatography-mass spectrometry analysis showed that combinatorial pretreatment released more aromatic monomers, which could be more readily utilized by lignin-degrading strains. Three detoxification strategies were used to remove potential inhibitors produced from pretreatment. After heating detoxification of the lignin stream, the lipid concentration further increased by 2.9-9.7%. Different fermentation strategies were evaluated in scale-up lipid fermentation using a 2.0-l fermenter. With laccase treatment of the lignin stream produced from combinatorial pretreatment, the highest cell dry weight and lipid concentration were 10.1 and 1.83 g/l, respectively, in fed-batch fermentation, with a total soluble substrate concentration of 40 g/l. The improvement of the lipid fermentation performance may have resulted from lignin depolymerization by the combinatorial pretreatment and laccase treatment, reduced inhibition effects by fed-batch fermentation, adequate oxygen supply, and an accurate pH control in the fermenter. Overall, these results demonstrate that combinatorial pretreatment, together with fermentation optimization, favorably improves lipid production using lignin as the carbon source. Combinatorial pretreatment integrated with fed-batch fermentation was an effective strategy to improve the bioconversion of lignin into lipids, thus facilitating lignin valorization in biorefineries.

An Indexed Combinatorial Library: The Synthesis and Testing of Insect Repellents

NASA Astrophysics Data System (ADS)

Miles, William H.; Gelato, Kathy A.; Pompizzi, Kristen M.; Scarbinsky, Aislinn M.; Albrecht, Brian K.; Reynolds, Elaine R.

2001-04-01

An indexed combinatorial library of amides was prepared by the reaction of amines and acid chlorides. A simple test for insect repellency using fruit flies (Drosophila melanogaster) allowed the determination of the most repellent sublibraries. The student-generated data were collected and analyzed to determine the most active amide(s) in the library. This experiment illustrates the fundamentals of combinatorial chemistry, a field that has undergone explosive growth in the last decade.

Abductive networks applied to electronic combat

NASA Astrophysics Data System (ADS)

Montgomery, Gerard J.; Hess, Paul; Hwang, Jong S.

1990-08-01

A practical approach to dealing with combinatorial decision problems and uncertainties associated with electronic combat through the use of networks of high-level functional elements called abductive networks is presented. It describes the application of the Abductory Induction Mechanism (AIMTM) a supervised inductive learning tool for synthesizing polynomial abductive networks to the electronic combat problem domain. From databases of historical expert-generated or simulated combat engagements AIM can often induce compact and robust network models for making effective real-time electronic combat decisions despite significant uncertainties or a combinatorial explosion of possible situations. The feasibility of applying abductive networks to realize advanced combat decision aiding capabilities was demonstrated by applying AIM to a set of electronic combat simulations. The networks synthesized by AIM generated accurate assessments of the intent lethality and overall risk associated with a variety of simulated threats and produced reasonable estimates of the expected effectiveness of a group of electronic countermeasures for a large number of simulated combat scenarios. This paper presents the application of abductive networks to electronic combat summarizes the results of experiments performed using AIM discusses the benefits and limitations of applying abductive networks to electronic combat and indicates why abductive networks can often result in capabilities not attainable using alternative approaches. 1. ELECTRONIC COMBAT. UNCERTAINTY. AND MACHINE LEARNING Electronic combat has become an essential part of the ability to make war and has become increasingly complex since

On Some Algebraic and Combinatorial Properties of Dunkl Elements

NASA Astrophysics Data System (ADS)

Kirillov, Anatol N.

2013-06-01

We introduce and study a certain class of nonhomogeneous quadratic algebras together with the special set of mutually commuting elements inside of each, the so-called Dunkl elements. We describe relations among the Dunkl elements. This result is a further generalization of similar results obtained in [S. Fomin and A. N. Kirillov, Quadratic algebras, Dunkl elements and Schubert calculus, in Advances in Geometry (eds. J.-S. Brylinski, V. Nistor, B. Tsygan and P. Xu), Progress in Math. Vol. 172 (Birkhäuser Boston, Boston, 1995), pp. 147-182, A. Postnikov, On a quantum version of Pieri's formula, in Advances in Geometry (eds. J.-S. Brylinski, R. Brylinski, V. Nistor, B. Tsygan and P. Xu), Progress in Math. Vol. 172 (Birkhäuser Boston, 1995), pp. 371-383 and A. N. Kirillov and T. Maenor, A Note on Quantum K-Theory of Flag Varieties, preprint]. As an application we describe explicitly the set of relations among the Gaudin elements in the group ring of the symmetric group, cf. [E. Mukhin, V. Tarasov and A. Varchenko, Bethe Subalgebras of the Group Algebra of the Symmetric Group, preprint arXiv:1004.4248]. Also we describe a few combinatorial properties of some special elements in the associative quasi-classical Yang-Baxter algebra in a connection with the values of the β-Grothendieck polynomials for some special permutations, and on the other hand, with the Ehrhart polynomial of the Chan-Robbins polytope.

A Hybrid Symbiotic Organisms Search Algorithm with Variable Neighbourhood Search for Solving Symmetric and Asymmetric Traveling Salesman Problem

NASA Astrophysics Data System (ADS)

Umam, M. I. H.; Santosa, B.

2018-04-01

Combinatorial optimization has been frequently used to solve both problems in science, engineering, and commercial applications. One combinatorial problems in the field of transportation is to find a shortest travel route that can be taken from the initial point of departure to point of destination, as well as minimizing travel costs and travel time. When the distance from one (initial) node to another (destination) node is the same with the distance to travel back from destination to initial, this problems known to the Traveling Salesman Problem (TSP), otherwise it call as an Asymmetric Traveling Salesman Problem (ATSP). The most recent optimization techniques is Symbiotic Organisms Search (SOS). This paper discuss how to hybrid the SOS algorithm with variable neighborhoods search (SOS-VNS) that can be applied to solve the ATSP problem. The proposed mechanism to add the variable neighborhoods search as a local search is to generate the better initial solution and then we modify the phase of parasites with adapting mechanism of mutation. After modification, the performance of the algorithm SOS-VNS is evaluated with several data sets and then the results is compared with the best known solution and some algorithm such PSO algorithm and SOS original algorithm. The SOS-VNS algorithm shows better results based on convergence, divergence and computing time.

On Some Algebraic and Combinatorial Properties of Dunkl Elements

NASA Astrophysics Data System (ADS)

Kirillov, Anatol N.

2012-11-01

We introduce and study a certain class of nonhomogeneous quadratic algebras together with the special set of mutually commuting elements inside of each, the so-called Dunkl elements. We describe relations among the Dunkl elements. This result is a further generalization of similar results obtained in [S. Fomin and A. N. Kirillov, Quadratic algebras, Dunkl elements and Schubert calculus, in Advances in Geometry (eds. J.-S. Brylinski, V. Nistor, B. Tsygan and P. Xu), Progress in Math. Vol. 172 (Birkhäuser Boston, Boston, 1995), pp. 147-182, A. Postnikov, On a quantum version of Pieri's formula, in Advances in Geometry (eds. J.-S. Brylinski, R. Brylinski, V. Nistor, B. Tsygan and P. Xu), Progress in Math. Vol. 172 (Birkhäuser Boston, 1995), pp. 371-383 and A. N. Kirillov and T. Maenor, A Note on Quantum K-Theory of Flag Varieties, preprint]. As an application we describe explicitly the set of relations among the Gaudin elements in the group ring of the symmetric group, cf. [E. Mukhin, V. Tarasov and A. Varchenko, Bethe Subalgebras of the Group Algebra of the Symmetric Group, preprint arXiv:1004.4248]. Also we describe a few combinatorial properties of some special elements in the associative quasi-classical Yang-Baxter algebra in a connection with the values of the β-Grothendieck polynomials for some special permutations, and on the other hand, with the Ehrhart polynomial of the Chan-Robbins polytope.

Scientific discovery as a combinatorial optimisation problem: How best to navigate the landscape of possible experiments?

PubMed Central

Kell, Douglas B

2012-01-01

A considerable number of areas of bioscience, including gene and drug discovery, metabolic engineering for the biotechnological improvement of organisms, and the processes of natural and directed evolution, are best viewed in terms of a ‘landscape’ representing a large search space of possible solutions or experiments populated by a considerably smaller number of actual solutions that then emerge. This is what makes these problems ‘hard’, but as such these are to be seen as combinatorial optimisation problems that are best attacked by heuristic methods known from that field. Such landscapes, which may also represent or include multiple objectives, are effectively modelled in silico, with modern active learning algorithms such as those based on Darwinian evolution providing guidance, using existing knowledge, as to what is the ‘best’ experiment to do next. An awareness, and the application, of these methods can thereby enhance the scientific discovery process considerably. This analysis fits comfortably with an emerging epistemology that sees scientific reasoning, the search for solutions, and scientific discovery as Bayesian processes. PMID:22252984

BDNF gene delivery within and beyond templated agarose multi-channel guidance scaffolds enhances peripheral nerve regeneration

NASA Astrophysics Data System (ADS)

Gao, Mingyong; Lu, Paul; Lynam, Dan; Bednark, Bridget; Campana, W. Marie; Sakamoto, Jeff; Tuszynski, Mark

2016-12-01

Objective. We combined implantation of multi-channel templated agarose scaffolds with growth factor gene delivery to examine whether this combinatorial treatment can enhance peripheral axonal regeneration through long sciatic nerve gaps. Approach. 15 mm long scaffolds were templated into highly organized, strictly linear channels, mimicking the linear organization of natural nerves into fascicles of related function. Scaffolds were filled with syngeneic bone marrow stromal cells (MSCs) secreting the growth factor brain derived neurotrophic factor (BDNF), and lentiviral vectors expressing BDNF were injected into the sciatic nerve segment distal to the scaffold implantation site. Main results. Twelve weeks after injury, scaffolds supported highly linear regeneration of host axons across the 15 mm lesion gap. The incorporation of BDNF-secreting cells into scaffolds significantly increased axonal regeneration, and additional injection of viral vectors expressing BDNF into the distal segment of the transected nerve significantly enhanced axonal regeneration beyond the lesion. Significance. Combinatorial treatment with multichannel bioengineered scaffolds and distal growth factor delivery significantly improves peripheral nerve repair, rivaling the gold standard of autografts.

Biogeography-based combinatorial strategy for efficient autonomous underwater vehicle motion planning and task-time management

NASA Astrophysics Data System (ADS)

Zadeh, S. M.; Powers, D. M. W.; Sammut, K.; Yazdani, A. M.

2016-12-01

Autonomous Underwater Vehicles (AUVs) are capable of spending long periods of time for carrying out various underwater missions and marine tasks. In this paper, a novel conflict-free motion planning framework is introduced to enhance underwater vehicle's mission performance by completing maximum number of highest priority tasks in a limited time through a large scale waypoint cluttered operating field, and ensuring safe deployment during the mission. The proposed combinatorial route-path planner model takes the advantages of the Biogeography-Based Optimization (BBO) algorithm toward satisfying objectives of both higher-lower level motion planners and guarantees maximization of the mission productivity for a single vehicle operation. The performance of the model is investigated under different scenarios including the particular cost constraints in time-varying operating fields. To show the reliability of the proposed model, performance of each motion planner assessed separately and then statistical analysis is undertaken to evaluate the total performance of the entire model. The simulation results indicate the stability of the contributed model and its feasible application for real experiments.

Scientific discovery as a combinatorial optimisation problem: how best to navigate the landscape of possible experiments?

PubMed

Kell, Douglas B

2012-03-01

A considerable number of areas of bioscience, including gene and drug discovery, metabolic engineering for the biotechnological improvement of organisms, and the processes of natural and directed evolution, are best viewed in terms of a 'landscape' representing a large search space of possible solutions or experiments populated by a considerably smaller number of actual solutions that then emerge. This is what makes these problems 'hard', but as such these are to be seen as combinatorial optimisation problems that are best attacked by heuristic methods known from that field. Such landscapes, which may also represent or include multiple objectives, are effectively modelled in silico, with modern active learning algorithms such as those based on Darwinian evolution providing guidance, using existing knowledge, as to what is the 'best' experiment to do next. An awareness, and the application, of these methods can thereby enhance the scientific discovery process considerably. This analysis fits comfortably with an emerging epistemology that sees scientific reasoning, the search for solutions, and scientific discovery as Bayesian processes. Copyright © 2012 WILEY Periodicals, Inc.

Final Report

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

Chidambaram, Dev; Misra, Mano; Heske, Clemens

2014-12-21

The objectives included: Develop high efficiency metal oxide nanotubular array photo-anodes for generating hydrogen by water splitting; Develop density functional theory to understand the effect of the morphology of the nanotubes on the photo-electrochemical (PEC) properties of the photo-anodes; Develop kinetics and formation mechanism of the metal oxide nanotubes under different synthesis conditions; Develop combinatorial approach to prepare hybrid photo-anodes having multiple hetero-atoms incorporation in a single photo anode; Improve the durability of the material; and Scale up the laboratory demonstration to production unit.

Combinatorial fabrication and screening of organic light-emitting device arrays

NASA Astrophysics Data System (ADS)

Shinar, Joseph; Shinar, Ruth; Zhou, Zhaoqun

2007-11-01

The combinatorial fabrication and screening of 2-dimensional (2-d) small molecular UV-violet organic light-emitting device (OLED) arrays, 1-d blue-to-red arrays, 1-d intense white OLED libraries, 1-d arrays to study Förster energy transfer in guest-host OLEDs, and 2-d arrays to study exciplex emission from OLEDs is described. The results demonstrate the power of combinatorial approaches for screening OLED materials and configurations, and for studying their basic properties.

Combinatorial Dyson-Schwinger equations and inductive data types

NASA Astrophysics Data System (ADS)

Kock, Joachim

2016-06-01

The goal of this contribution is to explain the analogy between combinatorial Dyson-Schwinger equations and inductive data types to a readership of mathematical physicists. The connection relies on an interpretation of combinatorial Dyson-Schwinger equations as fixpoint equations for polynomial functors (established elsewhere by the author, and summarised here), combined with the now-classical fact that polynomial functors provide semantics for inductive types. The paper is expository, and comprises also a brief introduction to type theory.

Combinatorial stresses kill pathogenic Candida species

PubMed Central

Kaloriti, Despoina; Tillmann, Anna; Cook, Emily; Jacobsen, Mette; You, Tao; Lenardon, Megan; Ames, Lauren; Barahona, Mauricio; Chandrasekaran, Komelapriya; Coghill, George; Goodman, Daniel; Gow, Neil A. R.; Grebogi, Celso; Ho, Hsueh-Lui; Ingram, Piers; McDonagh, Andrew; De Moura, Alessandro P. S.; Pang, Wei; Puttnam, Melanie; Radmaneshfar, Elahe; Romano, Maria Carmen; Silk, Daniel; Stark, Jaroslav; Stumpf, Michael; Thiel, Marco; Thorne, Thomas; Usher, Jane; Yin, Zhikang; Haynes, Ken; Brown, Alistair J. P.

2012-01-01

Pathogenic microbes exist in dynamic niches and have evolved robust adaptive responses to promote survival in their hosts. The major fungal pathogens of humans, Candida albicans and Candida glabrata, are exposed to a range of environmental stresses in their hosts including osmotic, oxidative and nitrosative stresses. Significant efforts have been devoted to the characterization of the adaptive responses to each of these stresses. In the wild, cells are frequently exposed simultaneously to combinations of these stresses and yet the effects of such combinatorial stresses have not been explored. We have developed a common experimental platform to facilitate the comparison of combinatorial stress responses in C. glabrata and C. albicans. This platform is based on the growth of cells in buffered rich medium at 30°C, and was used to define relatively low, medium and high doses of osmotic (NaCl), oxidative (H 2O2) and nitrosative stresses (e.g., dipropylenetriamine (DPTA)-NONOate). The effects of combinatorial stresses were compared with the corresponding individual stresses under these growth conditions. We show for the first time that certain combinations of combinatorial stress are especially potent in terms of their ability to kill C. albicans and C. glabrata and/or inhibit their growth. This was the case for combinations of osmotic plus oxidative stress and for oxidative plus nitrosative stress. We predict that combinatorial stresses may be highly signif cant in host defences against these pathogenic yeasts. PMID:22463109

Steam explosion and its combinatorial pretreatment refining technology of plant biomass to bio-based products.

PubMed

Chen, Hong-Zhang; Liu, Zhi-Hua

2015-06-01

Pretreatment is a key unit operation affecting the refinery efficiency of plant biomass. However, the poor efficiency of pretreatment and the lack of basic theory are the main challenges to the industrial implementation of the plant biomass refinery. The purpose of this work is to review steam explosion and its combinatorial pretreatment as a means of overcoming the intrinsic characteristics of plant biomass, including recalcitrance, heterogeneity, multi-composition, and diversity. The main advantages of the selective use of steam explosion and other combinatorial pretreatments across the diversity of raw materials are introduced. Combinatorial pretreatment integrated with other unit operations is proposed as a means to exploit the high-efficiency production of bio-based products from plant biomass. Finally, several pilot- and demonstration-scale operations of the plant biomass refinery are described. Based on the principle of selective function and structure fractionation, and multi-level and directional composition conversion, an integrated process with the combinatorial pretreatments of steam explosion and other pretreatments as the core should be feasible and conform to the plant biomass refinery concept. Combinatorial pretreatments of steam explosion and other pretreatments should be further exploited based on the type and intrinsic characteristics of the plant biomass used, the bio-based products to be made, and the complementarity of the processes. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Clinical and pharmacogenomic data mining: 1. Generalized theory of expected information and application to the development of tools.

PubMed

Robson, Barry

2003-01-01

New scientific problems, arising from the human genome project, are challenging the classical means of using statistics. Yet quantified knowledge in the form of rules and rule strengths based on real relationships in data, as opposed to expert opinion, is urgently required for researcher and physician decision support. The problem is that with many parameters, the space to be analyzed is highly dimensional. That is, the combinations of data to examine are subject to a combinatorial explosion as the number of possible events (entries, items, sub-records) (a),(b),(c),... per record (a,b,c,..) increases, and hence much of the space is sparsely populated. These combinatorial considerations are particularly problematic for identifying those associations called "Unicorn Events" which occur significantly less than expected to the extent that they are never seen to be counted. To cope with the combinatorial explosion, a novel numerical "book keeping" approach is taken to generate information terms relating to the combinatorial subsets of events (a,b,c,..), and, most importantly, the zeta (Zeta) function is employed. The incomplete Zeta function zeta(s,n) with s = 1, in which frequencies of occurrence such as n = n(a,b,c,...) determine the range of summation n, is argued to be the natural choice of information function. It emerges from Bayesian integration, taken over the distribution of possible values of information measures for sparse and ample data alike. Expected mutual information l(a;b;c) in nats (i.e., natural units analogous to bits but based on the natural logarithm), such as is available to the observer, is measured as e.g., the difference zeta(s,o(a,b,c..)) - zeta(s,e(a,b,c..)) where o(a,b,c,..) and e(a,b,c,..) are, or relate to, the observed and expected frequencies of occurrence, respectively. For real values of s > 1 the qualitative impact of strongly (positively or negatively) ranked data is preserved despite several numerical approximations. As real s increases, and the output of the information functions converge into three values +1, 0, and -1 nats representing a trinary logic system. For quantitative data, a useful ad hoc method, to report sigma-normalized covariations in an analogous manner to mutual information for significance comparison purposes, is demonstrated. Finally, the potential ability to make use of mutual information in a complex biomedical study, and to include Bayesian prior information derived from statistical, tabular, anecdotal, and expert opinion is briefly illustrated.

Detecting independent and recurrent copy number aberrations using interval graphs.

PubMed

Wu, Hsin-Ta; Hajirasouliha, Iman; Raphael, Benjamin J

2014-06-15

Somatic copy number aberrations SCNAS: are frequent in cancer genomes, but many of these are random, passenger events. A common strategy to distinguish functional aberrations from passengers is to identify those aberrations that are recurrent across multiple samples. However, the extensive variability in the length and position of SCNA: s makes the problem of identifying recurrent aberrations notoriously difficult. We introduce a combinatorial approach to the problem of identifying independent and recurrent SCNA: s, focusing on the key challenging of separating the overlaps in aberrations across individuals into independent events. We derive independent and recurrent SCNA: s as maximal cliques in an interval graph constructed from overlaps between aberrations. We efficiently enumerate all such cliques, and derive a dynamic programming algorithm to find an optimal selection of non-overlapping cliques, resulting in a very fast algorithm, which we call RAIG (Recurrent Aberrations from Interval Graphs). We show that RAIG outperforms other methods on simulated data and also performs well on data from three cancer types from The Cancer Genome Atlas (TCGA). In contrast to existing approaches that employ various heuristics to select independent aberrations, RAIG optimizes a well-defined objective function. We show that this allows RAIG to identify rare aberrations that are likely functional, but are obscured by overlaps with larger passenger aberrations. http://compbio.cs.brown.edu/software. © The Author 2014. Published by Oxford University Press.

Evaluation of Recoverable-Robust Timetables on Tree Networks

NASA Astrophysics Data System (ADS)

D'Angelo, Gianlorenzo; di Stefano, Gabriele; Navarra, Alfredo

In the context of scheduling and timetabling, we study a challenging combinatorial problem which is interesting from both a practical and a theoretical point of view. The motivation behind it is to cope with scheduled activities which might be subject to unavoidable disturbances, such as delays, occurring during the operational phase. The idea is to preventively plan some extra time for the scheduled activities in order to be "prepared" if a delay occurs, and to absorb it without the necessity of re-scheduling the activities from scratch. This realizes the concept of designing so called robust timetables. During the planning phase, one has to consider recovery features that might be applied at runtime if delays occur. Such recovery capabilities are given as input along with the possible delays that must be considered. The objective is the minimization of the overall needed time. The quality of a robust timetable is measured by the price of robustness, i.e. the ratio between the cost of the robust timetable and that of a non-robust optimal timetable. The considered problem is known to be NP-hard. We propose a pseudo-polynomial time algorithm and apply it on random networks and real case scenarios provided by Italian railways. We evaluate the effect of robustness on the scheduling of the activities and provide the price of robustness with respect to different scenarios. We experimentally show the practical effectiveness and efficiency of the proposed algorithm.

Measurement problem in Program Universe. Revision

NASA Astrophysics Data System (ADS)

Noyes, H. P.; Gefwert, C.; Manthey, M. J.

1985-07-01

The measurement problem of contemporary physics is in our view an artifact of its philosophical and mathematical underpinnings. We describe a new philosophical view of theory formation, rooted in Wittgenstein, and Bishop's and Martin-Loef's constructivity, which obviates such discussions. We present an unfinished, but very encouraging, theory which is compatible with this philosophical framework. The theory is based on the concepts of counting and combinatorics in the framework provided by the combinatorial hierarchy, a unique hierarchy of bit strings which interact by an operation called discrimination. Measurement criteria incorporate c, h-bar and m/sub p/ or (not and) G. The resulting theory is discrete throughout, contains no infinities, and, as far as we have developed it, is in agreement with quantum mechanical and cosmological fact.

Cohomology of line bundles: Applications

NASA Astrophysics Data System (ADS)

Blumenhagen, Ralph; Jurke, Benjamin; Rahn, Thorsten; Roschy, Helmut

2012-01-01

Massless modes of both heterotic and Type II string compactifications on compact manifolds are determined by vector bundle valued cohomology classes. Various applications of our recent algorithm for the computation of line bundle valued cohomology classes over toric varieties are presented. For the heterotic string, the prime examples are so-called monad constructions on Calabi-Yau manifolds. In the context of Type II orientifolds, one often needs to compute cohomology for line bundles on finite group action coset spaces, necessitating us to generalize our algorithm to this case. Moreover, we exemplify that the different terms in Batyrev's formula and its generalizations can be given a one-to-one cohomological interpretation. Furthermore, we derive a combinatorial closed form expression for two Hodge numbers of a codimension two Calabi-Yau fourfold.

Evaluation of the Current Status of the Combinatorial Approach for the Study of Phase Diagrams

PubMed Central

Wong-Ng, W.

2012-01-01

This paper provides an evaluation of the effectiveness of using the high throughput combinatorial approach for preparing phase diagrams of thin film and bulk materials. Our evaluation is based primarily on examples of combinatorial phase diagrams that have been reported in the literature as well as based on our own laboratory experiments. Various factors that affect the construction of these phase diagrams are examined. Instrumentation and analytical approaches needed to improve data acquisition and data analysis are summarized. PMID:26900530

Research on thermal protection mechanism of forward-facing cavity and opposing jet combinatorial thermal protection system

NASA Astrophysics Data System (ADS)

Lu, Hai-Bo; Liu, Wei-Qiang

2014-04-01

Validated by the correlated experiments, a nose-tip with forward-facing cavity/opposing jet/the combinatorial configuration of forward-facing cavity and opposing jet thermal protection system (TPS) are investigated numerically. The physical mechanism of these TPS is discussed, and the cooling efficiency of them is compared. The combinatorial system is more suitable to be the TPS for the high speed vehicles which need fly under various flow conditions with long-range and long time.

Combinatorial approach to the representation of the Schur-Weyl duality in one-dimensional spin systems

NASA Astrophysics Data System (ADS)

Jakubczyk, Dorota; Jakubczyk, Paweł

2018-02-01

We propose combinatorial approach to the representation of Schur-Weyl duality in physical systems on the example of one-dimensional spin chains. Exploiting the Robinson-Schensted-Knuth algorithm, we perform decomposition of the dual group representations into irreducible representations in a fully combinatorial way. As representation space, we choose the Hilbert space of the spin chains, but this approach can be easily generalized to an arbitrary physical system where the Schur-Weyl duality works.

Massively multiplex single-cell Hi-C

PubMed Central

Ramani, Vijay; Deng, Xinxian; Qiu, Ruolan; Gunderson, Kevin L; Steemers, Frank J; Disteche, Christine M; Noble, William S; Duan, Zhijun; Shendure, Jay

2016-01-01

We present single-cell combinatorial indexed Hi-C (sciHi-C), which applies the concept of combinatorial cellular indexing to chromosome conformation capture. In this proof-of-concept, we generate and sequence six sciHi-C libraries comprising a total of 10,696 single cells. We use sciHi-C data to separate cells by karytoypic and cell-cycle state differences and identify cell-to-cell heterogeneity in mammalian chromosomal conformation. Our results demonstrate that combinatorial indexing is a generalizable strategy for single-cell genomics. PMID:28135255

Combinatorial Interdependence in Lottery

ERIC Educational Resources Information Center

Helman, Danny

2005-01-01

This paper examines a real life question of gamble facing lottery players. Combinatorial dependence plays a central role in shaping the game probabilistic structure, but might not carry the merited weight in punters' considerations.

Combinatorial Mathematics: Research into Practice

ERIC Educational Resources Information Center

Sriraman, Bharath; English, Lyn D.

2004-01-01

Implications and suggestions for using combinatorial mathematics in the classroom through a survey and synthesis of numerous research studies are presented. The implications revolve around five major themes that emerge from analysis of these studies.

Enabling techniques in the search for new antibiotics: Combinatorial biosynthesis of sugar-containing antibiotics.

PubMed

Park, Je Won; Nam, Sang-Jip; Yoon, Yeo Joon

2017-06-15

Nature has a talent for inventing a vast number of natural products, including hybrids generated by blending different scaffolds, resulting in a myriad of bioactive chemical entities. Herein, we review the highlights and recent trends (2010-2016) in the combinatorial biosynthesis of sugar-containing antibiotics where nature's structural diversification capabilities are exploited to enable the creation of new anti-infective and anti-proliferative drugs. In this review, we describe the modern combinatorial biosynthetic approaches for polyketide synthase-derived complex and aromatic polyketides, non-ribosomal peptide synthetase-directed lipo-/glycopeptides, aminoglycosides, nucleoside antibiotics, and alkaloids, along with their therapeutic potential. Finally, we present the feasible nexus between combinatorial biosynthesis, systems biology, and synthetic biology as a toolbox to provide new antibiotics that will be indispensable in the post-antibiotic era. Copyright © 2016 Elsevier Inc. All rights reserved.

Combinatorial vector fields and the valley structure of fitness landscapes.

PubMed

Stadler, Bärbel M R; Stadler, Peter F

2010-12-01

Adaptive (downhill) walks are a computationally convenient way of analyzing the geometric structure of fitness landscapes. Their inherently stochastic nature has limited their mathematical analysis, however. Here we develop a framework that interprets adaptive walks as deterministic trajectories in combinatorial vector fields and in return associate these combinatorial vector fields with weights that measure their steepness across the landscape. We show that the combinatorial vector fields and their weights have a product structure that is governed by the neutrality of the landscape. This product structure makes practical computations feasible. The framework presented here also provides an alternative, and mathematically more convenient, way of defining notions of valleys, saddle points, and barriers in landscape. As an application, we propose a refined approximation for transition rates between macrostates that are associated with the valleys of the landscape.

Measuring and Specifying Combinatorial Coverage of Test Input Configurations

PubMed Central

Kuhn, D. Richard; Kacker, Raghu N.; Lei, Yu

2015-01-01

A key issue in testing is how many tests are needed for a required level of coverage or fault detection. Estimates are often based on error rates in initial testing, or on code coverage. For example, tests may be run until a desired level of statement or branch coverage is achieved. Combinatorial methods present an opportunity for a different approach to estimating required test set size, using characteristics of the test set. This paper describes methods for estimating the coverage of, and ability to detect, t-way interaction faults of a test set based on a covering array. We also develop a connection between (static) combinatorial coverage and (dynamic) code coverage, such that if a specific condition is satisfied, 100% branch coverage is assured. Using these results, we propose practical recommendations for using combinatorial coverage in specifying test requirements. PMID:28133442

Combinatorial chemical bath deposition of CdS contacts for chalcogenide photovoltaics

DOE PAGES

Mokurala, Krishnaiah; Baranowski, Lauryn L.; de Souza Lucas, Francisco W.; ...

2016-08-01

Contact layers play an important role in thin film solar cells, but new material development and optimization of its thickness is usually a long and tedious process. A high-throughput experimental approach has been used to accelerate the rate of research in photovoltaic (PV) light absorbers and transparent conductive electrodes, however the combinatorial research on contact layers is less common. Here, we report on the chemical bath deposition (CBD) of CdS thin films by combinatorial dip coating technique and apply these contact layers to Cu(In,Ga)Se 2 (CIGSe) and Cu 2ZnSnSe 4 (CZTSe) light absorbers in PV devices. Combinatorial thickness steps ofmore » CdS thin films were achieved by removal of the substrate from the chemical bath, at regular intervals of time, and in equal distance increments. The trends in the photoconversion efficiency and in the spectral response of the PV devices as a function of thickness of CdS contacts were explained with the help of optical and morphological characterization of the CdS thin films. The maximum PV efficiency achieved for the combinatorial dip-coating CBD was similar to that for the PV devices processed using conventional CBD. Finally, the results of this study lead to the conclusion that combinatorial dip-coating can be used to accelerate the optimization of PV device performance of CdS and other candidate contact layers for a wide range of emerging absorbers.« less

Polynomial functors and combinatorial Dyson-Schwinger equations

NASA Astrophysics Data System (ADS)

Kock, Joachim

2017-04-01

We present a general abstract framework for combinatorial Dyson-Schwinger equations, in which combinatorial identities are lifted to explicit bijections of sets, and more generally equivalences of groupoids. Key features of combinatorial Dyson-Schwinger equations are revealed to follow from general categorical constructions and universal properties. Rather than beginning with an equation inside a given Hopf algebra and referring to given Hochschild 1-cocycles, our starting point is an abstract fixpoint equation in groupoids, shown canonically to generate all the algebraic structures. Precisely, for any finitary polynomial endofunctor P defined over groupoids, the system of combinatorial Dyson-Schwinger equations X = 1 + P(X) has a universal solution, namely the groupoid of P-trees. The isoclasses of P-trees generate naturally a Connes-Kreimer-like bialgebra, in which the abstract Dyson-Schwinger equation can be internalised in terms of canonical B+-operators. The solution to this equation is a series (the Green function), which always enjoys a Faà di Bruno formula, and hence generates a sub-bialgebra isomorphic to the Faà di Bruno bialgebra. Varying P yields different bialgebras, and cartesian natural transformations between various P yield bialgebra homomorphisms and sub-bialgebras, corresponding for example to truncation of Dyson-Schwinger equations. Finally, all constructions can be pushed inside the classical Connes-Kreimer Hopf algebra of trees by the operation of taking core of P-trees. A byproduct of the theory is an interpretation of combinatorial Green functions as inductive data types in the sense of Martin-Löf type theory (expounded elsewhere).

Operator Approach to the Master Equation for the One-Step Process

NASA Astrophysics Data System (ADS)

Hnatič, M.; Eferina, E. G.; Korolkova, A. V.; Kulyabov, D. S.; Sevastyanov, L. A.

2016-02-01

Background. Presentation of the probability as an intrinsic property of the nature leads researchers to switch from deterministic to stochastic description of the phenomena. The kinetics of the interaction has recently attracted attention because it often occurs in the physical, chemical, technical, biological, environmental, economic, and sociological systems. However, there are no general methods for the direct study of this equation. The expansion of the equation in a formal Taylor series (the so called Kramers-Moyal's expansion) is used in the procedure of stochastization of one-step processes. Purpose. However, this does not eliminate the need for the study of the master equation. Method. It is proposed to use quantum field perturbation theory for the statistical systems (the so-called Doi method). Results: This work is a methodological material that describes the principles of master equation solution based on quantum field perturbation theory methods. The characteristic property of the work is that it is intelligible for non-specialists in quantum field theory. Conclusions: We show the full equivalence of the operator and combinatorial methods of obtaining and study of the one-step process master equation.

Combinatorial invariants and covariants as tools for conical intersections.

PubMed

Ryb, Itai; Baer, Roi

2004-12-01

The combinatorial invariant and covariant are introduced as practical tools for analysis of conical intersections in molecules. The combinatorial invariant is a quantity depending on adiabatic electronic states taken at discrete nuclear configuration points. It is invariant to the phase choice (gauge) of these states. In the limit that the points trace a loop in nuclear configuration space, the value of the invariant approaches the corresponding Berry phase factor. The Berry phase indicates the presence of an odd or even number of conical intersections on surfaces bounded by these loops. Based on the combinatorial invariant, we develop a computationally simple and efficient method for locating conical intersections. The method is robust due to its use of gauge invariant nature. It does not rely on the landscape of intersecting potential energy surfaces nor does it require the computation of nonadiabatic couplings. We generalize the concept to open paths and combinatorial covariants for higher dimensions obtaining a technique for the construction of the gauge-covariant adiabatic-diabatic transformation matrix. This too does not make use of nonadiabatic couplings. The importance of using gauge-covariant expressions is underlined throughout. These techniques can be readily implemented by standard quantum chemistry codes. (c) 2004 American Institute of Physics.

On the suitability of different representations of solid catalysts for combinatorial library design by genetic algorithms.

PubMed

Gobin, Oliver C; Schüth, Ferdi

2008-01-01

Genetic algorithms are widely used to solve and optimize combinatorial problems and are more often applied for library design in combinatorial chemistry. Because of their flexibility, however, their implementation can be challenging. In this study, the influence of the representation of solid catalysts on the performance of genetic algorithms was systematically investigated on the basis of a new, constrained, multiobjective, combinatorial test problem with properties common to problems in combinatorial materials science. Constraints were satisfied by penalty functions, repair algorithms, or special representations. The tests were performed using three state-of-the-art evolutionary multiobjective algorithms by performing 100 optimization runs for each algorithm and test case. Experimental data obtained during the optimization of a noble metal-free solid catalyst system active in the selective catalytic reduction of nitric oxide with propene was used to build up a predictive model to validate the results of the theoretical test problem. A significant influence of the representation on the optimization performance was observed. Binary encodings were found to be the preferred encoding in most of the cases, and depending on the experimental test unit, repair algorithms or penalty functions performed best.

Direct Profiling the Post-Translational Modification Codes of a Single Protein Immobilized on a Surface Using Cu-free Click Chemistry.

PubMed

Kim, Kyung Lock; Park, Kyeng Min; Murray, James; Kim, Kimoon; Ryu, Sung Ho

2018-05-23

Combinatorial post-translational modifications (PTMs), which can serve as dynamic "molecular barcodes", have been proposed to regulate distinct protein functions. However, studies of combinatorial PTMs on single protein molecules have been hindered by a lack of suitable analytical methods. Here, we describe erasable single-molecule blotting (eSiMBlot) for combinatorial PTM profiling. This assay is performed in a highly multiplexed manner and leverages the benefits of covalent protein immobilization, cyclic probing with different antibodies, and single molecule fluorescence imaging. Especially, facile and efficient covalent immobilization on a surface using Cu-free click chemistry permits multiple rounds (>10) of antibody erasing/reprobing without loss of antigenicity. Moreover, cumulative detection of coregistered multiple data sets for immobilized single-epitope molecules, such as HA peptide, can be used to increase the antibody detection rate. Finally, eSiMBlot enables direct visualization and quantitative profiling of combinatorial PTM codes at the single-molecule level, as we demonstrate by revealing the novel phospho-codes of ligand-induced epidermal growth factor receptor. Thus, eSiMBlot provides an unprecedentedly simple, rapid, and versatile platform for analyzing the vast number of combinatorial PTMs in biological pathways.

Direct Profiling the Post-Translational Modification Codes of a Single Protein Immobilized on a Surface Using Cu-free Click Chemistry

PubMed Central

2018-01-01

Combinatorial post-translational modifications (PTMs), which can serve as dynamic “molecular barcodes”, have been proposed to regulate distinct protein functions. However, studies of combinatorial PTMs on single protein molecules have been hindered by a lack of suitable analytical methods. Here, we describe erasable single-molecule blotting (eSiMBlot) for combinatorial PTM profiling. This assay is performed in a highly multiplexed manner and leverages the benefits of covalent protein immobilization, cyclic probing with different antibodies, and single molecule fluorescence imaging. Especially, facile and efficient covalent immobilization on a surface using Cu-free click chemistry permits multiple rounds (>10) of antibody erasing/reprobing without loss of antigenicity. Moreover, cumulative detection of coregistered multiple data sets for immobilized single-epitope molecules, such as HA peptide, can be used to increase the antibody detection rate. Finally, eSiMBlot enables direct visualization and quantitative profiling of combinatorial PTM codes at the single-molecule level, as we demonstrate by revealing the novel phospho-codes of ligand-induced epidermal growth factor receptor. Thus, eSiMBlot provides an unprecedentedly simple, rapid, and versatile platform for analyzing the vast number of combinatorial PTMs in biological pathways.

Lexicographic goal programming and assessment tools for a combinatorial production problem.

DOT National Transportation Integrated Search

2008-01-01

NP-complete combinatorial problems often necessitate the use of near-optimal solution techniques including : heuristics and metaheuristics. The addition of multiple optimization criteria can further complicate : comparison of these solution technique...

"Anticlumping" and Other Combinatorial Effects on Clumped Isotopes: Implications for Tracing Biogeochemical Cycling

NASA Astrophysics Data System (ADS)

Yeung, L.

2015-12-01

I present a mode of isotopic ordering that has purely combinatorial origins. It can be important when identical rare isotopes are paired by coincidence (e.g., they are neighbors on the same molecule), or when extrinsic factors govern the isotopic composition of the two atoms that share a chemical bond. By itself, combinatorial isotope pairing yields products with isotopes either randomly distributed or with a deficit relative to a random distribution of isotopes. These systematics arise because of an unconventional coupling between the formation of singly- and multiply-substituted isotopic moieties. In a random distribution, rare isotopes are symmetrically distributed: Single isotopic substitutions (e.g., H‒D and D‒H in H2) occur with equal probability, and double isotopic substitutions (e.g., D2) occur according to random chance. The absence of symmetry in a bond-making complex can yield unequal numbers of singly-substituted molecules (e.g., more H‒D than D‒H in H2), which is recorded in the product molecule as a deficit in doubly-substituted moieties and an "anticlumped" isotope distribution (i.e., Δn < 0). Enzymatic isotope pairing reactions, which can have site-specific isotopic fractionation factors and atom reservoirs, should express this class of combinatorial isotope effect. Chemical-kinetic isotope effects, which are related to the bond-forming transition state, arise independently and express second-order combinatorial effects. In general, both combinatorial and chemical factors are important for calculating and interpreting clumped-isotope signatures of individual reactions. In many reactions relevant to geochemical oxygen, carbon, and nitrogen cycling, combinatorial isotope pairing likely plays a strong role in the clumped isotope distribution of the products. These isotopic signatures, manifest as either directly bound isotope clumps or as features of a molecule's isotopic anatomy, could be exploited as tracers of biogeochemistry that can relate molecular mechanisms to signals observable at environmentally relevant spatial scales.

Creative thought as blind-variation and selective-retention: Combinatorial models of exceptional creativity

NASA Astrophysics Data System (ADS)

Simonton, Dean Keith

2010-06-01

Campbell (1960) proposed that creative thought should be conceived as a blind-variation and selective-retention process (BVSR). This article reviews the developments that have taken place in the half century that has elapsed since his proposal, with special focus on the use of combinatorial models as formal representations of the general theory. After defining the key concepts of blind variants, creative thought, and disciplinary context, the combinatorial models are specified in terms of individual domain samples, variable field size, ideational combination, and disciplinary communication. Empirical implications are then derived with respect to individual, domain, and field systems. These abstract combinatorial models are next provided substantive reinforcement with respect to findings concerning the cognitive processes, personality traits, developmental factors, and social contexts that contribute to creativity. The review concludes with some suggestions regarding future efforts to explicate creativity according to BVSR theory.

Combinatorial Color Space Models for Skin Detection in Sub-continental Human Images

NASA Astrophysics Data System (ADS)

Khaled, Shah Mostafa; Saiful Islam, Md.; Rabbani, Md. Golam; Tabassum, Mirza Rehenuma; Gias, Alim Ul; Kamal, Md. Mostafa; Muctadir, Hossain Muhammad; Shakir, Asif Khan; Imran, Asif; Islam, Saiful

Among different color models HSV, HLS, YIQ, YCbCr, YUV, etc. have been most popular for skin detection. Most of the research done in the field of skin detection has been trained and tested on human images of African, Mongolian and Anglo-Saxon ethnic origins, skin colors of Indian sub-continentals have not been focused separately. Combinatorial algorithms, without affecting asymptotic complexity can be developed using the skin detection concepts of these color models for boosting detection performance. In this paper a comparative study of different combinatorial skin detection algorithms have been made. For training and testing 200 images (skin and non skin) containing pictures of sub-continental male and females have been used to measure the performance of the combinatorial approaches, and considerable development in success rate with True Positive of 99.5% and True Negative of 93.3% have been observed.

Optimized Reaction Conditions for Amide Bond Formation in DNA-Encoded Combinatorial Libraries.

PubMed

Li, Yizhou; Gabriele, Elena; Samain, Florent; Favalli, Nicholas; Sladojevich, Filippo; Scheuermann, Jörg; Neri, Dario

2016-08-08

DNA-encoded combinatorial libraries are increasingly being used as tools for the discovery of small organic binding molecules to proteins of biological or pharmaceutical interest. In the majority of cases, synthetic procedures for the formation of DNA-encoded combinatorial libraries incorporate at least one step of amide bond formation between amino-modified DNA and a carboxylic acid. We investigated reaction conditions and established a methodology by using 1-ethyl-3-(3-(dimethylamino)propyl)carbodiimide, 1-hydroxy-7-azabenzotriazole and N,N'-diisopropylethylamine (EDC/HOAt/DIPEA) in combination, which provided conversions greater than 75% for 423/543 (78%) of the carboxylic acids tested. These reaction conditions were efficient with a variety of primary and secondary amines, as well as with various types of amino-modified oligonucleotides. The reaction conditions, which also worked efficiently over a broad range of DNA concentrations and reaction scales, should facilitate the synthesis of novel DNA-encoded combinatorial libraries.

Combinatorial games with a pass: a dynamical systems approach.

PubMed

Morrison, Rebecca E; Friedman, Eric J; Landsberg, Adam S

2011-12-01

By treating combinatorial games as dynamical systems, we are able to address a longstanding open question in combinatorial game theory, namely, how the introduction of a "pass" move into a game affects its behavior. We consider two well known combinatorial games, 3-pile Nim and 3-row Chomp. In the case of Nim, we observe that the introduction of the pass dramatically alters the game's underlying structure, rendering it considerably more complex, while for Chomp, the pass move is found to have relatively minimal impact. We show how these results can be understood by recasting these games as dynamical systems describable by dynamical recursion relations. From these recursion relations, we are able to identify underlying structural connections between these "games with passes" and a recently introduced class of "generic (perturbed) games." This connection, together with a (non-rigorous) numerical stability analysis, allows one to understand and predict the effect of a pass on a game.

Mixture-based combinatorial libraries from small individual peptide libraries: a case study on α1-antitrypsin deficiency.

PubMed

Chang, Yi-Pin; Chu, Yen-Ho

2014-05-16

The design, synthesis and screening of diversity-oriented peptide libraries using a "libraries from libraries" strategy for the development of inhibitors of α1-antitrypsin deficiency are described. The major buttress of the biochemical approach presented here is the use of well-established solid-phase split-and-mix method for the generation of mixture-based libraries. The combinatorial technique iterative deconvolution was employed for library screening. While molecular diversity is the general consideration of combinatorial libraries, exquisite design through systematic screening of small individual libraries is a prerequisite for effective library screening and can avoid potential problems in some cases. This review will also illustrate how large peptide libraries were designed, as well as how a conformation-sensitive assay was developed based on the mechanism of the conformational disease. Finally, the combinatorially selected peptide inhibitor capable of blocking abnormal protein aggregation will be characterized by biophysical, cellular and computational methods.

A compositional approach to building applications in a computational environment

NASA Astrophysics Data System (ADS)

Roslovtsev, V. V.; Shumsky, L. D.; Wolfengagen, V. E.

2014-04-01

The paper presents an approach to creating an applicative computational environment to feature computational processes and data decomposition, and a compositional approach to application building. The approach in question is based on the notion of combinator - both in systems with variable binding (such as λ-calculi) and those allowing programming without variables (combinatory logic style). We present a computation decomposition technique based on objects' structural decomposition, with the focus on computation decomposition. The computational environment's architecture is based on a network with nodes playing several roles simultaneously.

Combinatorial Strategies and High Throughput Screening in Drug Discovery Targeted to the Channel of Botulinum Neurotoxin

DTIC Science & Technology

2006-09-01

block the HC channel. memantine NH2 amantadine H2N quinacrine NH O N lidocaine NH O N QX-222 S N Cl chlorpromazine N NCl O HN N Our objective was to...M2 protein2 and its derivative, memantine , which blocks the NMDA receptor channel3, and is approved by the FDA for the treatment of dementia...intracellular processing of BoNTs by collapsing the pH gradient across endosomes6,7. Chlorpromazine, quinacrine and memantine , in addition, cross the blood

How the brain assigns a neural tag to arbitrary points in a high-dimensional space

NASA Astrophysics Data System (ADS)

Stevens, Charles

Brains in almost all organisms need to deal with very complex stimuli. For example, most mammals are very good at face recognition, and faces are very complex objects indeed. For example, modern face recognition software represents a face as a point in a 10,000 dimensional space. Every human must be able to learn to recognize any of the 7 billion faces in the world, and can recognize familiar faces after a display of the face is viewed for only a few hundred milliseconds. Because we do not understand how faces are assigned locations in a high-dimensional space by the brain, attacking the problem of how face recognition is accomplished is very difficult. But a much easier problem of the same sort can be studied for odor recognition. For the mouse, each odor is assigned a point in a 1000 dimensional space, and the fruit fly assigns any odor a location in only a 50 dimensional space. A fly has about 50 distinct types of odorant receptor neurons (ORNs), each of which produce nerve impulses at a specific rate for each different odor. This pattern of firing produced across 50 ORNs is called `a combinatorial odor code', and this code assigns every odor a point in a 50 dimensional space that is used to identify the odor. In order to learn the odor, the brain must alter the strength of synapses. The combinatorial code cannot itself by used to change synaptic strength because all odors use same neurons to form the code, and so all synapses would be changed for any odor and the odors could not be distinguished. In order to learn an odor, the brain must assign a set of neurons - the odor tag - that have the property that these neurons (1) should make use of all of the information available about the odor, and (2) insure that any two tags overlap as little as possible (so one odor does not modify synapses used by other odors). In the talk, I will explain how the olfactory system of both the fruit fly and the mouse produce a tag for each odor that has these two properties. Supported by NSF.

Finite Geometries in Quantum Theory:. from Galois (fields) to Hjelmslev (rings)

NASA Astrophysics Data System (ADS)

Saniga, Metod; Planat, Michel

Geometries over Galois fields (and related finite combinatorial structures/algebras) have recently been recognized to play an ever-increasing role in quantum theory, especially when addressing properties of mutually unbiased bases (MUBs). The purpose of this contribution is to show that completely new vistas open up if we consider a generalized class of finite (projective) geometries, viz. those defined over Galois rings and/or other finite Hjelmslev rings. The case is illustrated by demonstrating that the basic combinatorial properties of a complete set of MUBs of a q-dimensional Hilbert space { H}q, q = pr with p being a prime and r a positive integer, are qualitatively mimicked by the configuration of points lying on a proper conic in a projective Hjelmslev plane defined over a Galois ring of characteristic p2 and rank r. The q vectors of a basis of { H}q correspond to the q points of a (so-called) neighbour class and the q + 1 MUBs answer to the total number of (pairwise disjoint) neighbour classes on the conic. Although this remarkable analogy is still established at the level of cardinalities only, we currently work on constructing an explicit mapping by associating a MUB to each neighbour class of the points of the conic and a state vector of this MUB to a particular point of the class. Further research in this direction may prove to be of great relevance for many areas of quantum information theory, in particular for quantum information processing.

Transport of calcium ions through a bulk membrane by use of a dynamic combinatorial library.

PubMed

Saggiomo, Vittorio; Lüning, Ulrich

2009-07-07

In a bulk membrane transport experiment, a dynamic combinatorial library (DCL) has been used to transport calcium ions; the calcium ions amplify the formation of a macrocyclic carrier which results in transport.

Counting Pizza Pieces and Other Combinatorial Problems.

ERIC Educational Resources Information Center

Maier, Eugene

1988-01-01

The general combinatorial problem of counting the number of regions into which the interior of a circle is divided by a family of lines is considered. A general formula is developed and its use is illustrated in two situations. (PK)

On the existence of binary simplex codes. [using combinatorial construction

NASA Technical Reports Server (NTRS)

Taylor, H.

1977-01-01

Using a simple combinatorial construction, the existence of a binary simplex code with m codewords for all m is greater than or equal to 1 is proved. The problem of the shortest possible length is left open.

Application of combinatorial biocatalysis for a unique ring expansion of dihydroxymethylzearalenone

USDA-ARS?s Scientific Manuscript database

Combinatorial biocatalysis was applied to generate a diverse set of dihydroxymethylzearalenone derivatives with modified ring structure. In one chemoenzymatic reaction sequence, dihydroxymethylzearalenone was first subjected to a unique enzyme-catalyzed oxidative ring opening reaction that creates ...

Complexity: an internet resource for analysis of DNA sequence complexity

PubMed Central

Orlov, Y. L.; Potapov, V. N.

2004-01-01

The search for DNA regions with low complexity is one of the pivotal tasks of modern structural analysis of complete genomes. The low complexity may be preconditioned by strong inequality in nucleotide content (biased composition), by tandem or dispersed repeats or by palindrome-hairpin structures, as well as by a combination of all these factors. Several numerical measures of textual complexity, including combinatorial and linguistic ones, together with complexity estimation using a modified Lempel–Ziv algorithm, have been implemented in a software tool called ‘Complexity’ (http://wwwmgs.bionet.nsc.ru/mgs/programs/low_complexity/). The software enables a user to search for low-complexity regions in long sequences, e.g. complete bacterial genomes or eukaryotic chromosomes. In addition, it estimates the complexity of groups of aligned sequences. PMID:15215465

The 1/ N Expansion of Tensor Models Beyond Perturbation Theory

NASA Astrophysics Data System (ADS)

Gurau, Razvan

2014-09-01

We analyze in full mathematical rigor the most general quartically perturbed invariant probability measure for a random tensor. Using a version of the Loop Vertex Expansion (which we call the mixed expansion) we show that the cumulants write as explicit series in 1/ N plus bounded rest terms. The mixed expansion recasts the problem of determining the subleading corrections in 1/ N into a simple combinatorial problem of counting trees decorated by a finite number of loop edges. As an aside, we use the mixed expansion to show that the (divergent) perturbative expansion of the tensor models is Borel summable and to prove that the cumulants respect an uniform scaling bound. In particular the quartically perturbed measures fall, in the N→ ∞ limit, in the universality class of Gaussian tensor models.

A Message Passing Approach to Side Chain Positioning with Applications in Protein Docking Refinement *

PubMed Central

Moghadasi, Mohammad; Kozakov, Dima; Mamonov, Artem B.; Vakili, Pirooz; Vajda, Sandor; Paschalidis, Ioannis Ch.

2013-01-01

We introduce a message-passing algorithm to solve the Side Chain Positioning (SCP) problem. SCP is a crucial component of protein docking refinement, which is a key step of an important class of problems in computational structural biology called protein docking. We model SCP as a combinatorial optimization problem and formulate it as a Maximum Weighted Independent Set (MWIS) problem. We then employ a modified and convergent belief-propagation algorithm to solve a relaxation of MWIS and develop randomized estimation heuristics that use the relaxed solution to obtain an effective MWIS feasible solution. Using a benchmark set of protein complexes we demonstrate that our approach leads to more accurate docking predictions compared to a baseline algorithm that does not solve the SCP. PMID:23515575

Consistency of a counterexample to Naimark's problem

PubMed Central

Akemann, Charles; Weaver, Nik

2004-01-01

We construct a C*-algebra that has only one irreducible representation up to unitary equivalence but is not isomorphic to the algebra of compact operators on any Hilbert space. This answers an old question of Naimark. Our construction uses a combinatorial statement called the diamond principle, which is known to be consistent with but not provable from the standard axioms of set theory (assuming that these axioms are consistent). We prove that the statement “there exists a counterexample to Naimark's problem which is generated by \\documentclass[10pt]{article} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{pmc} \\usepackage[Euler]{upgreek} \\pagestyle{empty} \\oddsidemargin -1.0in \\begin{document} \\begin{equation*}{\\aleph}_{1}\\end{equation*}\\end{document} elements” is undecidable in standard set theory. PMID:15131270

Perspectives on object manipulation and action grammar for percussive actions in primates

PubMed Central

Hayashi, Misato

2015-01-01

The skill of object manipulation is a common feature of primates including humans, although there are species-typical patterns of manipulation. Object manipulation can be used as a comparative scale of cognitive development, focusing on its complexity. Nut cracking in chimpanzees has the highest hierarchical complexity of tool use reported in non-human primates. An analysis of the patterns of object manipulation in naive chimpanzees after nut-cracking demonstrations revealed the cause of difficulties in learning nut-cracking behaviour. Various types of behaviours exhibited within a nut-cracking context can be examined in terms of the application of problem-solving strategies, focusing on their basis in causal understanding or insightful intentionality. Captive chimpanzees also exhibit complex forms of combinatory manipulation, which is the precursor of tool use. A new notation system of object manipulation was invented to assess grammatical rules in manipulative actions. The notation system of action grammar enabled direct comparisons to be made between primates including humans in a variety of object-manipulation tasks, including percussive-tool use. PMID:26483528

Perspectives on object manipulation and action grammar for percussive actions in primates.

PubMed

Hayashi, Misato

2015-11-19

The skill of object manipulation is a common feature of primates including humans, although there are species-typical patterns of manipulation. Object manipulation can be used as a comparative scale of cognitive development, focusing on its complexity. Nut cracking in chimpanzees has the highest hierarchical complexity of tool use reported in non-human primates. An analysis of the patterns of object manipulation in naive chimpanzees after nut-cracking demonstrations revealed the cause of difficulties in learning nut-cracking behaviour. Various types of behaviours exhibited within a nut-cracking context can be examined in terms of the application of problem-solving strategies, focusing on their basis in causal understanding or insightful intentionality. Captive chimpanzees also exhibit complex forms of combinatory manipulation, which is the precursor of tool use. A new notation system of object manipulation was invented to assess grammatical rules in manipulative actions. The notation system of action grammar enabled direct comparisons to be made between primates including humans in a variety of object-manipulation tasks, including percussive-tool use. © 2015 The Author(s).

A hybrid genetic algorithm for solving bi-objective traveling salesman problems

NASA Astrophysics Data System (ADS)

Ma, Mei; Li, Hecheng

2017-08-01

The traveling salesman problem (TSP) is a typical combinatorial optimization problem, in a traditional TSP only tour distance is taken as a unique objective to be minimized. When more than one optimization objective arises, the problem is known as a multi-objective TSP. In the present paper, a bi-objective traveling salesman problem (BOTSP) is taken into account, where both the distance and the cost are taken as optimization objectives. In order to efficiently solve the problem, a hybrid genetic algorithm is proposed. Firstly, two satisfaction degree indices are provided for each edge by considering the influences of the distance and the cost weight. The first satisfaction degree is used to select edges in a “rough” way, while the second satisfaction degree is executed for a more “refined” choice. Secondly, two satisfaction degrees are also applied to generate new individuals in the iteration process. Finally, based on genetic algorithm framework as well as 2-opt selection strategy, a hybrid genetic algorithm is proposed. The simulation illustrates the efficiency of the proposed algorithm.

Criticism of EFSA's scientific opinion on combinatorial effects of 'stacked' GM plants.

PubMed

Bøhn, Thomas

2018-01-01

Recent genetically modified plants tend to include both insect resistance and herbicide tolerance traits. Some of these 'stacked' GM plants have multiple Cry-toxins expressed as well as tolerance to several herbicides. This means that non-target organisms in the environment (biodiversity) will be co-exposed to multiple stressors simultaneously. A similar co-exposure may happen to consumers through chemical residues in the food chain. EFSA, the responsible unit for minimizing risk of harm in European food chains, has expressed its scientific interest in combinatorial effects. However, when new data showed how two Cry-toxins acted in combination (added toxicity), and that the same Cry-toxins showed combinatorial effects when co-exposed with Roundup (Bøhn et al., 2016), EFSA dismissed these new peer-reviewed results. In effect, EFSA claimed that combinatorial effects are not relevant for itself. EFSA was justifying this by referring to a policy question, and by making invalid assumptions, which could have been checked directly with the lead-author. With such approach, EFSA may miss the opportunity to improve its environmental and health risk assessment of toxins and pesticides in the food chain. Failure to follow its own published requests for combinatorial effects research, may also risk jeopardizing EFSA's scientific and public reputation. Copyright © 2017. Published by Elsevier Ltd.

Magnetic separation: its application in mining, waste purification, medicine, biochemistry and chemistry.

PubMed

Iranmanesh, M; Hulliger, J

2017-10-02

The use of strong magnetic field gradients and high magnetic fields generated by permanent magnets or superconducting coils has found applications in many fields such as mining, solid state chemistry, biochemistry and medical research. Lab scale or industrial implementations involve separation of macro- and nanoparticles, cells, proteins, and macromolecules down to small molecules and ions. Most promising are those attempts where the object to be separated is attached to a strong magnetic nanoparticle. Here, all kinds of specific affinity interactions are used to attach magnetic carrier particles to mainly objects of biological interest. Other attempts use a strong paramagnetic suspension for the separation of purely diamagnetic objects, such as bio-macromolecules or heavy metals. The application of magnetic separation to superconducting inorganic phases is of particular interest in combination with ceramic combinatorial chemistry to generate a library of e.g. cuprate superconductors.

Running Clubs--A Combinatorial Investigation.

ERIC Educational Resources Information Center

Nissen, Phillip; Taylor, John

1991-01-01

Presented is a combinatorial problem based on the Hash House Harriers rule which states that the route of the run should not have previously been traversed by the club. Discovered is how many weeks the club can meet before the rule has to be broken. (KR)

Quantum Resonance Approach to Combinatorial Optimization

NASA Technical Reports Server (NTRS)

Zak, Michail

1997-01-01

It is shown that quantum resonance can be used for combinatorial optimization. The advantage of the approach is in independence of the computing time upon the dimensionality of the problem. As an example, the solution to a constraint satisfaction problem of exponential complexity is demonstrated.

Comprehensive human transcription factor binding site map for combinatory binding motifs discovery.

PubMed

Müller-Molina, Arnoldo J; Schöler, Hans R; Araúzo-Bravo, Marcos J

2012-01-01

To know the map between transcription factors (TFs) and their binding sites is essential to reverse engineer the regulation process. Only about 10%-20% of the transcription factor binding motifs (TFBMs) have been reported. This lack of data hinders understanding gene regulation. To address this drawback, we propose a computational method that exploits never used TF properties to discover the missing TFBMs and their sites in all human gene promoters. The method starts by predicting a dictionary of regulatory "DNA words." From this dictionary, it distills 4098 novel predictions. To disclose the crosstalk between motifs, an additional algorithm extracts TF combinatorial binding patterns creating a collection of TF regulatory syntactic rules. Using these rules, we narrowed down a list of 504 novel motifs that appear frequently in syntax patterns. We tested the predictions against 509 known motifs confirming that our system can reliably predict ab initio motifs with an accuracy of 81%-far higher than previous approaches. We found that on average, 90% of the discovered combinatorial binding patterns target at least 10 genes, suggesting that to control in an independent manner smaller gene sets, supplementary regulatory mechanisms are required. Additionally, we discovered that the new TFBMs and their combinatorial patterns convey biological meaning, targeting TFs and genes related to developmental functions. Thus, among all the possible available targets in the genome, the TFs tend to regulate other TFs and genes involved in developmental functions. We provide a comprehensive resource for regulation analysis that includes a dictionary of "DNA words," newly predicted motifs and their corresponding combinatorial patterns. Combinatorial patterns are a useful filter to discover TFBMs that play a major role in orchestrating other factors and thus, are likely to lock/unlock cellular functional clusters.

Comprehensive Human Transcription Factor Binding Site Map for Combinatory Binding Motifs Discovery

PubMed Central

Müller-Molina, Arnoldo J.; Schöler, Hans R.; Araúzo-Bravo, Marcos J.

2012-01-01

To know the map between transcription factors (TFs) and their binding sites is essential to reverse engineer the regulation process. Only about 10%–20% of the transcription factor binding motifs (TFBMs) have been reported. This lack of data hinders understanding gene regulation. To address this drawback, we propose a computational method that exploits never used TF properties to discover the missing TFBMs and their sites in all human gene promoters. The method starts by predicting a dictionary of regulatory “DNA words.” From this dictionary, it distills 4098 novel predictions. To disclose the crosstalk between motifs, an additional algorithm extracts TF combinatorial binding patterns creating a collection of TF regulatory syntactic rules. Using these rules, we narrowed down a list of 504 novel motifs that appear frequently in syntax patterns. We tested the predictions against 509 known motifs confirming that our system can reliably predict ab initio motifs with an accuracy of 81%—far higher than previous approaches. We found that on average, 90% of the discovered combinatorial binding patterns target at least 10 genes, suggesting that to control in an independent manner smaller gene sets, supplementary regulatory mechanisms are required. Additionally, we discovered that the new TFBMs and their combinatorial patterns convey biological meaning, targeting TFs and genes related to developmental functions. Thus, among all the possible available targets in the genome, the TFs tend to regulate other TFs and genes involved in developmental functions. We provide a comprehensive resource for regulation analysis that includes a dictionary of “DNA words,” newly predicted motifs and their corresponding combinatorial patterns. Combinatorial patterns are a useful filter to discover TFBMs that play a major role in orchestrating other factors and thus, are likely to lock/unlock cellular functional clusters. PMID:23209563

Random vs. Combinatorial Methods for Discrete Event Simulation of a Grid Computer Network

NASA Technical Reports Server (NTRS)

Kuhn, D. Richard; Kacker, Raghu; Lei, Yu

2010-01-01

This study compared random and t-way combinatorial inputs of a network simulator, to determine if these two approaches produce significantly different deadlock detection for varying network configurations. Modeling deadlock detection is important for analyzing configuration changes that could inadvertently degrade network operations, or to determine modifications that could be made by attackers to deliberately induce deadlock. Discrete event simulation of a network may be conducted using random generation, of inputs. In this study, we compare random with combinatorial generation of inputs. Combinatorial (or t-way) testing requires every combination of any t parameter values to be covered by at least one test. Combinatorial methods can be highly effective because empirical data suggest that nearly all failures involve the interaction of a small number of parameters (1 to 6). Thus, for example, if all deadlocks involve at most 5-way interactions between n parameters, then exhaustive testing of all n-way interactions adds no additional information that would not be obtained by testing all 5-way interactions. While the maximum degree of interaction between parameters involved in the deadlocks clearly cannot be known in advance, covering all t-way interactions may be more efficient than using random generation of inputs. In this study we tested this hypothesis for t = 2, 3, and 4 for deadlock detection in a network simulation. Achieving the same degree of coverage provided by 4-way tests would have required approximately 3.2 times as many random tests; thus combinatorial methods were more efficient for detecting deadlocks involving a higher degree of interactions. The paper reviews explanations for these results and implications for modeling and simulation.

Intrinsic information carriers in combinatorial dynamical systems

NASA Astrophysics Data System (ADS)

Harmer, Russ; Danos, Vincent; Feret, Jérôme; Krivine, Jean; Fontana, Walter

2010-09-01

Many proteins are composed of structural and chemical features—"sites" for short—characterized by definite interaction capabilities, such as noncovalent binding or covalent modification of other proteins. This modularity allows for varying degrees of independence, as the behavior of a site might be controlled by the state of some but not all sites of the ambient protein. Independence quickly generates a startling combinatorial complexity that shapes most biological networks, such as mammalian signaling systems, and effectively prevents their study in terms of kinetic equations—unless the complexity is radically trimmed. Yet, if combinatorial complexity is key to the system's behavior, eliminating it will prevent, not facilitate, understanding. A more adequate representation of a combinatorial system is provided by a graph-based framework of rewrite rules where each rule specifies only the information that an interaction mechanism depends on. Unlike reactions, which deal with molecular species, rules deal with patterns, i.e., multisets of molecular species. Although the stochastic dynamics induced by a collection of rules on a mixture of molecules can be simulated, it appears useful to capture the system's average or deterministic behavior by means of differential equations. However, expansion of the rules into kinetic equations at the level of molecular species is not only impractical, but conceptually indefensible. If rules describe bona fide patterns of interaction, molecular species are unlikely to constitute appropriate units of dynamics. Rather, we must seek aggregate variables reflective of the causal structure laid down by the rules. We call these variables "fragments" and the process of identifying them "fragmentation." Ideally, fragments are aspects of the system's microscopic population that the set of rules can actually distinguish on average; in practice, it may only be feasible to identify an approximation to this. Most importantly, fragments are self-consistent descriptors of system dynamics in that their time-evolution is governed by a closed system of kinetic equations. Taken together, fragments are endogenous distinctions that matter for the dynamics of a system, which warrants viewing them as the carriers of information. Although fragments can be thought of as multisets of molecular species (an extensional view), their self-consistency suggests treating them as autonomous aspects cut off from their microscopic realization (an intensional view). Fragmentation is a seeded process that depends on the choice of observables whose dynamics one insists to describe. Different observables can cause distinct fragmentations, in effect altering the set of information carriers that govern the behavior of a system, even though nothing has changed in its microscopic constitution. In this contribution, we present a mathematical specification of fragments, but not an algorithmic implementation. We have described the latter elsewhere in rather technical terms that, although effective, were lacking an embedding into a more general conceptual framework, which we here provide.

Intrinsic information carriers in combinatorial dynamical systems.

PubMed

Harmer, Russ; Danos, Vincent; Feret, Jérôme; Krivine, Jean; Fontana, Walter

2010-09-01

Many proteins are composed of structural and chemical features--"sites" for short--characterized by definite interaction capabilities, such as noncovalent binding or covalent modification of other proteins. This modularity allows for varying degrees of independence, as the behavior of a site might be controlled by the state of some but not all sites of the ambient protein. Independence quickly generates a startling combinatorial complexity that shapes most biological networks, such as mammalian signaling systems, and effectively prevents their study in terms of kinetic equations-unless the complexity is radically trimmed. Yet, if combinatorial complexity is key to the system's behavior, eliminating it will prevent, not facilitate, understanding. A more adequate representation of a combinatorial system is provided by a graph-based framework of rewrite rules where each rule specifies only the information that an interaction mechanism depends on. Unlike reactions, which deal with molecular species, rules deal with patterns, i.e., multisets of molecular species. Although the stochastic dynamics induced by a collection of rules on a mixture of molecules can be simulated, it appears useful to capture the system's average or deterministic behavior by means of differential equations. However, expansion of the rules into kinetic equations at the level of molecular species is not only impractical, but conceptually indefensible. If rules describe bona fide patterns of interaction, molecular species are unlikely to constitute appropriate units of dynamics. Rather, we must seek aggregate variables reflective of the causal structure laid down by the rules. We call these variables "fragments" and the process of identifying them "fragmentation." Ideally, fragments are aspects of the system's microscopic population that the set of rules can actually distinguish on average; in practice, it may only be feasible to identify an approximation to this. Most importantly, fragments are self-consistent descriptors of system dynamics in that their time-evolution is governed by a closed system of kinetic equations. Taken together, fragments are endogenous distinctions that matter for the dynamics of a system, which warrants viewing them as the carriers of information. Although fragments can be thought of as multisets of molecular species (an extensional view), their self-consistency suggests treating them as autonomous aspects cut off from their microscopic realization (an intensional view). Fragmentation is a seeded process that depends on the choice of observables whose dynamics one insists to describe. Different observables can cause distinct fragmentations, in effect altering the set of information carriers that govern the behavior of a system, even though nothing has changed in its microscopic constitution. In this contribution, we present a mathematical specification of fragments, but not an algorithmic implementation. We have described the latter elsewhere in rather technical terms that, although effective, were lacking an embedding into a more general conceptual framework, which we here provide.

Formal Operations and Ego Identity in Adolescence.

ERIC Educational Resources Information Center

Wagner, Janis A.

1987-01-01

Investigated the relationship between the development of formal operations and the formation of ego identity in adolescence. Obtained significant positive correlations between combinatorial ability and degree of identity, suggesting that high identity may facilitate the application of combinatorial operations. Found some gender differences in task…

Manipulating Combinatorial Structures.

ERIC Educational Resources Information Center

Labelle, Gilbert

This set of transparencies shows how the manipulation of combinatorial structures in the context of modern combinatorics can easily lead to interesting teaching and learning activities at every level of education from elementary school to university. The transparencies describe: (1) the importance and relations of combinatorics to science and…

Gian-Carlos Rota and Combinatorial Math.

ERIC Educational Resources Information Center

Kolata, Gina Bari

1979-01-01

Presents the first of a series of occasional articles about mathematics as seen through the eyes of its prominent scholars. In an interview with Gian-Carlos Rota of the Massachusetts Institute of Technology he discusses how combinatorial mathematics began as a field and its future. (HM)

A Model of Students' Combinatorial Thinking

ERIC Educational Resources Information Center

Lockwood, Elise

2013-01-01

Combinatorial topics have become increasingly prevalent in K-12 and undergraduate curricula, yet research on combinatorics education indicates that students face difficulties when solving counting problems. The research community has not yet addressed students' ways of thinking at a level that facilitates deeper understanding of how students…

The LATL as locus of composition: MEG evidence from English and Arabic.

PubMed

Westerlund, Masha; Kastner, Itamar; Al Kaabi, Meera; Pylkkänen, Liina

2015-02-01

Neurolinguistic investigations into the processing of structured sentences as well as simple adjective-noun phrases point to the left anterior temporal lobe (LATL) as a leading candidate for basic linguistic composition. Here, we characterized the combinatory profile of the LATL over a variety of syntactic and semantic environments, and across two languages, English and Arabic. The contribution of the LATL was investigated across two types of composition: the optional modification of a predicate (modification) and the satisfaction of a predicate's argument position (argument saturation). Target words were presented during MEG recordings, either in combinatory contexts (e.g. "eats meat") or in non-combinatory contexts (preceded by an unpronounceable consonant string, e.g. "xqkr meat"). Across both languages, the LATL showed increased responses to words in combinatory contexts, an effect that was robust to composition type and word order. Together with related findings, these results solidify the role of the LATL in basic semantic composition. Copyright © 2014 Elsevier Inc. All rights reserved.

DNA Assembly Techniques for Next Generation Combinatorial Biosynthesis of Natural Products

PubMed Central

Cobb, Ryan E.; Ning, Jonathan C.; Zhao, Huimin

2013-01-01

Natural product scaffolds remain important leads for pharmaceutical development. However, transforming a natural product into a drug entity often requires derivatization to enhance the compound’s therapeutic properties. A powerful method by which to perform this derivatization is combinatorial biosynthesis, the manipulation of the genes in the corresponding pathway to divert synthesis towards novel derivatives. While these manipulations have traditionally been carried out via restriction digestion/ligation-based cloning, the shortcomings of such techniques limit their throughput and thus the scope of corresponding combinatorial biosynthesis experiments. In the burgeoning field of synthetic biology, the demand for facile DNA assembly techniques has promoted the development of a host of novel DNA assembly strategies. Here we describe the advantages of these recently-developed tools for rapid, efficient synthesis of large DNA constructs. We also discuss their potential to facilitate the simultaneous assembly of complete libraries of natural product biosynthetic pathways, ushering in the next generation of combinatorial biosynthesis. PMID:24127070

Novel Design Strategy for Checkpoint Kinase 2 Inhibitors Using Pharmacophore Modeling, Combinatorial Fusion, and Virtual Screening

PubMed Central

Wang, Yen-Ling

2014-01-01

Checkpoint kinase 2 (Chk2) has a great effect on DNA-damage and plays an important role in response to DNA double-strand breaks and related lesions. In this study, we will concentrate on Chk2 and the purpose is to find the potential inhibitors by the pharmacophore hypotheses (PhModels), combinatorial fusion, and virtual screening techniques. Applying combinatorial fusion into PhModels and virtual screening techniques is a novel design strategy for drug design. We used combinatorial fusion to analyze the prediction results and then obtained the best correlation coefficient of the testing set (r test) with the value 0.816 by combining the BesttrainBesttest and FasttrainFasttest prediction results. The potential inhibitors were selected from NCI database by screening according to BesttrainBesttest + FasttrainFasttest prediction results and molecular docking with CDOCKER docking program. Finally, the selected compounds have high interaction energy between a ligand and a receptor. Through these approaches, 23 potential inhibitors for Chk2 are retrieved for further study. PMID:24864236

In vitro and direct in vivo testing of mixture-based combinatorial libraries for the identification of highly active and specific opiate ligands.

PubMed

Houghten, Richard A; Dooley, Colette T; Appel, Jon R

2006-05-26

The use of combinatorial libraries for the identification of novel opiate and related ligands in opioid receptor assays is reviewed. Case studies involving opioid assays used to demonstrate the viability of combinatorial libraries are described. The identification of new opioid peptides composed of L-amino acids, D-amino acids, or L-, D-, and unnatural amino acids is reviewed. New opioid compounds have also been identified from peptidomimetic libraries, such as peptoids and alkylated dipeptides, and those identified from acyclic (eg, polyamine, urea) and heterocyclic (eg, bicyclic guanidine) libraries are reviewed.

Experimental Design for Combinatorial and High Throughput Materials Development

NASA Astrophysics Data System (ADS)

Cawse, James N.

2002-12-01

In the past decade, combinatorial and high throughput experimental methods have revolutionized the pharmaceutical industry, allowing researchers to conduct more experiments in a week than was previously possible in a year. Now high throughput experimentation is rapidly spreading from its origins in the pharmaceutical world to larger industrial research establishments such as GE and DuPont, and even to smaller companies and universities. Consequently, researchers need to know the kinds of problems, desired outcomes, and appropriate patterns for these new strategies. Editor James Cawse's far-reaching study identifies and applies, with specific examples, these important new principles and techniques. Experimental Design for Combinatorial and High Throughput Materials Development progresses from methods that are now standard, such as gradient arrays, to mathematical developments that are breaking new ground. The former will be particularly useful to researchers entering the field, while the latter should inspire and challenge advanced practitioners. The book's contents are contributed by leading researchers in their respective fields. Chapters include: -High Throughput Synthetic Approaches for the Investigation of Inorganic Phase Space -Combinatorial Mapping of Polymer Blends Phase Behavior -Split-Plot Designs -Artificial Neural Networks in Catalyst Development -The Monte Carlo Approach to Library Design and Redesign This book also contains over 200 useful charts and drawings. Industrial chemists, chemical engineers, materials scientists, and physicists working in combinatorial and high throughput chemistry will find James Cawse's study to be an invaluable resource.

Quantum Efficiency and Bandgap Analysis for Combinatorial Photovoltaics: Sorting Activity of Cu–O Compounds in All-Oxide Device Libraries

PubMed Central

2014-01-01

All-oxide-based photovoltaics (PVs) encompass the potential for extremely low cost solar cells, provided they can obtain an order of magnitude improvement in their power conversion efficiencies. To achieve this goal, we perform a combinatorial materials study of metal oxide based light absorbers, charge transporters, junctions between them, and PV devices. Here we report the development of a combinatorial internal quantum efficiency (IQE) method. IQE measures the efficiency associated with the charge separation and collection processes, and thus is a proxy for PV activity of materials once placed into devices, discarding optical properties that cause uncontrolled light harvesting. The IQE is supported by high-throughput techniques for bandgap fitting, composition analysis, and thickness mapping, which are also crucial parameters for the combinatorial investigation cycle of photovoltaics. As a model system we use a library of 169 solar cells with a varying thickness of sprayed titanium dioxide (TiO2) as the window layer, and covarying thickness and composition of binary compounds of copper oxides (Cu–O) as the light absorber, fabricated by Pulsed Laser Deposition (PLD). The analysis on the combinatorial devices shows the correlation between compositions and bandgap, and their effect on PV activity within several device configurations. The analysis suggests that the presence of Cu4O3 plays a significant role in the PV activity of binary Cu–O compounds. PMID:24410367

Combinatorial enzyme technology: Conversion of pectin to oligo species and its effect on microbial growth

USDA-ARS?s Scientific Manuscript database

Plant cell wall polysaccharides, which consist of polymeric backbones with various types of substitution, were studied using the concept of combinatorial enzyme technology for conversion of agricultural fibers to functional products. Using citrus pectin as the starting substrate, an active oligo spe...

Students' Verification Strategies for Combinatorial Problems

ERIC Educational Resources Information Center

Mashiach Eizenberg, Michal; Zaslavsky, Orit

2004-01-01

We focus on a major difficulty in solving combinatorial problems, namely, on the verification of a solution. Our study aimed at identifying undergraduate students' tendencies to verify their solutions, and the verification strategies that they employ when solving these problems. In addition, an attempt was made to evaluate the level of efficiency…

Applications of Combinatorial Programming to Data Analysis: The Traveling Salesman and Related Problems

ERIC Educational Resources Information Center

Hubert, Lawrence J.; Baker, Frank B.

1978-01-01

The "Traveling Salesman" and similar combinatorial programming tasks encountered in operations research are discussed as possible data analysis models in psychology, for example, in developmental scaling, Guttman scaling, profile smoothing, and data array clustering. A short overview of various computational approaches from this area of…

Nash Social Welfare in Multiagent Resource Allocation

NASA Astrophysics Data System (ADS)

Ramezani, Sara; Endriss, Ulle

We study different aspects of the multiagent resource allocation problem when the objective is to find an allocation that maximizes Nash social welfare, the product of the utilities of the individual agents. The Nash solution is an important welfare criterion that combines efficiency and fairness considerations. We show that the problem of finding an optimal outcome is NP-hard for a number of different languages for representing agent preferences; we establish new results regarding convergence to Nash-optimal outcomes in a distributed negotiation framework; and we design and test algorithms similar to those applied in combinatorial auctions for computing such an outcome directly.

The Syntax and Meaning of Wild Gibbon Songs

PubMed Central

Clarke, Esther; Reichard, Ulrich H.; Zuberbühler, Klaus

2006-01-01

Spoken language is a result of the human capacity to assemble simple vocal units into more complex utterances, the basic carriers of semantic information. Not much is known about the evolutionary origins of this behaviour. The vocal abilities of non-human primates are relatively unimpressive in comparison, with gibbon songs being a rare exception. These apes assemble a repertoire of call notes into elaborate songs, which function to repel conspecific intruders, advertise pair bonds, and attract mates. We conducted a series of field experiments with white-handed gibbons at Khao Yai National Park, Thailand, which showed that this ape species uses songs also to protect themselves against predation. We compared the acoustic structure of predatory-induced songs with regular songs that were given as part of their daily routine. Predator-induced songs were identical to normal songs in the call note repertoire, but we found consistent differences in how the notes were assembled into songs. The responses of out-of-sight receivers demonstrated that these syntactic differences were meaningful to conspecifics. Our study provides the first evidence of referential signalling in a free-ranging ape species, based on a communication system that utilises combinatorial rules. PMID:17183705

Robust Multi-unit Auction Protocol against False-name Bids

NASA Astrophysics Data System (ADS)

Yokoo, Makoto; Sakurai, Yuko; Matsubara, Shigeo

This paper presents a new multi-unit auction protocol (IR protocol) that is robust against false-name bids. Internet auctions have become an integral part of Electronic Commerce and a promising field for applying agent and Artificial Intelligence technologies. Although the Internet provides an excellent infrastructure for executing auctions, the possibility of a new type of cheating called false-name bids has been pointed out. A false-name bid is a bid submitted under a fictitious name. A protocol called LDS has been developed for combinatorial auctions of multiple different items and has proven to be robust against false-name bids. Although we can modify the LDS protocol to handle multi-unit auctions, in which multiple units of an identical item are auctioned, the protocol is complicated and requires the auctioneer to carefully pre-determine the combination of bundles to obtain a high social surplus or revenue. For the auctioneer, our newly developed IR protocol is easier to use than the LDS, since the combination of bundles is automatically determined in a flexible manner according to the declared evaluation values of agents. The evaluation results show that the IR protocol can obtain a better social surplus than that obtained by the LDS protocol.

Phase transition in the countdown problem

NASA Astrophysics Data System (ADS)

Lacasa, Lucas; Luque, Bartolo

2012-07-01

We present a combinatorial decision problem, inspired by the celebrated quiz show called Countdown, that involves the computation of a given target number T from a set of k randomly chosen integers along with a set of arithmetic operations. We find that the probability of winning the game evidences a threshold phenomenon that can be understood in the terms of an algorithmic phase transition as a function of the set size k. Numerical simulations show that such probability sharply transitions from zero to one at some critical value of the control parameter, hence separating the algorithm's parameter space in different phases. We also find that the system is maximally efficient close to the critical point. We derive analytical expressions that match the numerical results for finite size and permit us to extrapolate the behavior in the thermodynamic limit.

PERMutation Using Transposase Engineering (PERMUTE): A Simple Approach for Constructing Circularly Permuted Protein Libraries.

PubMed

Jones, Alicia M; Atkinson, Joshua T; Silberg, Jonathan J

2017-01-01

Rearrangements that alter the order of a protein's sequence are used in the lab to study protein folding, improve activity, and build molecular switches. One of the simplest ways to rearrange a protein sequence is through random circular permutation, where native protein termini are linked together and new termini are created elsewhere through random backbone fission. Transposase mutagenesis has emerged as a simple way to generate libraries encoding different circularly permuted variants of proteins. With this approach, a synthetic transposon (called a permuteposon) is randomly inserted throughout a circularized gene to generate vectors that express different permuted variants of a protein. In this chapter, we outline the protocol for constructing combinatorial libraries of circularly permuted proteins using transposase mutagenesis, and we describe the different permuteposons that have been developed to facilitate library construction.

Quantum Adiabatic Optimization and Combinatorial Landscapes

NASA Technical Reports Server (NTRS)

Smelyanskiy, V. N.; Knysh, S.; Morris, R. D.

2003-01-01

In this paper we analyze the performance of the Quantum Adiabatic Evolution (QAE) algorithm on a variant of Satisfiability problem for an ensemble of random graphs parametrized by the ratio of clauses to variables, gamma = M / N. We introduce a set of macroscopic parameters (landscapes) and put forward an ansatz of universality for random bit flips. We then formulate the problem of finding the smallest eigenvalue and the excitation gap as a statistical mechanics problem. We use the so-called annealing approximation with a refinement that a finite set of macroscopic variables (verses only energy) is used, and are able to show the existence of a dynamic threshold gamma = gammad, beyond which QAE should take an exponentially long time to find a solution. We compare the results for extended and simplified sets of landscapes and provide numerical evidence in support of our universality ansatz.

Experimental design for estimating unknown groundwater pumping using genetic algorithm and reduced order model

NASA Astrophysics Data System (ADS)

Ushijima, Timothy T.; Yeh, William W.-G.

2013-10-01

An optimal experimental design algorithm is developed to select locations for a network of observation wells that provide maximum information about unknown groundwater pumping in a confined, anisotropic aquifer. The design uses a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. The formulated optimization problem is non-convex and contains integer variables necessitating a combinatorial search. Given a realistic large-scale model, the size of the combinatorial search required can make the problem difficult, if not impossible, to solve using traditional mathematical programming techniques. Genetic algorithms (GAs) can be used to perform the global search; however, because a GA requires a large number of calls to a groundwater model, the formulated optimization problem still may be infeasible to solve. As a result, proper orthogonal decomposition (POD) is applied to the groundwater model to reduce its dimensionality. Then, the information matrix in the full model space can be searched without solving the full model. Results from a small-scale test case show identical optimal solutions among the GA, integer programming, and exhaustive search methods. This demonstrates the GA's ability to determine the optimal solution. In addition, the results show that a GA with POD model reduction is several orders of magnitude faster in finding the optimal solution than a GA using the full model. The proposed experimental design algorithm is applied to a realistic, two-dimensional, large-scale groundwater problem. The GA converged to a solution for this large-scale problem.

Combining on-chip synthesis of a focused combinatorial library with computational target prediction reveals imidazopyridine GPCR ligands.

PubMed

Reutlinger, Michael; Rodrigues, Tiago; Schneider, Petra; Schneider, Gisbert

2014-01-07

Using the example of the Ugi three-component reaction we report a fast and efficient microfluidic-assisted entry into the imidazopyridine scaffold, where building block prioritization was coupled to a new computational method for predicting ligand-target associations. We identified an innovative GPCR-modulating combinatorial chemotype featuring ligand-efficient adenosine A1/2B and adrenergic α1A/B receptor antagonists. Our results suggest the tight integration of microfluidics-assisted synthesis with computer-based target prediction as a viable approach to rapidly generate bioactivity-focused combinatorial compound libraries with high success rates. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Generation of Dynamic Combinatorial Libraries Using Hydrazone‐Functionalized Surface Mimetics

PubMed Central

Hewitt, Sarah H.

2018-01-01

Dynamic combinatorial chemistry (DCC) represents an approach, whereby traditional supramolecular scaffolds used for protein surface recognition might be exploited to achieve selective high affinity target recognition. Synthesis, in situ screening and amplification under selection pressure allows the generation of ligands, which bear different moieties capable of making multivalent non‐covalent interactions with target proteins. Generic tetracarboxyphenyl porphyrin scaffolds bearing four hydrazide moieties have been used to form dynamic combinatorial libraries (DCLs) using aniline‐catalyzed reversible hydrazone exchange reactions, in 10 % DMSO, 5 mm NH4OAc, at pH 6.75. High resolution mass spectrometry (HRMS) was used to monitor library composition and establish conditions under which equilibria were established.

Automated Combinatorial Chemistry in the Organic Chemistry Majors Laboratory

ERIC Educational Resources Information Center

Nichols, Christopher J.; Hanne, Larry F.

2010-01-01

A multidisciplinary experiment has been developed in which students each synthesize a combinatorial library of 48 hydrazones with the aid of a liquid-handling robot. Each product is then subjected to a Kirby-Bauer disk diffusion assay to assess its antibacterial activity. Students gain experience working with automation and at the…

More Combinatorial Proofs via Flagpole Arrangements

ERIC Educational Resources Information Center

DeTemple, Duane; Reynolds, H. David, II

2006-01-01

Combinatorial identities are proved by counting the number of arrangements of a flagpole and guy wires on a row of blocks that satisfy a set of conditions. An identity is proved by first deriving and then equating two expressions that each count the number of permissible arrangements. Identities for binomial coefficients and recursion relations…

Children's Strategies for Solving Two- and Three-Dimensional Combinatorial Problems.

ERIC Educational Resources Information Center

English, Lyn D.

1993-01-01

Investigated strategies that 7- to 12-year-old children (n=96) spontaneously applied in solving novel combinatorial problems. With experience in solving two-dimensional problems, children were able to refine their strategies and adapt them to three dimensions. Results on some problems indicated significant effects of age. (Contains 32 references.)…

Identities for Generalized Fibonacci Numbers: A Combinatorial Approach

ERIC Educational Resources Information Center

Plaza, A.; Falcon, S.

2008-01-01

This note shows a combinatorial approach to some identities for generalized Fibonacci numbers. While it is a straightforward task to prove these identities with induction, and also by arithmetical manipulations such as rearrangements, the approach used here is quite simple to follow and eventually reduces the proof to a counting problem. (Contains…

Combinatorial Partial Hydrogenation Reactions of 4-Nitroacetophenone: An Undergraduate Organic Laboratory

ERIC Educational Resources Information Center

Kittredge, Kevin W.; Marine, Susan S.; Taylor, Richard T.

2004-01-01

A molecule possessing other functional groups that could be hydrogenerated is examined, where a variety of metal catalysts are evaluated under similar reaction conditions. Optimizing organic reactions is both time and labor intensive, and the use of a combinatorial parallel synthesis reactor was great time saving device, as per summary.

Human Performance on the Traveling Salesman and Related Problems: A Review

ERIC Educational Resources Information Center

MacGregor, James N.; Chu, Yun

2011-01-01

The article provides a review of recent research on human performance on the traveling salesman problem (TSP) and related combinatorial optimization problems. We discuss what combinatorial optimization problems are, why they are important, and why they may be of interest to cognitive scientists. We next describe the main characteristics of human…

Heuristic Implementation of Dynamic Programming for Matrix Permutation Problems in Combinatorial Data Analysis

ERIC Educational Resources Information Center

Brusco, Michael J.; Kohn, Hans-Friedrich; Stahl, Stephanie

2008-01-01

Dynamic programming methods for matrix permutation problems in combinatorial data analysis can produce globally-optimal solutions for matrices up to size 30x30, but are computationally infeasible for larger matrices because of enormous computer memory requirements. Branch-and-bound methods also guarantee globally-optimal solutions, but computation…

Iconicity and the Emergence of Combinatorial Structure in Language

ERIC Educational Resources Information Center

Verhoef, Tessa; Kirby, Simon; de Boer, Bart

2016-01-01

In language, recombination of a discrete set of meaningless building blocks forms an unlimited set of possible utterances. How such combinatorial structure emerged in the evolution of human language is increasingly being studied. It has been shown that it can emerge when languages culturally evolve and adapt to human cognitive biases. How the…

Novel design strategy for checkpoint kinase 2 inhibitors using pharmacophore modeling, combinatorial fusion, and virtual screening.

PubMed

Lin, Chun-Yuan; Wang, Yen-Ling

2014-01-01

Checkpoint kinase 2 (Chk2) has a great effect on DNA-damage and plays an important role in response to DNA double-strand breaks and related lesions. In this study, we will concentrate on Chk2 and the purpose is to find the potential inhibitors by the pharmacophore hypotheses (PhModels), combinatorial fusion, and virtual screening techniques. Applying combinatorial fusion into PhModels and virtual screening techniques is a novel design strategy for drug design. We used combinatorial fusion to analyze the prediction results and then obtained the best correlation coefficient of the testing set (r test) with the value 0.816 by combining the Best(train)Best(test) and Fast(train)Fast(test) prediction results. The potential inhibitors were selected from NCI database by screening according to Best(train)Best(test) + Fast(train)Fast(test) prediction results and molecular docking with CDOCKER docking program. Finally, the selected compounds have high interaction energy between a ligand and a receptor. Through these approaches, 23 potential inhibitors for Chk2 are retrieved for further study.

A combinatorial filtering method for magnetotelluric time-series based on Hilbert-Huang transform

NASA Astrophysics Data System (ADS)

Cai, Jianhua

2014-11-01

Magnetotelluric (MT) time-series are often contaminated with noise from natural or man-made processes. A substantial improvement is possible when the time-series are presented as clean as possible for further processing. A combinatorial method is described for filtering of MT time-series based on the Hilbert-Huang transform that requires a minimum of human intervention and leaves good data sections unchanged. Good data sections are preserved because after empirical mode decomposition the data are analysed through hierarchies, morphological filtering, adaptive threshold and multi-point smoothing, allowing separation of noise from signals. The combinatorial method can be carried out without any assumption about the data distribution. Simulated data and the real measured MT time-series from three different regions, with noise caused by baseline drift, high frequency noise and power-line contribution, are processed to demonstrate the application of the proposed method. Results highlight the ability of the combinatorial method to pick out useful signals, and the noise is suppressed greatly so that their deleterious influence is eliminated for the MT transfer function estimation.

Combinatorial discovery of new methanol-tolerant non-noble metal cathode electrocatalysts for direct methanol fuel cells.

PubMed

Yu, Jong-Sung; Kim, Min-Sik; Kim, Jung Ho

2010-12-14

Combinatorial synthesis and screening were used to identify methanol-tolerant non-platinum cathode electrocatalysts for use in direct methanol fuel cells (DMFCs). Oxygen reduction consumes protons at the surface of DMFC cathode catalysts. In combinatorial screening, this pH change allows one to differentiate active catalysts using fluorescent acid-base indicators. Combinatorial libraries of carbon-supported catalyst compositions containing Ru, Mo, W, Sn, and Se were screened. Ternary and quaternary compositions containing Ru, Sn, Mo, Se were more active than the "standard" Alonso-Vante catalyst, Ru(3)Mo(0.08)Se(2), when tested in liquid-feed DMFCs. Physical characterization of the most active catalysts by powder X-ray diffraction, gas adsorption, and X-ray photoelectron spectroscopy revealed that the predominant crystalline phase was hexagonal close-packed (hcp) ruthenium, and showed a surface mostly covered with oxide. The best new catalyst, Ru(7.0)Sn(1.0)Se(1.0), was significantly more active than Ru(3)Se(2)Mo(0.08), even though the latter contained smaller particles.

Combinatorial Characterization of TiO2 Chemical Vapor Deposition Utilizing Titanium Isopropoxide.

PubMed

Reinke, Michael; Ponomarev, Evgeniy; Kuzminykh, Yury; Hoffmann, Patrik

2015-07-13

The combinatorial characterization of the growth kinetics in chemical vapor deposition processes is challenging because precise information about the local precursor flow is usually difficult to access. In consequence, combinatorial chemical vapor deposition techniques are utilized more to study functional properties of thin films as a function of chemical composition, growth rate or crystallinity than to study the growth process itself. We present an experimental procedure which allows the combinatorial study of precursor surface kinetics during the film growth using high vacuum chemical vapor deposition. As consequence of the high vacuum environment, the precursor transport takes place in the molecular flow regime, which allows predicting and modifying precursor impinging rates on the substrate with comparatively little experimental effort. In this contribution, we study the surface kinetics of titanium dioxide formation using titanium tetraisopropoxide as precursor molecule over a large parameter range. We discuss precursor flux and temperature dependent morphology, crystallinity, growth rates, and precursor deposition efficiency. We conclude that the surface reaction of the adsorbed precursor molecules comprises a higher order reaction component with respect to precursor surface coverage.

Combinatorial programming of human neuronal progenitors using magnetically-guided stoichiometric mRNA delivery.

PubMed

Azimi, Sayyed M; Sheridan, Steven D; Ghannad-Rezaie, Mostafa; Eimon, Peter M; Yanik, Mehmet Fatih

2018-05-01

Identification of optimal transcription-factor expression patterns to direct cellular differentiation along a desired pathway presents significant challenges. We demonstrate massively combinatorial screening of temporally-varying mRNA transcription factors to direct differentiation of neural progenitor cells using a dynamically-reconfigurable magnetically-guided spotting technology for localizing mRNA, enabling experiments on millimetre size spots. In addition, we present a time-interleaved delivery method that dramatically reduces fluctuations in the delivered transcription-factor copy-numbers per cell. We screened combinatorial and temporal delivery of a pool of midbrain-specific transcription factors to augment the generation of dopaminergic neurons. We show that the combinatorial delivery of LMX1A, FOXA2 and PITX3 is highly effective in generating dopaminergic neurons from midbrain progenitors. We show that LMX1A significantly increases TH -expression levels when delivered to neural progenitor cells either during proliferation or after induction of neural differentiation, while FOXA2 and PITX3 increase expression only when delivered prior to induction, demonstrating temporal dependence of factor addition. © 2018, Azimi et al.

Particle-Based Microarrays of Oligonucleotides and Oligopeptides.

PubMed

Nesterov-Mueller, Alexander; Maerkle, Frieder; Hahn, Lothar; Foertsch, Tobias; Schillo, Sebastian; Bykovskaya, Valentina; Sedlmayr, Martyna; Weber, Laura K; Ridder, Barbara; Soehindrijo, Miriam; Muenster, Bastian; Striffler, Jakob; Bischoff, F Ralf; Breitling, Frank; Loeffler, Felix F

2014-10-28

In this review, we describe different methods of microarray fabrication based on the use of micro-particles/-beads and point out future tendencies in the development of particle-based arrays. First, we consider oligonucleotide bead arrays, where each bead is a carrier of one specific sequence of oligonucleotides. This bead-based array approach, appearing in the late 1990s, enabled high-throughput oligonucleotide analysis and had a large impact on genome research. Furthermore, we consider particle-based peptide array fabrication using combinatorial chemistry. In this approach, particles can directly participate in both the synthesis and the transfer of synthesized combinatorial molecules to a substrate. Subsequently, we describe in more detail the synthesis of peptide arrays with amino acid polymer particles, which imbed the amino acids inside their polymer matrix. By heating these particles, the polymer matrix is transformed into a highly viscous gel, and thereby, imbedded monomers are allowed to participate in the coupling reaction. Finally, we focus on combinatorial laser fusing of particles for the synthesis of high-density peptide arrays. This method combines the advantages of particles and combinatorial lithographic approaches.

Particle-Based Microarrays of Oligonucleotides and Oligopeptides

PubMed Central

Nesterov-Mueller, Alexander; Maerkle, Frieder; Hahn, Lothar; Foertsch, Tobias; Schillo, Sebastian; Bykovskaya, Valentina; Sedlmayr, Martyna; Weber, Laura K.; Ridder, Barbara; Soehindrijo, Miriam; Muenster, Bastian; Striffler, Jakob; Bischoff, F. Ralf; Breitling, Frank; Loeffler, Felix F.

2014-01-01

In this review, we describe different methods of microarray fabrication based on the use of micro-particles/-beads and point out future tendencies in the development of particle-based arrays. First, we consider oligonucleotide bead arrays, where each bead is a carrier of one specific sequence of oligonucleotides. This bead-based array approach, appearing in the late 1990s, enabled high-throughput oligonucleotide analysis and had a large impact on genome research. Furthermore, we consider particle-based peptide array fabrication using combinatorial chemistry. In this approach, particles can directly participate in both the synthesis and the transfer of synthesized combinatorial molecules to a substrate. Subsequently, we describe in more detail the synthesis of peptide arrays with amino acid polymer particles, which imbed the amino acids inside their polymer matrix. By heating these particles, the polymer matrix is transformed into a highly viscous gel, and thereby, imbedded monomers are allowed to participate in the coupling reaction. Finally, we focus on combinatorial laser fusing of particles for the synthesis of high-density peptide arrays. This method combines the advantages of particles and combinatorial lithographic approaches. PMID:27600347

Combinatorially-generated library of 6-fluoroquinolone analogs as potential novel antitubercular agents: a chemometric and molecular modeling assessment.

PubMed

Minovski, Nikola; Perdih, Andrej; Solmajer, Tom

2012-05-01

The virtual combinatorial chemistry approach as a methodology for generating chemical libraries of structurally-similar analogs in a virtual environment was employed for building a general mixed virtual combinatorial library with a total of 53.871 6-FQ structural analogs, introducing the real synthetic pathways of three well known 6-FQ inhibitors. The druggability properties of the generated combinatorial 6-FQs were assessed using an in-house developed drug-likeness filter integrating the Lipinski/Veber rule-sets. The compounds recognized as drug-like were used as an external set for prediction of the biological activity values using a neural-networks (NN) model based on an experimentally-determined set of active 6-FQs. Furthermore, a subset of compounds was extracted from the pool of drug-like 6-FQs, with predicted biological activity, and subsequently used in virtual screening (VS) campaign combining pharmacophore modeling and molecular docking studies. This complex scheme, a powerful combination of chemometric and molecular modeling approaches provided novel QSAR guidelines that could aid in the further lead development of 6-FQs agents.

Solving Connected Subgraph Problems in Wildlife Conservation

NASA Astrophysics Data System (ADS)

Dilkina, Bistra; Gomes, Carla P.

We investigate mathematical formulations and solution techniques for a variant of the Connected Subgraph Problem. Given a connected graph with costs and profits associated with the nodes, the goal is to find a connected subgraph that contains a subset of distinguished vertices. In this work we focus on the budget-constrained version, where we maximize the total profit of the nodes in the subgraph subject to a budget constraint on the total cost. We propose several mixed-integer formulations for enforcing the subgraph connectivity requirement, which plays a key role in the combinatorial structure of the problem. We show that a new formulation based on subtour elimination constraints is more effective at capturing the combinatorial structure of the problem, providing significant advantages over the previously considered encoding which was based on a single commodity flow. We test our formulations on synthetic instances as well as on real-world instances of an important problem in environmental conservation concerning the design of wildlife corridors. Our encoding results in a much tighter LP relaxation, and more importantly, it results in finding better integer feasible solutions as well as much better upper bounds on the objective (often proving optimality or within less than 1% of optimality), both when considering the synthetic instances as well as the real-world wildlife corridor instances.

Identification of FVIII gene mutations in patients with hemophilia A using new combinatorial sequencing by hybridization

PubMed Central

Chetta, M.; Drmanac, A.; Santacroce, R.; Grandone, E.; Surrey, S.; Fortina, P.; Margaglione, M.

2008-01-01

BACKGROUND: Standard methods of mutation detection are time consuming in Hemophilia A (HA) rendering their application unavailable in some analysis such as prenatal diagnosis. OBJECTIVES: To evaluate the feasibility of combinatorial sequencing-by-hybridization (cSBH) as an alternative and reliable tool for mutation detection in FVIII gene. PATIENTS/METHODS: We have applied a new method of cSBH that uses two different colors for detection of multiple point mutations in the FVIII gene. The 26 exons encompassing the HA gene were analyzed in 7 newly diagnosed Italian patients and in 19 previously characterized individuals with FVIII deficiency. RESULTS: Data show that, when solution-phase TAMRA and QUASAR labeled 5-mer oligonucleotide sets mixed with unlabeled target PCR templates are co-hybridized in the presence of DNA ligase to universal 6-mer oligonucleotide probe-based arrays, a number of mutations can be successfully detected. The technique was reliable also in identifying a mutant FVIII allele in an obligate heterozygote. A novel missense mutation (Leu1843Thr) in exon 16 and three novel neutral polymorphisms are presented with an updated protocol for 2-color cSBH. CONCLUSIONS: cSBH is a reliable tool for mutation detection in FVIII gene and may represent a complementary method for the genetic screening of HA patients. PMID:20300295

The role of neural precursor cells and self assembling peptides in nerve regeneration

PubMed Central

2013-01-01

Objective Cranial nerve injury involves loss of central neural cells in the brain stem and surrounding support matrix, leading to severe functional impairment. Therapeutically targeting cellular replacement and enhancing structural support may promote neural regeneration. We examined the combinatorial effect of neural precursor cells (NPC) and self assembling peptide (SAP) administration on nerve regeneration. Methods Nerve injury was induced by clip compression of the rodent spinal cord. SAPs were injected immediately into the injured cord and NPCs at 2 weeks post-injury. Behavioral analysis was done weekly and rats were sacrificed at 11 weeks post injury. LFB-H&E staining was done on cord tissue to assess cavitation volume. Motor evoked potentials (MEP) were measured at week 11 to assess nerve conduction and Kaplan meier curves were created to compare survival estimates. Results NPCs and SAPs were distributed both caudal and rostral to the injury site. Behavioral analysis showed that SAP + NPC transplantation significantly improved locomotor score p <0.03) and enhanced survival (log rank test, p = 0.008) compared to control. SAP + NPC treatment also improved nerve conduction velocity (p = 0.008) but did not affect cavitation volume (p = 0.73). Conclusion Combinatorial NPC and SAP injection into injured nerve tissue may enhance neural repair and regeneration. PMID:24351041

Combinatorial effect of substratum properties on mesenchymal stem cell sheet engineering and subsequent multi-lineage differentiation.

PubMed

Chuah, Yon Jin; Zhang, Ying; Wu, Yingnan; Menon, Nishanth V; Goh, Ghim Hian; Lee, Ann Charlene; Chan, Vincent; Zhang, Yilei; Kang, Yuejun

2015-09-01

Cell sheet engineering has been exploited as an alternative approach in tissue regeneration and the use of stem cells to generate cell sheets has further showed its potential in stem cell-mediated tissue regeneration. There exist vast interests in developing strategies to enhance the formation of stem cell sheets for downstream applications. It has been proved that stem cells are sensitive to the biophysical cues of the microenvironment. Therefore we hypothesized that the combinatorial substratum properties could be tailored to modulate the development of cell sheet formation and further influence its multipotency. For validation, polydimethylsiloxane (PDMS) of different combinatorial substratum properties (including stiffness, roughness and wettability) were created, on which the human bone marrow derived mesenchymal stem cells (BMSCs) were cultured to form cell sheets with their multipotency evaluated after induced differentiation. The results showed that different combinatorial effects of these substratum properties were able to influence BMSC behavior such as adhesion, spreading and proliferation during cell sheet development. Collagen formation within the cell sheet was enhanced on substrates with lower stiffness, higher hydrophobicity and roughness, which further assisted the induced chondrogenesis and osteogenesis, respectively. These findings suggested that combinatorial substratum properties had profound effects on BMSC cell sheet integrity and multipotency, which had significant implications for future biomaterials and scaffold designs in the field of BMSC-mediated tissue regeneration. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

High-throughput combinatorial chemical bath deposition: The case of doping Cu (In, Ga) Se film with antimony

NASA Astrophysics Data System (ADS)

Yan, Zongkai; Zhang, Xiaokun; Li, Guang; Cui, Yuxing; Jiang, Zhaolian; Liu, Wen; Peng, Zhi; Xiang, Yong

2018-01-01

The conventional methods for designing and preparing thin film based on wet process remain a challenge due to disadvantages such as time-consuming and ineffective, which hinders the development of novel materials. Herein, we present a high-throughput combinatorial technique for continuous thin film preparation relied on chemical bath deposition (CBD). The method is ideally used to prepare high-throughput combinatorial material library with low decomposition temperatures and high water- or oxygen-sensitivity at relatively high-temperature. To check this system, a Cu(In, Ga)Se (CIGS) thin films library doped with 0-19.04 at.% of antimony (Sb) was taken as an example to evaluate the regulation of varying Sb doping concentration on the grain growth, structure, morphology and electrical properties of CIGS thin film systemically. Combined with the Energy Dispersive Spectrometer (EDS), X-ray Photoelectron Spectroscopy (XPS), automated X-ray Diffraction (XRD) for rapid screening and Localized Electrochemical Impedance Spectroscopy (LEIS), it was confirmed that this combinatorial high-throughput system could be used to identify the composition with the optimal grain orientation growth, microstructure and electrical properties systematically, through accurately monitoring the doping content and material composition. According to the characterization results, a Sb2Se3 quasi-liquid phase promoted CIGS film-growth model has been put forward. In addition to CIGS thin film reported here, the combinatorial CBD also could be applied to the high-throughput screening of other sulfide thin film material systems.

A label-free, fluorescence based assay for microarray

NASA Astrophysics Data System (ADS)

Niu, Sanjun

DNA chip technology has drawn tremendous attention since it emerged in the mid 90's as a method that expedites gene sequencing by over 100-fold. DNA chip, also called DNA microarray, is a combinatorial technology in which different single-stranded DNA (ssDNA) molecules of known sequences are immobilized at specific spots. The immobilized ssDNA strands are called probes. In application, the chip is exposed to a solution containing ssDNA of unknown sequence, called targets, which are labeled with fluorescent dyes. Due to specific molecular recognition among the base pairs in the DNA, the binding or hybridization occurs only when the probe and target sequences are complementary. The nucleotide sequence of the target is determined by imaging the fluorescence from the spots. The uncertainty of background in signal detection and statistical error in data analysis, primarily due to the error in the DNA amplification process and statistical distribution of the tags in the target DNA, have become the fundamental barriers in bringing the technology into application for clinical diagnostics. Furthermore, the dye and tagging process are expensive, making the cost of DNA chips inhibitive for clinical testing. These limitations and challenges make it difficult to implement DNA chip methods as a diagnostic tool in a pathology laboratory. The objective of this dissertation research is to provide an alternative approach that will address the above challenges. In this research, a label-free assay is designed and studied. Polystyrene (PS), a commonly used polymeric material, serves as the fluorescence agent. Probe ssDNA is covalently immobilized on polystyrene thin film that is supported by a reflecting substrate. When this chip is exposed to excitation light, fluorescence light intensity from PS is detected as the signal. Since the optical constants and conformations of ssDNA and dsDNA (double stranded DNA) are different, the measured fluorescence from PS changes for the same intensity of excitation light. The fluorescence contrast is used to quantify the amount of probe-target hybridization. A mathematical model that considers multiple reflections and scattering is developed to explain the mechanism of the fluorescence contrast which depends on the thickness of the PS film. Scattering is the dominant factor that contributes to the contrast. The potential of this assay to detect single nucleotide polymorphism is also tested.

Combination Across Domains: An MEG Investigation into the Relationship between Mathematical, Pictorial, and Linguistic Processing

PubMed Central

Bemis, Douglas K.; Pylkkänen, Liina

2013-01-01

Debates surrounding the evolution of language often hinge upon its relationship to cognition more generally and many investigations have attempted to demark the boundary between the two. Though results from these studies suggest that language may recruit domain-general mechanisms during certain types of complex processing, the domain-generality of basic combinatorial mechanisms that lie at the core of linguistic processing is still unknown. Our previous work (Bemis and Pylkkänen, 2011, 2012) used magnetoencephalography to isolate neural activity associated with the simple composition of an adjective and a noun (“red boat”) and found increased activity during this processing localized to the left anterior temporal lobe (lATL), ventro-medial prefrontal cortex (vmPFC), and left angular gyrus (lAG). The present study explores the domain-generality of these effects and their associated combinatorial mechanisms through two parallel non-linguistic combinatorial tasks designed to be as minimal and natural as the linguistic paradigm. In the first task, we used pictures of colored shapes to elicit combinatorial conceptual processing similar to that evoked by the linguistic expressions and find increased activity again localized to the vmPFC during combinatorial processing. This result suggests that a domain-general semantic combinatorial mechanism operates during basic linguistic composition, and that activity generated by its processing localizes to the vmPFC. In the second task, we recorded neural activity as subjects performed simple addition between two small numerals. Consistent with a wide array of recent results, we find no effects related to basic addition that coincide with our linguistic effects and instead find increased activity localized to the intraparietal sulcus. This result suggests that the scope of the previously identified linguistic effects is restricted to compositional operations and does not extend generally to all tasks that are merely similar in form. PMID:23293621

How communication changes when we cannot mime the world: Experimental evidence for the effect of iconicity on combinatoriality.

PubMed

Roberts, Gareth; Lewandowski, Jirka; Galantucci, Bruno

2015-08-01

Communication systems are exposed to two different pressures: a pressure for transmission efficiency, such that messages are simple to produce and perceive, and a pressure for referential efficiency, such that messages are easy to understand with their intended meaning. A solution to the first pressure is combinatoriality--the recombination of a few basic meaningless forms to express an infinite number of meanings. A solution to the second is iconicity--the use of forms that resemble what they refer to. These two solutions appear to be incompatible with each other, as iconic forms are ill-suited for use as meaningless combinatorial units. Furthermore, in the early stages of a communication system, when basic referential forms are in the process of being established, the pressure for referential efficiency is likely to be particularly strong, which may lead it to trump the pressure for transmission efficiency. This means that, where iconicity is available as a strategy, it is likely to impede the emergence of combinatoriality. Although this hypothesis seems consistent with some observations of natural language, it was unclear until recently how it could be soundly tested. This has changed thanks to the development of a line of research, known as Experimental Semiotics, in which participants construct novel communication systems in the laboratory using an unfamiliar medium. We conducted an Experimental Semiotic study in which we manipulated the opportunity for iconicity by varying the kind of referents to be communicated, while keeping the communication medium constant. We then measured the combinatoriality and transmission efficiency of the communication systems. We found that, where iconicity was available, it provided scaffolding for the construction of communication systems and was overwhelmingly adopted. Where it was not available, however, the resulting communication systems were more combinatorial and their forms more efficient to produce. This study enriches our understanding of the fundamental design principles of human communication and contributes tools to enrich it further. Copyright © 2015 Elsevier B.V. All rights reserved.

Applications of high throughput (combinatorial) methodologies to electronic, magnetic, optical, and energy-related materials

NASA Astrophysics Data System (ADS)

Green, Martin L.; Takeuchi, Ichiro; Hattrick-Simpers, Jason R.

2013-06-01

High throughput (combinatorial) materials science methodology is a relatively new research paradigm that offers the promise of rapid and efficient materials screening, optimization, and discovery. The paradigm started in the pharmaceutical industry but was rapidly adopted to accelerate materials research in a wide variety of areas. High throughput experiments are characterized by synthesis of a "library" sample that contains the materials variation of interest (typically composition), and rapid and localized measurement schemes that result in massive data sets. Because the data are collected at the same time on the same "library" sample, they can be highly uniform with respect to fixed processing parameters. This article critically reviews the literature pertaining to applications of combinatorial materials science for electronic, magnetic, optical, and energy-related materials. It is expected that high throughput methodologies will facilitate commercialization of novel materials for these critically important applications. Despite the overwhelming evidence presented in this paper that high throughput studies can effectively inform commercial practice, in our perception, it remains an underutilized research and development tool. Part of this perception may be due to the inaccessibility of proprietary industrial research and development practices, but clearly the initial cost and availability of high throughput laboratory equipment plays a role. Combinatorial materials science has traditionally been focused on materials discovery, screening, and optimization to combat the extremely high cost and long development times for new materials and their introduction into commerce. Going forward, combinatorial materials science will also be driven by other needs such as materials substitution and experimental verification of materials properties predicted by modeling and simulation, which have recently received much attention with the advent of the Materials Genome Initiative. Thus, the challenge for combinatorial methodology will be the effective coupling of synthesis, characterization and theory, and the ability to rapidly manage large amounts of data in a variety of formats.

Combinatorial Pooling Enables Selective Sequencing of the Barley Gene Space

PubMed Central

Lonardi, Stefano; Duma, Denisa; Alpert, Matthew; Cordero, Francesca; Beccuti, Marco; Bhat, Prasanna R.; Wu, Yonghui; Ciardo, Gianfranco; Alsaihati, Burair; Ma, Yaqin; Wanamaker, Steve; Resnik, Josh; Bozdag, Serdar; Luo, Ming-Cheng; Close, Timothy J.

2013-01-01

For the vast majority of species – including many economically or ecologically important organisms, progress in biological research is hampered due to the lack of a reference genome sequence. Despite recent advances in sequencing technologies, several factors still limit the availability of such a critical resource. At the same time, many research groups and international consortia have already produced BAC libraries and physical maps and now are in a position to proceed with the development of whole-genome sequences organized around a physical map anchored to a genetic map. We propose a BAC-by-BAC sequencing protocol that combines combinatorial pooling design and second-generation sequencing technology to efficiently approach denovo selective genome sequencing. We show that combinatorial pooling is a cost-effective and practical alternative to exhaustive DNA barcoding when preparing sequencing libraries for hundreds or thousands of DNA samples, such as in this case gene-bearing minimum-tiling-path BAC clones. The novelty of the protocol hinges on the computational ability to efficiently compare hundred millions of short reads and assign them to the correct BAC clones (deconvolution) so that the assembly can be carried out clone-by-clone. Experimental results on simulated data for the rice genome show that the deconvolution is very accurate, and the resulting BAC assemblies have high quality. Results on real data for a gene-rich subset of the barley genome confirm that the deconvolution is accurate and the BAC assemblies have good quality. While our method cannot provide the level of completeness that one would achieve with a comprehensive whole-genome sequencing project, we show that it is quite successful in reconstructing the gene sequences within BACs. In the case of plants such as barley, this level of sequence knowledge is sufficient to support critical end-point objectives such as map-based cloning and marker-assisted breeding. PMID:23592960

Combinatorial pooling enables selective sequencing of the barley gene space.

PubMed

Lonardi, Stefano; Duma, Denisa; Alpert, Matthew; Cordero, Francesca; Beccuti, Marco; Bhat, Prasanna R; Wu, Yonghui; Ciardo, Gianfranco; Alsaihati, Burair; Ma, Yaqin; Wanamaker, Steve; Resnik, Josh; Bozdag, Serdar; Luo, Ming-Cheng; Close, Timothy J

2013-04-01

For the vast majority of species - including many economically or ecologically important organisms, progress in biological research is hampered due to the lack of a reference genome sequence. Despite recent advances in sequencing technologies, several factors still limit the availability of such a critical resource. At the same time, many research groups and international consortia have already produced BAC libraries and physical maps and now are in a position to proceed with the development of whole-genome sequences organized around a physical map anchored to a genetic map. We propose a BAC-by-BAC sequencing protocol that combines combinatorial pooling design and second-generation sequencing technology to efficiently approach denovo selective genome sequencing. We show that combinatorial pooling is a cost-effective and practical alternative to exhaustive DNA barcoding when preparing sequencing libraries for hundreds or thousands of DNA samples, such as in this case gene-bearing minimum-tiling-path BAC clones. The novelty of the protocol hinges on the computational ability to efficiently compare hundred millions of short reads and assign them to the correct BAC clones (deconvolution) so that the assembly can be carried out clone-by-clone. Experimental results on simulated data for the rice genome show that the deconvolution is very accurate, and the resulting BAC assemblies have high quality. Results on real data for a gene-rich subset of the barley genome confirm that the deconvolution is accurate and the BAC assemblies have good quality. While our method cannot provide the level of completeness that one would achieve with a comprehensive whole-genome sequencing project, we show that it is quite successful in reconstructing the gene sequences within BACs. In the case of plants such as barley, this level of sequence knowledge is sufficient to support critical end-point objectives such as map-based cloning and marker-assisted breeding.

A new pooling strategy for high-throughput screening: the Shifted Transversal Design

PubMed Central

Thierry-Mieg, Nicolas

2006-01-01

Background In binary high-throughput screening projects where the goal is the identification of low-frequency events, beyond the obvious issue of efficiency, false positives and false negatives are a major concern. Pooling constitutes a natural solution: it reduces the number of tests, while providing critical duplication of the individual experiments, thereby correcting for experimental noise. The main difficulty consists in designing the pools in a manner that is both efficient and robust: few pools should be necessary to correct the errors and identify the positives, yet the experiment should not be too vulnerable to biological shakiness. For example, some information should still be obtained even if there are slightly more positives or errors than expected. This is known as the group testing problem, or pooling problem. Results In this paper, we present a new non-adaptive combinatorial pooling design: the "shifted transversal design" (STD). It relies on arithmetics, and rests on two intuitive ideas: minimizing the co-occurrence of objects, and constructing pools of constant-sized intersections. We prove that it allows unambiguous decoding of noisy experimental observations. This design is highly flexible, and can be tailored to function robustly in a wide range of experimental settings (i.e., numbers of objects, fractions of positives, and expected error-rates). Furthermore, we show that our design compares favorably, in terms of efficiency, to the previously described non-adaptive combinatorial pooling designs. Conclusion This method is currently being validated by field-testing in the context of yeast-two-hybrid interactome mapping, in collaboration with Marc Vidal's lab at the Dana Farber Cancer Institute. Many similar projects could benefit from using the Shifted Transversal Design. PMID:16423300

Intercell scheduling: A negotiation approach using multi-agent coalitions

NASA Astrophysics Data System (ADS)

Tian, Yunna; Li, Dongni; Zheng, Dan; Jia, Yunde

2016-10-01

Intercell scheduling problems arise as a result of intercell transfers in cellular manufacturing systems. Flexible intercell routes are considered in this article, and a coalition-based scheduling (CBS) approach using distributed multi-agent negotiation is developed. Taking advantage of the extended vision of the coalition agents, the global optimization is improved and the communication cost is reduced. The objective of the addressed problem is to minimize mean tardiness. Computational results show that, compared with the widely used combinatorial rules, CBS provides better performance not only in minimizing the objective, i.e. mean tardiness, but also in minimizing auxiliary measures such as maximum completion time, mean flow time and the ratio of tardy parts. Moreover, CBS is better than the existing intercell scheduling approach for the same problem with respect to the solution quality and computational costs.

Integrating Monetary and Non-monetary Reenlistment Incentives Utilizing the Combinatorial Retention Auction Mechanism (CRAM)

DTIC Science & Technology

2008-12-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS INTEGRATING MONETARY AND NON-MONETARY REENLISTMENT INCENTIVES UTILIZING THE...Monetary and Non- monetary Reenlistment Incentives Utilizing the Combinatorial Retention Auction Mechanism (CRAM) 6. AUTHOR(S) Brooke Zimmerman 5...iii Approved for public release; distribution is unlimited INTEGRATING MONETARY AND NON-MONETARY REENLISTMENT INCENTIVES UTILIZING THE

Combinatorial Solid-Phase Synthesis of Aromatic Oligoamides: A Research-Based Laboratory Module for Undergraduate Organic Chemistry

ERIC Educational Resources Information Center

Fuller, Amelia A.

2016-01-01

A five-week, research-based experiment suitable for second-semester introductory organic laboratory students is described. Each student designs, prepares, and analyzes a combinatorial array of six aromatic oligoamides. Molecules are prepared on solid phase via a six-step synthetic sequence, and purities and identities are determined by analysis of…

Two-dimensional combinatorial screening enables the bottom-up design of a microRNA-10b inhibitor.

PubMed

Velagapudi, Sai Pradeep; Disney, Matthew D

2014-03-21

The RNA motifs that bind guanidinylated kanamycin A (G Kan A) and guanidinylated neomycin B (G Neo B) were identified via two-dimensional combinatorial screening (2DCS). The results of these studies enabled the "bottom-up" design of a small molecule inhibitor of oncogenic microRNA-10b.

The Classicist and the Frequentist Approach to Probability within a "TinkerPlots2" Combinatorial Problem

ERIC Educational Resources Information Center

Prodromou, Theodosia

2012-01-01

This article seeks to address a pedagogical theory of introducing the classicist and the frequentist approach to probability, by investigating important elements in 9th grade students' learning process while working with a "TinkerPlots2" combinatorial problem. Results from this research study indicate that, after the students had seen…

An Onto-Semiotic Analysis of Combinatorial Problems and the Solving Processes by University Students

ERIC Educational Resources Information Center

Godino, Juan D.; Batanero, Carmen; Roa, Rafael

2005-01-01

In this paper we describe an ontological and semiotic model for mathematical knowledge, using elementary combinatorics as an example. We then apply this model to analyze the solving process of some combinatorial problems by students with high mathematical training, and show its utility in providing a semiotic explanation for the difficulty of…

Combinatorial synthesis of ceramic materials

DOEpatents

Lauf, Robert J [Oak Ridge, TN; Walls, Claudia A [Oak Ridge, TN; Boatner, Lynn A [Oak Ridge, TN

2010-02-23

A combinatorial library includes a gelcast substrate defining a plurality of cavities in at least one surface thereof; and a plurality of gelcast test materials in the cavities, at least two of the test materials differing from the substrate in at least one compositional characteristic, the two test materials differing from each other in at least one compositional characteristic.

Combinatorial synthesis of ceramic materials

DOEpatents

Lauf, Robert J.; Walls, Claudia A.; Boatner, Lynn A.

2006-11-14

A combinatorial library includes a gelcast substrate defining a plurality of cavities in at least one surface thereof; and a plurality of gelcast test materials in the cavities, at least two of the test materials differing from the substrate in at least one compositional characteristic, the two test materials differing from each other in at least one compositional characteristic.

The Shape of Things to Come: The Computational Pictograph as a Bridge from Combinatorial Space to Outcome Distribution

ERIC Educational Resources Information Center

Abrahamson, Dor

2006-01-01

This snapshot introduces a computer-based representation and activity that enables students to simultaneously "see" the combinatorial space of a stochastic device (e.g., dice, spinner, coins) and its outcome distribution. The author argues that the "ambiguous" representation fosters student insight into probability. [Snapshots are subject to peer…

Phase Transitions in Combinatorial Optimization Problems: Basics, Algorithms and Statistical Mechanics

NASA Astrophysics Data System (ADS)

Hartmann, Alexander K.; Weigt, Martin

2005-10-01

A concise, comprehensive introduction to the topic of statistical physics of combinatorial optimization, bringing together theoretical concepts and algorithms from computer science with analytical methods from physics. The result bridges the gap between statistical physics and combinatorial optimization, investigating problems taken from theoretical computing, such as the vertex-cover problem, with the concepts and methods of theoretical physics. The authors cover rapid developments and analytical methods that are both extremely complex and spread by word-of-mouth, providing all the necessary basics in required detail. Throughout, the algorithms are shown with examples and calculations, while the proofs are given in a way suitable for graduate students, post-docs, and researchers. Ideal for newcomers to this young, multidisciplinary field.

Combinatorial complexity of pathway analysis in metabolic networks.

PubMed

Klamt, Steffen; Stelling, Jörg

2002-01-01

Elementary flux mode analysis is a promising approach for a pathway-oriented perspective of metabolic networks. However, in larger networks it is hampered by the combinatorial explosion of possible routes. In this work we give some estimations on the combinatorial complexity including theoretical upper bounds for the number of elementary flux modes in a network of a given size. In a case study, we computed the elementary modes in the central metabolism of Escherichia coli while utilizing four different substrates. Interestingly, although the number of modes occurring in this complex network can exceed half a million, it is still far below the upper bound. Hence, to a certain extent, pathway analysis of central catabolism is feasible to assess network properties such as flexibility and functionality.

Building synthetic gene circuits from combinatorial libraries: screening and selection strategies.

PubMed

Schaerli, Yolanda; Isalan, Mark

2013-07-01

The promise of wide-ranging biotechnology applications inspires synthetic biologists to design novel genetic circuits. However, building such circuits rationally is still not straightforward and often involves painstaking trial-and-error. Mimicking the process of natural selection can help us to bridge the gap between our incomplete understanding of nature's design rules and our desire to build functional networks. By adopting the powerful method of directed evolution, which is usually applied to protein engineering, functional networks can be obtained through screening or selecting from randomised combinatorial libraries. This review first highlights the practical options to introduce combinatorial diversity into gene circuits and then examines strategies for identifying the potentially rare library members with desired functions, either by screening or selection.

PCTFPeval: a web tool for benchmarking newly developed algorithms for predicting cooperative transcription factor pairs in yeast.

PubMed

Lai, Fu-Jou; Chang, Hong-Tsun; Wu, Wei-Sheng

2015-01-01

Computational identification of cooperative transcription factor (TF) pairs helps understand the combinatorial regulation of gene expression in eukaryotic cells. Many advanced algorithms have been proposed to predict cooperative TF pairs in yeast. However, it is still difficult to conduct a comprehensive and objective performance comparison of different algorithms because of lacking sufficient performance indices and adequate overall performance scores. To solve this problem, in our previous study (published in BMC Systems Biology 2014), we adopted/proposed eight performance indices and designed two overall performance scores to compare the performance of 14 existing algorithms for predicting cooperative TF pairs in yeast. Most importantly, our performance comparison framework can be applied to comprehensively and objectively evaluate the performance of a newly developed algorithm. However, to use our framework, researchers have to put a lot of effort to construct it first. To save researchers time and effort, here we develop a web tool to implement our performance comparison framework, featuring fast data processing, a comprehensive performance comparison and an easy-to-use web interface. The developed tool is called PCTFPeval (Predicted Cooperative TF Pair evaluator), written in PHP and Python programming languages. The friendly web interface allows users to input a list of predicted cooperative TF pairs from their algorithm and select (i) the compared algorithms among the 15 existing algorithms, (ii) the performance indices among the eight existing indices, and (iii) the overall performance scores from two possible choices. The comprehensive performance comparison results are then generated in tens of seconds and shown as both bar charts and tables. The original comparison results of each compared algorithm and each selected performance index can be downloaded as text files for further analyses. Allowing users to select eight existing performance indices and 15 existing algorithms for comparison, our web tool benefits researchers who are eager to comprehensively and objectively evaluate the performance of their newly developed algorithm. Thus, our tool greatly expedites the progress in the research of computational identification of cooperative TF pairs.

PCTFPeval: a web tool for benchmarking newly developed algorithms for predicting cooperative transcription factor pairs in yeast

PubMed Central

2015-01-01

Background Computational identification of cooperative transcription factor (TF) pairs helps understand the combinatorial regulation of gene expression in eukaryotic cells. Many advanced algorithms have been proposed to predict cooperative TF pairs in yeast. However, it is still difficult to conduct a comprehensive and objective performance comparison of different algorithms because of lacking sufficient performance indices and adequate overall performance scores. To solve this problem, in our previous study (published in BMC Systems Biology 2014), we adopted/proposed eight performance indices and designed two overall performance scores to compare the performance of 14 existing algorithms for predicting cooperative TF pairs in yeast. Most importantly, our performance comparison framework can be applied to comprehensively and objectively evaluate the performance of a newly developed algorithm. However, to use our framework, researchers have to put a lot of effort to construct it first. To save researchers time and effort, here we develop a web tool to implement our performance comparison framework, featuring fast data processing, a comprehensive performance comparison and an easy-to-use web interface. Results The developed tool is called PCTFPeval (Predicted Cooperative TF Pair evaluator), written in PHP and Python programming languages. The friendly web interface allows users to input a list of predicted cooperative TF pairs from their algorithm and select (i) the compared algorithms among the 15 existing algorithms, (ii) the performance indices among the eight existing indices, and (iii) the overall performance scores from two possible choices. The comprehensive performance comparison results are then generated in tens of seconds and shown as both bar charts and tables. The original comparison results of each compared algorithm and each selected performance index can be downloaded as text files for further analyses. Conclusions Allowing users to select eight existing performance indices and 15 existing algorithms for comparison, our web tool benefits researchers who are eager to comprehensively and objectively evaluate the performance of their newly developed algorithm. Thus, our tool greatly expedites the progress in the research of computational identification of cooperative TF pairs. PMID:26677932

Ligand design by a combinatorial approach based on modeling and experiment: application to HLA-DR4

NASA Astrophysics Data System (ADS)

Evensen, Erik; Joseph-McCarthy, Diane; Weiss, Gregory A.; Schreiber, Stuart L.; Karplus, Martin

2007-07-01

Combinatorial synthesis and large scale screening methods are being used increasingly in drug discovery, particularly for finding novel lead compounds. Although these "random" methods sample larger areas of chemical space than traditional synthetic approaches, only a relatively small percentage of all possible compounds are practically accessible. It is therefore helpful to select regions of chemical space that have greater likelihood of yielding useful leads. When three-dimensional structural data are available for the target molecule this can be achieved by applying structure-based computational design methods to focus the combinatorial library. This is advantageous over the standard usage of computational methods to design a small number of specific novel ligands, because here computation is employed as part of the combinatorial design process and so is required only to determine a propensity for binding of certain chemical moieties in regions of the target molecule. This paper describes the application of the Multiple Copy Simultaneous Search (MCSS) method, an active site mapping and de novo structure-based design tool, to design a focused combinatorial library for the class II MHC protein HLA-DR4. Methods for the synthesizing and screening the computationally designed library are presented; evidence is provided to show that binding was achieved. Although the structure of the protein-ligand complex could not be determined, experimental results including cross-exclusion of a known HLA-DR4 peptide ligand (HA) by a compound from the library. Computational model building suggest that at least one of the ligands designed and identified by the methods described binds in a mode similar to that of native peptides.

MiYA, an efficient machine-learning workflow in conjunction with the YeastFab assembly strategy for combinatorial optimization of heterologous metabolic pathways in Saccharomyces cerevisiae.

PubMed

Zhou, Yikang; Li, Gang; Dong, Junkai; Xing, Xin-Hui; Dai, Junbiao; Zhang, Chong

2018-05-01

Facing boosting ability to construct combinatorial metabolic pathways, how to search the metabolic sweet spot has become the rate-limiting step. We here reported an efficient Machine-learning workflow in conjunction with YeastFab Assembly strategy (MiYA) for combinatorial optimizing the large biosynthetic genotypic space of heterologous metabolic pathways in Saccharomyces cerevisiae. Using β-carotene biosynthetic pathway as example, we first demonstrated that MiYA has the power to search only a small fraction (2-5%) of combinatorial space to precisely tune the expression level of each gene with a machine-learning algorithm of an artificial neural network (ANN) ensemble to avoid over-fitting problem when dealing with a small number of training samples. We then applied MiYA to improve the biosynthesis of violacein. Feed with initial data from a colorimetric plate-based, pre-screened pool of 24 strains producing violacein, MiYA successfully predicted, and verified experimentally, the existence of a strain that showed a 2.42-fold titer improvement in violacein production among 3125 possible designs. Furthermore, MiYA was able to largely avoid the branch pathway of violacein biosynthesis that makes deoxyviolacein, and produces very pure violacein. Together, MiYA combines the advantages of standardized building blocks and machine learning to accelerate the Design-Build-Test-Learn (DBTL) cycle for combinatorial optimization of metabolic pathways, which could significantly accelerate the development of microbial cell factories. Copyright © 2018 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Classification of hyperbolic singularities of rank zero of integrable Hamiltonian systems

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

Oshemkov, Andrey A

2010-10-06

A complete invariant is constructed that is a solution of the problem of semilocal classification of saddle singularities of integrable Hamiltonian systems. Namely, a certain combinatorial object (an f{sub n}-graph) is associated with every nondegenerate saddle singularity of rank zero; as a result, the problem of semilocal classification of saddle singularities of rank zero is reduced to the problem of enumeration of the f{sub n}-graphs. This enables us to describe a simple algorithm for obtaining the lists of saddle singularities of rank zero for a given number of degrees of freedom and a given complexity. Bibliography: 24 titles.

The Combinatorial Trace Method in Action

ERIC Educational Resources Information Center

Krebs, Mike; Martinez, Natalie C.

2013-01-01

On any finite graph, the number of closed walks of length k is equal to the sum of the kth powers of the eigenvalues of any adjacency matrix. This simple observation is the basis for the combinatorial trace method, wherein we attempt to count (or bound) the number of closed walks of a given length so as to obtain information about the graph's…

Gas phase electrodeposition: a programmable multimaterial deposition method for combinatorial nanostructured device discovery.

PubMed

Lin, En-Chiang; Cole, Jesse J; Jacobs, Heiko O

2010-11-10

This article reports and applies a recently discovered programmable multimaterial deposition process to the formation and combinatorial improvement of 3D nanostructured devices. The gas-phase deposition process produces charged <5 nm particles of silver, tungsten, and platinum and uses externally biased electrodes to control the material flux and to turn deposition ON/OFF in selected domains. Domains host nanostructured dielectrics to define arrays of electrodynamic 10 × nanolenses to further control the flux to form <100 nm resolution deposits. The unique feature of the process is that material type, amount, and sequence can be altered from one domain to the next leading to different types of nanostructures including multimaterial bridges, interconnects, or nanowire arrays with 20 nm positional accuracy. These features enable combinatorial nanostructured materials and device discovery. As a first demonstration, we produce and identify in a combinatorial way 3D nanostructured electrode designs that improve light scattering, absorption, and minority carrier extraction of bulk heterojunction photovoltaic cells. Photovoltaic cells from domains with long and dense nanowire arrays improve the relative power conversion efficiency by 47% when compared to flat domains on the same substrate.

Solving Energy-Aware Real-Time Tasks Scheduling Problem with Shuffled Frog Leaping Algorithm on Heterogeneous Platforms

PubMed Central

Zhang, Weizhe; Bai, Enci; He, Hui; Cheng, Albert M.K.

2015-01-01

Reducing energy consumption is becoming very important in order to keep battery life and lower overall operational costs for heterogeneous real-time multiprocessor systems. In this paper, we first formulate this as a combinatorial optimization problem. Then, a successful meta-heuristic, called Shuffled Frog Leaping Algorithm (SFLA) is proposed to reduce the energy consumption. Precocity remission and local optimal avoidance techniques are proposed to avoid the precocity and improve the solution quality. Convergence acceleration significantly reduces the search time. Experimental results show that the SFLA-based energy-aware meta-heuristic uses 30% less energy than the Ant Colony Optimization (ACO) algorithm, and 60% less energy than the Genetic Algorithm (GA) algorithm. Remarkably, the running time of the SFLA-based meta-heuristic is 20 and 200 times less than ACO and GA, respectively, for finding the optimal solution. PMID:26110406

A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern Matching.

PubMed

Romero, José R; Carballido, Jessica A; Garbus, Ingrid; Echenique, Viviana C; Ponzoni, Ignacio

2016-01-01

The identification of nested motifs in genomic sequences is a complex computational problem. The detection of these patterns is important to allow the discovery of transposable element (TE) insertions, incomplete reverse transcripts, deletions, and/or mutations. In this study, a de novo strategy for detecting patterns that represent nested motifs was designed based on exhaustive searches for pairs of motifs and combinatorial pattern analysis. These patterns can be grouped into three categories, motifs within other motifs, motifs flanked by other motifs, and motifs of large size. The methodology used in this study, applied to genomic sequences from the plant species Aegilops tauschii and Oryza sativa , revealed that it is possible to identify putative nested TEs by detecting these three types of patterns. The results were validated through BLAST alignments, which revealed the efficacy and usefulness of the new method, which is called Mamushka.

Geometrical study of phyllotactic patterns by Bernoulli spiral lattices.

PubMed

Sushida, Takamichi; Yamagishi, Yoshikazu

2017-06-01

Geometrical studies of phyllotactic patterns deal with the centric or cylindrical models produced by ideal lattices. van Iterson (Mathematische und mikroskopisch - anatomische Studien über Blattstellungen nebst Betrachtungen über den Schalenbau der Miliolinen, Verlag von Gustav Fischer, Jena, 1907) suggested a centric model representing ideal phyllotactic patterns as disk packings of Bernoulli spiral lattices and presented a phase diagram now called Van Iterson's diagram explaining the bifurcation processes of their combinatorial structures. Geometrical properties on disk packings were shown by Rothen & Koch (J. Phys France, 50(13), 1603-1621, 1989). In contrast, as another centric model, we organized a mathematical framework of Voronoi tilings of Bernoulli spiral lattices and showed mathematically that the phase diagram of a Voronoi tiling is graph-theoretically dual to Van Iterson's diagram. This paper gives a review of two centric models for disk packings and Voronoi tilings of Bernoulli spiral lattices. © 2017 Japanese Society of Developmental Biologists.

Improved mine blast algorithm for optimal cost design of water distribution systems

NASA Astrophysics Data System (ADS)

Sadollah, Ali; Guen Yoo, Do; Kim, Joong Hoon

2015-12-01

The design of water distribution systems is a large class of combinatorial, nonlinear optimization problems with complex constraints such as conservation of mass and energy equations. Since feasible solutions are often extremely complex, traditional optimization techniques are insufficient. Recently, metaheuristic algorithms have been applied to this class of problems because they are highly efficient. In this article, a recently developed optimizer called the mine blast algorithm (MBA) is considered. The MBA is improved and coupled with the hydraulic simulator EPANET to find the optimal cost design for water distribution systems. The performance of the improved mine blast algorithm (IMBA) is demonstrated using the well-known Hanoi, New York tunnels and Balerma benchmark networks. Optimization results obtained using IMBA are compared to those using MBA and other optimizers in terms of their minimum construction costs and convergence rates. For the complex Balerma network, IMBA offers the cheapest network design compared to other optimization algorithms.

Bifurcation-based adiabatic quantum computation with a nonlinear oscillator network.

PubMed

Goto, Hayato

2016-02-22

The dynamics of nonlinear systems qualitatively change depending on their parameters, which is called bifurcation. A quantum-mechanical nonlinear oscillator can yield a quantum superposition of two oscillation states, known as a Schrödinger cat state, via quantum adiabatic evolution through its bifurcation point. Here we propose a quantum computer comprising such quantum nonlinear oscillators, instead of quantum bits, to solve hard combinatorial optimization problems. The nonlinear oscillator network finds optimal solutions via quantum adiabatic evolution, where nonlinear terms are increased slowly, in contrast to conventional adiabatic quantum computation or quantum annealing, where quantum fluctuation terms are decreased slowly. As a result of numerical simulations, it is concluded that quantum superposition and quantum fluctuation work effectively to find optimal solutions. It is also notable that the present computer is analogous to neural computers, which are also networks of nonlinear components. Thus, the present scheme will open new possibilities for quantum computation, nonlinear science, and artificial intelligence.

Bifurcation-based adiabatic quantum computation with a nonlinear oscillator network

NASA Astrophysics Data System (ADS)

Goto, Hayato

2016-02-01

The dynamics of nonlinear systems qualitatively change depending on their parameters, which is called bifurcation. A quantum-mechanical nonlinear oscillator can yield a quantum superposition of two oscillation states, known as a Schrödinger cat state, via quantum adiabatic evolution through its bifurcation point. Here we propose a quantum computer comprising such quantum nonlinear oscillators, instead of quantum bits, to solve hard combinatorial optimization problems. The nonlinear oscillator network finds optimal solutions via quantum adiabatic evolution, where nonlinear terms are increased slowly, in contrast to conventional adiabatic quantum computation or quantum annealing, where quantum fluctuation terms are decreased slowly. As a result of numerical simulations, it is concluded that quantum superposition and quantum fluctuation work effectively to find optimal solutions. It is also notable that the present computer is analogous to neural computers, which are also networks of nonlinear components. Thus, the present scheme will open new possibilities for quantum computation, nonlinear science, and artificial intelligence.

Replicator equations, maximal cliques, and graph isomorphism.

PubMed

Pelillo, M

1999-11-15

We present a new energy-minimization framework for the graph isomorphism problem that is based on an equivalent maximum clique formulation. The approach is centered around a fundamental result proved by Motzkin and Straus in the mid-1960s, and recently expanded in various ways, which allows us to formulate the maximum clique problem in terms of a standard quadratic program. The attractive feature of this formulation is that a clear one-to-one correspondence exists between the solutions of the quadratic program and those in the original, combinatorial problem. To solve the program we use the so-called replicator equations--a class of straightforward continuous- and discrete-time dynamical systems developed in various branches of theoretical biology. We show how, despite their inherent inability to escape from local solutions, they nevertheless provide experimental results that are competitive with those obtained using more elaborate mean-field annealing heuristics.

Archetypal dynamics, emergent situations, and the reality game.

PubMed

Sulis, William

2010-07-01

The classical approach to the modeling of reality is founded upon its objectification. Although successful dealing with inanimate matter, objectification has proven to be much less successful elsewhere, sometimes to the point of paradox. This paper discusses an approach to the modeling of reality based upon the concept of process as formulated within the framework of archetypal dynamics. Reality is conceptualized as an intermingling of information-transducing systems, together with the semantic frames that effectively describe and ascribe meaning to each system, along with particular formal representations of same which constitute the archetypes. Archetypal dynamics is the study of the relationships between systems, frames and their representations and the flow of information among these different entities. In this paper a specific formal representation of archetypal dynamics using tapestries is given, and a dynamics is founded upon this representation in the form of a combinatorial game called a reality game. Some simple examples are presented.

A high-level language for rule-based modelling.

PubMed

Pedersen, Michael; Phillips, Andrew; Plotkin, Gordon D

2015-01-01

Rule-based languages such as Kappa excel in their support for handling the combinatorial complexities prevalent in many biological systems, including signalling pathways. But Kappa provides little structure for organising rules, and large models can therefore be hard to read and maintain. This paper introduces a high-level, modular extension of Kappa called LBS-κ. We demonstrate the constructs of the language through examples and three case studies: a chemotaxis switch ring, a MAPK cascade, and an insulin signalling pathway. We then provide a formal definition of LBS-κ through an abstract syntax and a translation to plain Kappa. The translation is implemented in a compiler tool which is available as a web application. We finally demonstrate how to increase the expressivity of LBS-κ through embedded scripts in a general-purpose programming language, a technique which we view as generally applicable to other domain specific languages.

Analysis of genome rearrangement by block-interchanges.

PubMed

Lu, Chin Lung; Lin, Ying Chih; Huang, Yen Lin; Tang, Chuan Yi

2007-01-01

Block-interchanges are a new kind of genome rearrangements that affect the gene order in a chromosome by swapping two nonintersecting blocks of genes of any length. More recently, the study of such rearrangements is becoming increasingly important because of its applications in molecular evolution. Usually, this kind of study requires to solve a combinatorial problem, called the block-interchange distance problem, which is to find a minimum number of block-interchanges between two given gene orders of linear/circular chromosomes to transform one gene order into another. In this chapter, we shall introduce the basics of block-interchange rearrangements and permutation groups in algebra that are useful in analyses of genome rearrangements. In addition, we shall present a simple algorithm on the basis of permutation groups to efficiently solve the block-interchange distance problem, as well as ROBIN, a web server for the online analyses of block-interchange rearrangements.

A High-Level Language for Rule-Based Modelling

PubMed Central

Pedersen, Michael; Phillips, Andrew; Plotkin, Gordon D.

2015-01-01

Rule-based languages such as Kappa excel in their support for handling the combinatorial complexities prevalent in many biological systems, including signalling pathways. But Kappa provides little structure for organising rules, and large models can therefore be hard to read and maintain. This paper introduces a high-level, modular extension of Kappa called LBS-κ. We demonstrate the constructs of the language through examples and three case studies: a chemotaxis switch ring, a MAPK cascade, and an insulin signalling pathway. We then provide a formal definition of LBS-κ through an abstract syntax and a translation to plain Kappa. The translation is implemented in a compiler tool which is available as a web application. We finally demonstrate how to increase the expressivity of LBS-κ through embedded scripts in a general-purpose programming language, a technique which we view as generally applicable to other domain specific languages. PMID:26043208

Sorting permutations by prefix and suffix rearrangements.

PubMed

Lintzmayer, Carla Negri; Fertin, Guillaume; Dias, Zanoni

2017-02-01

Some interesting combinatorial problems have been motivated by genome rearrangements, which are mutations that affect large portions of a genome. When we represent genomes as permutations, the goal is to transform a given permutation into the identity permutation with the minimum number of rearrangements. When they affect segments from the beginning (respectively end) of the permutation, they are called prefix (respectively suffix) rearrangements. This paper presents results for rearrangement problems that involve prefix and suffix versions of reversals and transpositions considering unsigned and signed permutations. We give 2-approximation and ([Formula: see text])-approximation algorithms for these problems, where [Formula: see text] is a constant divided by the number of breakpoints (pairs of consecutive elements that should not be consecutive in the identity permutation) in the input permutation. We also give bounds for the diameters concerning these problems and provide ways of improving the practical results of our algorithms.

Innovations in gene and growth factor delivery systems for diabetic wound healing

PubMed Central

Laiva, Ashang Luwang; O'Brien, Fergal J.

2017-01-01

Abstract The rise in lower extremity amputations due to nonhealing of foot ulcers in diabetic patients calls for rapid improvement in effective treatment regimens. Administration of growth factors (GFs) are thought to offer an off‐the‐shelf treatment; however, the dose‐ and time‐dependent efficacy of the GFs together with the hostile environment of diabetic wound beds impose a major hindrance in the selection of an ideal route for GF delivery. As an alternative, the delivery of therapeutic genes using viral and nonviral vectors, capable of transiently expressing the genes until the recovery of the wounded tissue offers promise. The development of implantable biomaterial dressings capable of modulating the release of either single or combinatorial GFs/genes may offer solutions to this overgrowing problem. This article reviews the state of the art on gene and protein delivery and the strategic optimization of clinically adopted delivery strategies for the healing of diabetic wounds. PMID:28482114

REVIEWS OF TOPICAL PROBLEMS: 21st century: what is life from the perspective of physics?

NASA Astrophysics Data System (ADS)

Ivanitskii, Genrikh R.

2010-07-01

The evolution of the biophysical paradigm over 65 years since the publication in 1944 of Erwin Schrödinger's What is Life? The Physical Aspects of the Living Cell is reviewed. Based on the advances in molecular genetics, it is argued that all the features characteristic of living systems can also be found in nonliving ones. Ten paradoxes in logic and physics are analyzed that allow defining life in terms of a spatial-temporal hierarchy of structures and combinatory probabilistic logic. From the perspective of physics, life can be defined as resulting from a game involving interactions of matter one part of which acquires the ability to remember the success (or failure) probabilities from the previous rounds of the game, thereby increasing its chances for further survival in the next round. This part of matter is currently called living matter.

Fundamental Entangling Operators in Quantum Mechanics and Their Properties

NASA Astrophysics Data System (ADS)

Dao-Ming, Lu

2016-07-01

For the first time, we introduce so-called fundamental entangling operators e^{iQ1 P2} and e^{iP1 Q2 } for composing bipartite entangled states of continuum variables, where Q i and P i ( i = 1, 2) are coordinate and momentum operator, respectively. We then analyze how these entangling operators naturally appear in the quantum image of classical quadratic coordinate transformation ( q 1, q 2) → ( A q 1 + B q 2, C q 1 + D q 2), where A D- B C = 1, which means even the basic coordinate transformation ( Q 1, Q 2) → ( A Q 1 + B Q 2, C Q 1 + D Q 2) involves entangling mechanism. We also analyse their Lie algebraic properties and use the integration technique within an ordered product of operators to show they are also one- and two- mode combinatorial squeezing operators.

Enhancing PC Cluster-Based Parallel Branch-and-Bound Algorithms for the Graph Coloring Problem

NASA Astrophysics Data System (ADS)

Taoka, Satoshi; Takafuji, Daisuke; Watanabe, Toshimasa

A branch-and-bound algorithm (BB for short) is the most general technique to deal with various combinatorial optimization problems. Even if it is used, computation time is likely to increase exponentially. So we consider its parallelization to reduce it. It has been reported that the computation time of a parallel BB heavily depends upon node-variable selection strategies. And, in case of a parallel BB, it is also necessary to prevent increase in communication time. So, it is important to pay attention to how many and what kind of nodes are to be transferred (called sending-node selection strategy). In this paper, for the graph coloring problem, we propose some sending-node selection strategies for a parallel BB algorithm by adopting MPI for parallelization and experimentally evaluate how these strategies affect computation time of a parallel BB on a PC cluster network.

Supramolecular assembly/reassembly processes: molecular motors and dynamers operating at surfaces.

PubMed

Ciesielski, Artur; Samorì, Paolo

2011-04-01

Among the many significant advances within the field of supramolecular chemistry over the past decades, the development of the so-called "dynamers" features a direct relevance to materials science. Defined as "combinatorial dynamic polymers", dynamers are constitutional dynamic systems and materials resulting from the application of the principles of supramolecular chemistry to polymer science. Like supramolecular materials in general, dynamers are reversible dynamic multifunctional architectures, capable of modifying their constitution by exchanging, recombining, incorporating components. They may exhibit a variety of novel properties and behave as adaptive materials. In this review we focus on the design of responsive switchable monolayers, i.e. monolayers capable to undergo significant changes in their physical or chemical properties as a result of external stimuli. Scanning tunneling microscopy studies provide direct evidence with a sub-nanometre resolution, on the formation and dynamic response of these self-assembled systems featuring controlled geometries and properties.

Construction of a scFv Library with Synthetic, Non-combinatorial CDR Diversity.

PubMed

Bai, Xuelian; Shim, Hyunbo

2017-01-01

Many large synthetic antibody libraries have been designed, constructed, and successfully generated high-quality antibodies suitable for various demanding applications. While synthetic antibody libraries have many advantages such as optimized framework sequences and a broader sequence landscape than natural antibodies, their sequence diversities typically are generated by random combinatorial synthetic processes which cause the incorporation of many undesired CDR sequences. Here, we describe the construction of a synthetic scFv library using oligonucleotide mixtures that contain predefined, non-combinatorially synthesized CDR sequences. Each CDR is first inserted to a master scFv framework sequence and the resulting single-CDR libraries are subjected to a round of proofread panning. The proofread CDR sequences are assembled to produce the final scFv library with six diversified CDRs.

Natural products and combinatorial chemistry: back to the future.

PubMed

Ortholand, Jean-Yves; Ganesan, A

2004-06-01

The introduction of high-throughput synthesis and combinatorial chemistry has precipitated a global decline in the screening of natural products by the pharmaceutical industry. Some companies terminated their natural products program, despite the unproven success of the new technologies. This was a premature decision, as natural products have a long history of providing important medicinal agents. Furthermore, they occupy a complementary region of chemical space compared with the typical synthetic compound library. For these reasons, the interest in natural products has been rekindled. Various approaches have evolved that combine the power of natural products and organic chemistry, ranging from the combinatorial total synthesis of analogues to the exploration of natural product scaffolds and the design of completely unnatural molecules that resemble natural products in their molecular characteristics.

Two is better than one; toward a rational design of combinatorial therapy.

PubMed

Chen, Sheng-Hong; Lahav, Galit

2016-12-01

Drug combination is an appealing strategy for combating the heterogeneity of tumors and evolution of drug resistance. However, the rationale underlying combinatorial therapy is often not well established due to lack of understandings of the specific pathways responding to the drugs, and their temporal dynamics following each treatment. Here we present several emerging trends in harnessing properties of biological systems for the optimal design of drug combinations, including the type of drugs, specific concentration, sequence of addition and the temporal schedule of treatments. We highlight recent studies showing different approaches for efficient design of drug combinations including single-cell signaling dynamics, adaption and pathway crosstalk. Finally, we discuss novel and feasible approaches that can facilitate the optimal design of combinatorial therapy. Copyright © 2016 Elsevier Ltd. All rights reserved.

SO2 and NH3 gas adsorption on a ternary ZnO/CuO/CuCl2 impregnated activated carbon evaluated using combinatorial methods.

PubMed

Romero, Jennifer V; Smith, Jock W H; Sullivan, Braden M; Croll, Lisa M; Dahn, J R

2012-01-09

Ternary libraries of 64 ZnO/CuO/CuCl(2) impregnated activated carbon samples were prepared on untreated or HNO(3)-treated carbon and evaluated for their SO(2) and NH(3) gas adsorption properties gravimetrically using a combinatorial method. CuCl(2) is shown to be a viable substitute for HNO(3) and some compositions of ternary ZnO/CuO/CuCl(2) impregnated carbon samples prepared on untreated carbon provided comparable SO(2) and NH(3) gas removal capacities to the materials prepared on HNO(3)-treated carbon. Through combinatorial methods, it was determined that the use of HNO(3) in this multigas adsorbent formulation can be avoided.

High-throughput screening for combinatorial thin-film library of thermoelectric materials.

PubMed

Watanabe, Masaki; Kita, Takuji; Fukumura, Tomoteru; Ohtomo, Akira; Ueno, Kazunori; Kawasaki, Masashi

2008-01-01

A high-throughput method has been developed to evaluate the Seebeck coefficient and electrical resistivity of combinatorial thin-film libraries of thermoelectric materials from room temperature to 673 K. Thin-film samples several millimeters in size were deposited on an integrated Al2O3 substrate with embedded lead wires and local heaters for measurement of the thermopower under a controlled temperature gradient. An infrared camera was used for real-time observation of the temperature difference Delta T between two electrical contacts on the sample to obtain the Seebeck coefficient. The Seebeck coefficient and electrical resistivity of constantan thin films were shown to be almost identical to standard data for bulk constantan. High-throughput screening was demonstrated for a thermoelectric Mg-Si-Ge combinatorial library.

Library fingerprints: a novel approach to the screening of virtual libraries.

PubMed

Klon, Anthony E; Diller, David J

2007-01-01

We propose a novel method to prioritize libraries for combinatorial synthesis and high-throughput screening that assesses the viability of a particular library on the basis of the aggregate physical-chemical properties of the compounds using a naïve Bayesian classifier. This approach prioritizes collections of related compounds according to the aggregate values of their physical-chemical parameters in contrast to single-compound screening. The method is also shown to be useful in screening existing noncombinatorial libraries when the compounds in these libraries have been previously clustered according to their molecular graphs. We show that the method used here is comparable or superior to the single-compound virtual screening of combinatorial libraries and noncombinatorial libraries and is superior to the pairwise Tanimoto similarity searching of a collection of combinatorial libraries.

Discrete Optimization Model for Vehicle Routing Problem with Scheduling Side Cosntraints

NASA Astrophysics Data System (ADS)

Juliandri, Dedy; Mawengkang, Herman; Bu'ulolo, F.

2018-01-01

Vehicle Routing Problem (VRP) is an important element of many logistic systems which involve routing and scheduling of vehicles from a depot to a set of customers node. This is a hard combinatorial optimization problem with the objective to find an optimal set of routes used by a fleet of vehicles to serve the demands a set of customers It is required that these vehicles return to the depot after serving customers’ demand. The problem incorporates time windows, fleet and driver scheduling, pick-up and delivery in the planning horizon. The goal is to determine the scheduling of fleet and driver and routing policies of the vehicles. The objective is to minimize the overall costs of all routes over the planning horizon. We model the problem as a linear mixed integer program. We develop a combination of heuristics and exact method for solving the model.

A hybrid Q-learning sine-cosine-based strategy for addressing the combinatorial test suite minimization problem

PubMed Central

Zamli, Kamal Z.; Din, Fakhrud; Bures, Miroslav

2018-01-01

The sine-cosine algorithm (SCA) is a new population-based meta-heuristic algorithm. In addition to exploiting sine and cosine functions to perform local and global searches (hence the name sine-cosine), the SCA introduces several random and adaptive parameters to facilitate the search process. Although it shows promising results, the search process of the SCA is vulnerable to local minima/maxima due to the adoption of a fixed switch probability and the bounded magnitude of the sine and cosine functions (from -1 to 1). In this paper, we propose a new hybrid Q-learning sine-cosine- based strategy, called the Q-learning sine-cosine algorithm (QLSCA). Within the QLSCA, we eliminate the switching probability. Instead, we rely on the Q-learning algorithm (based on the penalty and reward mechanism) to dynamically identify the best operation during runtime. Additionally, we integrate two new operations (Lévy flight motion and crossover) into the QLSCA to facilitate jumping out of local minima/maxima and enhance the solution diversity. To assess its performance, we adopt the QLSCA for the combinatorial test suite minimization problem. Experimental results reveal that the QLSCA is statistically superior with regard to test suite size reduction compared to recent state-of-the-art strategies, including the original SCA, the particle swarm test generator (PSTG), adaptive particle swarm optimization (APSO) and the cuckoo search strategy (CS) at the 95% confidence level. However, concerning the comparison with discrete particle swarm optimization (DPSO), there is no significant difference in performance at the 95% confidence level. On a positive note, the QLSCA statistically outperforms the DPSO in certain configurations at the 90% confidence level. PMID:29771918

Generation of Diverse Biological Forms through Combinatorial Interactions between Tissue Polarity and Growth

PubMed Central

Kennaway, Richard; Coen, Enrico; Green, Amelia; Bangham, Andrew

2011-01-01

A major problem in biology is to understand how complex tissue shapes may arise through growth. In many cases this process involves preferential growth along particular orientations raising the question of how these orientations are specified. One view is that orientations are specified through stresses in the tissue (axiality-based system). Another possibility is that orientations can be specified independently of stresses through molecular signalling (polarity-based system). The axiality-based system has recently been explored through computational modelling. Here we develop and apply a polarity-based system which we call the Growing Polarised Tissue (GPT) framework. Tissue is treated as a continuous material within which regionally expressed factors under genetic control may interact and propagate. Polarity is established by signals that propagate through the tissue and is anchored in regions termed tissue polarity organisers that are also under genetic control. Rates of growth parallel or perpendicular to the local polarity may then be specified through a regulatory network. The resulting growth depends on how specified growth patterns interact within the constraints of mechanically connected tissue. This constraint leads to the emergence of features such as curvature that were not directly specified by the regulatory networks. Resultant growth feeds back to influence spatial arrangements and local orientations of tissue, allowing complex shapes to emerge from simple rules. Moreover, asymmetries may emerge through interactions between polarity fields. We illustrate the value of the GPT-framework for understanding morphogenesis by applying it to a growing Snapdragon flower and indicate how the underlying hypotheses may be tested by computational simulation. We propose that combinatorial intractions between orientations and rates of growth, which are a key feature of polarity-based systems, have been exploited during evolution to generate a range of observed biological shapes. PMID:21698124

A hybrid Q-learning sine-cosine-based strategy for addressing the combinatorial test suite minimization problem.

PubMed

Zamli, Kamal Z; Din, Fakhrud; Ahmed, Bestoun S; Bures, Miroslav

2018-01-01

The sine-cosine algorithm (SCA) is a new population-based meta-heuristic algorithm. In addition to exploiting sine and cosine functions to perform local and global searches (hence the name sine-cosine), the SCA introduces several random and adaptive parameters to facilitate the search process. Although it shows promising results, the search process of the SCA is vulnerable to local minima/maxima due to the adoption of a fixed switch probability and the bounded magnitude of the sine and cosine functions (from -1 to 1). In this paper, we propose a new hybrid Q-learning sine-cosine- based strategy, called the Q-learning sine-cosine algorithm (QLSCA). Within the QLSCA, we eliminate the switching probability. Instead, we rely on the Q-learning algorithm (based on the penalty and reward mechanism) to dynamically identify the best operation during runtime. Additionally, we integrate two new operations (Lévy flight motion and crossover) into the QLSCA to facilitate jumping out of local minima/maxima and enhance the solution diversity. To assess its performance, we adopt the QLSCA for the combinatorial test suite minimization problem. Experimental results reveal that the QLSCA is statistically superior with regard to test suite size reduction compared to recent state-of-the-art strategies, including the original SCA, the particle swarm test generator (PSTG), adaptive particle swarm optimization (APSO) and the cuckoo search strategy (CS) at the 95% confidence level. However, concerning the comparison with discrete particle swarm optimization (DPSO), there is no significant difference in performance at the 95% confidence level. On a positive note, the QLSCA statistically outperforms the DPSO in certain configurations at the 90% confidence level.

Growth of Ca{sub 2}MnO{sub 4} Ruddlesden-Popper structured thin films using combinatorial substrate epitaxy

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

Lacotte, M.; David, A.; Pravarthana, D.

2014-12-28

The local epitaxial growth of pulsed laser deposited Ca{sub 2}MnO{sub 4} films on polycrystalline spark plasma sintered Sr{sub 2}TiO{sub 4} substrates was investigated to determine phase formation and preferred epitaxial orientation relationships (ORs) for isostructural Ruddlesden-Popper (RP) heteroepitaxy, further developing the high-throughput synthetic approach called Combinatorial Substrate Epitaxy (CSE). Both grazing incidence X-ray diffraction and electron backscatter diffraction patterns of the film and substrate were indexable as single-phase RP-structured compounds. The optimal growth temperature (between 650 °C and 800 °C) was found to be 750 °C using the maximum value of the average image quality of the backscattered diffraction patterns. Films grew inmore » a grain-over-grain pattern such that each Ca{sub 2}MnO{sub 4} grain had a single OR with the Sr{sub 2}TiO{sub 4} grain on which it grew. Three primary ORs described 47 out of 49 grain pairs that covered nearly all of RP orientation space. The first OR, found for 20 of the 49, was the expected RP unit-cell over RP unit-cell OR, expressed as [100][001]{sub film}||[100][001]{sub sub}. The other two ORs were essentially rotated from the first by 90°, with one (observed for 17 of 49 pairs) being rotated about the [100] and the other (observed for 10 of 49 pairs) being rotated about the [110] (and not exactly by 90°). These results indicate that only a small number of ORs are needed to describe isostructural RP heteroepitaxy and further demonstrate the potential of CSE in the design and growth of a wide range of complex functional oxides.« less

Discovering time-lagged rules from microarray data using gene profile classifiers

PubMed Central

2011-01-01

Background Gene regulatory networks have an essential role in every process of life. In this regard, the amount of genome-wide time series data is becoming increasingly available, providing the opportunity to discover the time-delayed gene regulatory networks that govern the majority of these molecular processes. Results This paper aims at reconstructing gene regulatory networks from multiple genome-wide microarray time series datasets. In this sense, a new model-free algorithm called GRNCOP2 (Gene Regulatory Network inference by Combinatorial OPtimization 2), which is a significant evolution of the GRNCOP algorithm, was developed using combinatorial optimization of gene profile classifiers. The method is capable of inferring potential time-delay relationships with any span of time between genes from various time series datasets given as input. The proposed algorithm was applied to time series data composed of twenty yeast genes that are highly relevant for the cell-cycle study, and the results were compared against several related approaches. The outcomes have shown that GRNCOP2 outperforms the contrasted methods in terms of the proposed metrics, and that the results are consistent with previous biological knowledge. Additionally, a genome-wide study on multiple publicly available time series data was performed. In this case, the experimentation has exhibited the soundness and scalability of the new method which inferred highly-related statistically-significant gene associations. Conclusions A novel method for inferring time-delayed gene regulatory networks from genome-wide time series datasets is proposed in this paper. The method was carefully validated with several publicly available data sets. The results have demonstrated that the algorithm constitutes a usable model-free approach capable of predicting meaningful relationships between genes, revealing the time-trends of gene regulation. PMID:21524308

Variability of Valuation of Non-Monetary Incentives: Motivating and Implementing the Combinatorial Retention Auction Mechanism

DTIC Science & Technology

2009-03-01

homeport, geographic stability for two tours and compressed work week; homeport, lump sum SRB, and telecommuting ). The Monte Carlo simulation...Geographic stability 2 tours, and compressed work week). The Add 2 combination includes home port choice, lump sum SRB, and telecommuting ...VALUATION OF NON-MONETARY INCENTIVES: MOTIVATING AND IMPLEMENTING THE COMBINATORIAL RETENTION AUCTION MECHANISM by Jason Blake Ellis March 2009

Combinatorial Targeting of Prostate Carcinoma Cells and Tumor Associated Pericytes with Antibody-Based Immunotherapy and Metronomic Chemotherapy

DTIC Science & Technology

2011-03-01

Carcinoma Cells and Tumor Associated Pericytes with Antibody-Based Immunotherapy and Metronomic Chemotherapy. PRINCIPAL INVESTIGATOR: Soldano...Combinatorial Targeting of Prostate Carcinoma Cells and Tumor Associated Pericytes with Antibody-Based Immunotherapy and Metronomic Chemotherapy. 5b. GRANT...SUPPLEMENTARY NOTES 14. ABSTRACT Seventy seven 10 week old TRAMP mice were enrolled in the study. Administration of metronomic chemotherapy with

Computer Description of Black Hawk Helicopter

DTIC Science & Technology

1979-06-01

Model Combinatorial Geometry Models Black Hawk Helicopter Helicopter GIFT Computer Code Geometric Description of Targets 20. ABSTRACT...description was made using the technique of combinatorial geometry (COM-GEOM) and will be used as input to the GIFT computer code which generates Tliic...rnHp The data used bv the COVART comtmter code was eenerated bv the Geometric Information for Targets ( GIFT )Z computer code. This report documents

Designed Electroresponsive Biomaterials: Sequence-Controlled Behavior

DTIC Science & Technology

2010-06-29

protein of the M13 . Traditional phage and yeast display methodologies indicate that peptide sequences with high affinities for electrode materials...drug delivery. The original vision for this work was to employ combinatorial tools such as phage and yeast display under electrical selection pressure...and drug delivery. The original vision for this work was to employ combinatorial tools such as phage and yeast display under electrical selection

Nonlinear Multidimensional Assignment Problems Efficient Conic Optimization Methods and Applications

DTIC Science & Technology

2015-06-24

WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Arizona State University School of Mathematical & Statistical Sciences 901 S...SUPPLEMENTARY NOTES 14. ABSTRACT The major goals of this project were completed: the exact solution of previously unsolved challenging combinatorial optimization... combinatorial optimization problem, the Directional Sensor Problem, was solved in two ways. First, heuristically in an engineering fashion and second, exactly

Antenna Allocation in MIMO Radar with Widely Separated Antennas for Multi-Target Detection

PubMed Central

Gao, Hao; Wang, Jian; Jiang, Chunxiao; Zhang, Xudong

2014-01-01

In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes. PMID:25350505

Antenna allocation in MIMO radar with widely separated antennas for multi-target detection.

PubMed

Gao, Hao; Wang, Jian; Jiang, Chunxiao; Zhang, Xudong

2014-10-27

In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes.

Assembler: Efficient Discovery of Spatial Co-evolving Patterns in Massive Geo-sensory Data.

PubMed

Zhang, Chao; Zheng, Yu; Ma, Xiuli; Han, Jiawei

2015-08-01

Recent years have witnessed the wide proliferation of geo-sensory applications wherein a bundle of sensors are deployed at different locations to cooperatively monitor the target condition. Given massive geo-sensory data, we study the problem of mining spatial co-evolving patterns (SCPs), i.e ., groups of sensors that are spatially correlated and co-evolve frequently in their readings. SCP mining is of great importance to various real-world applications, yet it is challenging because (1) the truly interesting evolutions are often flooded by numerous trivial fluctuations in the geo-sensory time series; and (2) the pattern search space is extremely large due to the spatiotemporal combinatorial nature of SCP. In this paper, we propose a two-stage method called Assembler. In the first stage, Assembler filters trivial fluctuations using wavelet transform and detects frequent evolutions for individual sensors via a segment-and-group approach. In the second stage, Assembler generates SCPs by assembling the frequent evolutions of individual sensors. Leveraging the spatial constraint, it conceptually organizes all the SCPs into a novel structure called the SCP search tree, which facilitates the effective pruning of the search space to generate SCPs efficiently. Our experiments on both real and synthetic data sets show that Assembler is effective, efficient, and scalable.

A simple protocol for combinatorial cyclic depsipeptide libraries sequencing by matrix-assisted laser desorption/ionisation mass spectrometry.

PubMed

Gurevich-Messina, Juan M; Giudicessi, Silvana L; Martínez-Ceron, María C; Acosta, Gerardo; Erra-Balsells, Rosa; Cascone, Osvaldo; Albericio, Fernando; Camperi, Silvia A

2015-01-01

Short cyclic peptides have a great interest in therapeutic, diagnostic and affinity chromatography applications. The screening of 'one-bead-one-peptide' combinatorial libraries combined with mass spectrometry (MS) is an excellent tool to find peptides with affinity for any target protein. The fragmentation patterns of cyclic peptides are quite more complex than those of their linear counterparts, and the elucidation of the resulting tandem mass spectra is rather more difficult. Here, we propose a simple protocol for combinatorial cyclic libraries synthesis and ring opening before MS analysis. In this strategy, 4-hydroxymethylbenzoic acid, which forms a benzyl ester with the first amino acid, was used as the linker. A glycolamidic ester group was incorporated after the combinatorial positions by adding glycolic acid. The library synthesis protocol consisted in the following: (i) incorporation of Fmoc-Asp[2-phenylisopropyl (OPp)]-OH to Ala-Gly-oxymethylbenzamide-ChemMatrix, (ii) synthesis of the combinatorial library, (iii) assembly of a glycolic acid, (iv) couple of an Ala residue in the N-terminal, (v) removal of OPp, (vi) peptide cyclisation through side chain Asp and N-Ala amino terminus and (vii) removal of side chain protecting groups. In order to simultaneously open the ring and release each peptide, benzyl and glycolamidic esters were cleaved with ammonia. Peptide sequences could be deduced from the tandem mass spectra of each single bead evaluated. The strategy herein proposed is suitable for the preparation of one-bead-one-cyclic depsipeptide libraries that can be easily open for its sequencing by matrix-assisted laser desorption/ionisation MS. It employs techniques and reagents frequently used in a broad range of laboratories without special expertise in organic synthesis. Copyright © 2014 European Peptide Society and John Wiley & Sons, Ltd.

"One-sample concept" micro-combinatory for high throughput TEM of binary films.

PubMed

Sáfrán, György

2018-04-01

Phases of thin films may remarkably differ from that of bulk. Unlike to the comprehensive data files of Binary Phase Diagrams [1] available for bulk, complete phase maps for thin binary layers do not exist. This is due to both the diverse metastable, non-equilibrium or instable phases feasible in thin films and the required volume of characterization work with analytical techniques like TEM, SAED and EDS. The aim of the present work was to develop a method that remarkably facilitates the TEM study of the diverse binary phases of thin films, or the creation of phase maps. A micro-combinatorial method was worked out that enables both preparation and study of a gradient two-component film within a single TEM specimen. For a demonstration of the technique thin Mn x Al 1- x binary samples with evolving concentration from x = 0 to x = 1 have been prepared so that the transition from pure Mn to pure Al covers a 1.5 mm long track within the 3 mm diameter TEM grid. The proposed method enables the preparation and study of thin combinatorial samples including all feasible phases as a function of composition or other deposition parameters. Contrary to known "combinatorial chemistry", in which a series of different samples are deposited in one run, and investigated, one at a time, the present micro-combinatorial method produces a single specimen condensing a complete library of a binary system that can be studied, efficiently, within a single TEM session. That provides extremely high throughput for TEM characterization of composition-dependent phases, exploration of new materials, or the construction of phase diagrams of binary films. Copyright © 2018 Elsevier B.V. All rights reserved.

Combinatorial anticancer effects of curcumin and 5-fluorouracil loaded thiolated chitosan nanoparticles towards colon cancer treatment.

PubMed

Anitha, A; Deepa, N; Chennazhi, K P; Lakshmanan, Vinoth-Kumar; Jayakumar, R

2014-09-01

Evaluation of the combinatorial anticancer effects of curcumin/5-fluorouracil loaded thiolated chitosan nanoparticles (CRC-TCS-NPs/5-FU-TCS-NPs) on colon cancer cells and the analysis of pharmacokinetics and biodistribution of CRC-TCS-NPs/5-FU-TCS-NPs in a mouse model. CRC-TCS-NPs/5-FU-TCS-NPs were developed by ionic cross-linking. The in vitro combinatorial anticancer effect of the nanomedicine was proven by different assays. Further the pharmacokinetics and biodistribution analyses were performed in Swiss Albino mouse using HPLC. The 5-FU-TCS-NPs (size: 150±40nm, zeta potential: +48.2±5mV) and CRC-TCS-NPs (size: 150±20nm, zeta potential: +35.7±3mV) were proven to be compatible with blood. The in vitro drug release studies at pH4.5 and 7.4 showed a sustained release profile over a period of 4 days, where both the systems exhibited a higher release in acidic pH. The in vitro combinatorial anticancer effects in colon cancer (HT29) cells using MTT, live/dead, mitochondrial membrane potential and cell cycle analysis measurements confirmed the enhanced anticancer effects (2.5 to 3 fold). The pharmacokinetic studies confirmed the improved plasma concentrations of 5-FU and CRC up to 72h, unlike bare CRC and 5-FU. To conclude, the combination of 5-FU-TCS-NPs and CRC-TCS-NPs showed enhanced anticancer effects on colon cancer cells in vitro and improved the bioavailability of the drugs in vivo. The enhanced anticancer effects of combinatorial nanomedicine are advantageous in terms of reduction in the dosage of 5-FU, thereby improving the chemotherapeutic efficacy and patient compliance of colorectal cancer cases. Copyright © 2014 Elsevier B.V. All rights reserved.

Optimum Design of PIλDμ Controller for an Automatic Voltage Regulator System Using Combinatorial Test Design

PubMed Central

Sahib, Mouayad A.; Gambardella, Luca M.; Afzal, Wasif; Zamli, Kamal Z.

2016-01-01

Combinatorial test design is a plan of test that aims to reduce the amount of test cases systematically by choosing a subset of the test cases based on the combination of input variables. The subset covers all possible combinations of a given strength and hence tries to match the effectiveness of the exhaustive set. This mechanism of reduction has been used successfully in software testing research with t-way testing (where t indicates the interaction strength of combinations). Potentially, other systems may exhibit many similarities with this approach. Hence, it could form an emerging application in different areas of research due to its usefulness. To this end, more recently it has been applied in a few research areas successfully. In this paper, we explore the applicability of combinatorial test design technique for Fractional Order (FO), Proportional-Integral-Derivative (PID) parameter design controller, named as FOPID, for an automatic voltage regulator (AVR) system. Throughout the paper, we justify this new application theoretically and practically through simulations. In addition, we report on first experiments indicating its practical use in this field. We design different algorithms and adapted other strategies to cover all the combinations with an optimum and effective test set. Our findings indicate that combinatorial test design can find the combinations that lead to optimum design. Besides this, we also found that by increasing the strength of combination, we can approach to the optimum design in a way that with only 4-way combinatorial set, we can get the effectiveness of an exhaustive test set. This significantly reduced the number of tests needed and thus leads to an approach that optimizes design of parameters quickly. PMID:27829025

A dynamical systems model for combinatorial cancer therapy enhances oncolytic adenovirus efficacy by MEK-inhibition.

PubMed

Bagheri, Neda; Shiina, Marisa; Lauffenburger, Douglas A; Korn, W Michael

2011-02-01

Oncolytic adenoviruses, such as ONYX-015, have been tested in clinical trials for currently untreatable tumors, but have yet to demonstrate adequate therapeutic efficacy. The extent to which viruses infect targeted cells determines the efficacy of this approach but many tumors down-regulate the Coxsackievirus and Adenovirus Receptor (CAR), rendering them less susceptible to infection. Disrupting MAPK pathway signaling by pharmacological inhibition of MEK up-regulates CAR expression, offering possible enhanced adenovirus infection. MEK inhibition, however, interferes with adenovirus replication due to resulting G1-phase cell cycle arrest. Therefore, enhanced efficacy will depend on treatment protocols that productively balance these competing effects. Predictive understanding of how to attain and enhance therapeutic efficacy of combinatorial treatment is difficult since the effects of MEK inhibitors, in conjunction with adenovirus/cell interactions, are complex nonlinear dynamic processes. We investigated combinatorial treatment strategies using a mathematical model that predicts the impact of MEK inhibition on tumor cell proliferation, ONYX-015 infection, and oncolysis. Specifically, we fit a nonlinear differential equation system to dedicated experimental data and analyzed the resulting simulations for favorable treatment strategies. Simulations predicted enhanced combinatorial therapy when both treatments were applied simultaneously; we successfully validated these predictions in an ensuing explicit test study. Further analysis revealed that a CAR-independent mechanism may be responsible for amplified virus production and cell death. We conclude that integrated computational and experimental analysis of combinatorial therapy provides a useful means to identify treatment/infection protocols that yield clinically significant oncolysis. Enhanced oncolytic therapy has the potential to dramatically improve non-surgical cancer treatment, especially in locally advanced or metastatic cases where treatment options remain limited.

Novel drug metabolism indices for pharmacogenetic functional status based on combinatory genotyping of CYP2C9, CYP2C19 and CYP2D6 genes

PubMed Central

Villagra, David; Goethe, John; Schwartz, Harold I; Szarek, Bonnie; Kocherla, Mohan; Gorowski, Krystyna; Windemuth, Andreas; Ruaño, Gualberto

2011-01-01

Aims We aim to demonstrate clinical relevance and utility of four novel drug-metabolism indices derived from a combinatory (multigene) approach to CYP2C9, CYP2C19 and CYP2D6 allele scoring. Each index considers all three genes as complementary components of a liver enzyme drug metabolism system and uniquely benchmarks innate hepatic drug metabolism reserve or alteration through CYP450 combinatory genotype scores. Methods A total of 1199 psychiatric referrals were genotyped for polymorphisms in the CYP2C9, CYP2C19 and CYP2D6 gene loci and were scored on each of the four indices. The data were used to create distributions and rankings of innate drug metabolism capacity to which individuals can be compared. Drug-specific indices are a combination of the drug metabolism indices with substrate-specific coefficients. Results The combinatory drug metabolism indices proved useful in positioning individuals relative to a population with regard to innate drug metabolism capacity prior to pharmacotherapy. Drug-specific indices generate pharmacogenetic guidance of immediate clinical relevance, and can be further modified to incorporate covariates in particular clinical cases. Conclusions We believe that this combinatory approach represents an improvement over the current gene-by-gene reporting by providing greater scope while still allowing for the resolution of a single-gene index when needed. This method will result in novel clinical and research applications, facilitating the translation from pharmacogenomics to personalized medicine, particularly in psychiatry where many drugs are metabolized or activated by multiple CYP450 isoenzymes. PMID:21861665

Co-LncRNA: investigating the lncRNA combinatorial effects in GO annotations and KEGG pathways based on human RNA-Seq data

PubMed Central

Zhao, Zheng; Bai, Jing; Wu, Aiwei; Wang, Yuan; Zhang, Jinwen; Wang, Zishan; Li, Yongsheng; Xu, Juan; Li, Xia

2015-01-01

Long non-coding RNAs (lncRNAs) are emerging as key regulators of diverse biological processes and diseases. However, the combinatorial effects of these molecules in a specific biological function are poorly understood. Identifying co-expressed protein-coding genes of lncRNAs would provide ample insight into lncRNA functions. To facilitate such an effort, we have developed Co-LncRNA, which is a web-based computational tool that allows users to identify GO annotations and KEGG pathways that may be affected by co-expressed protein-coding genes of a single or multiple lncRNAs. LncRNA co-expressed protein-coding genes were first identified in publicly available human RNA-Seq datasets, including 241 datasets across 6560 total individuals representing 28 tissue types/cell lines. Then, the lncRNA combinatorial effects in a given GO annotations or KEGG pathways are taken into account by the simultaneous analysis of multiple lncRNAs in user-selected individual or multiple datasets, which is realized by enrichment analysis. In addition, this software provides a graphical overview of pathways that are modulated by lncRNAs, as well as a specific tool to display the relevant networks between lncRNAs and their co-expressed protein-coding genes. Co-LncRNA also supports users in uploading their own lncRNA and protein-coding gene expression profiles to investigate the lncRNA combinatorial effects. It will be continuously updated with more human RNA-Seq datasets on an annual basis. Taken together, Co-LncRNA provides a web-based application for investigating lncRNA combinatorial effects, which could shed light on their biological roles and could be a valuable resource for this community. Database URL: http://www.bio-bigdata.com/Co-LncRNA/ PMID:26363020

Combinatorial Study of a Novel Poly (ADP-ribose) Polymerase Inhibitor and an HDAC Inhibitor, SAHA, in Leukemic Cell Lines.

PubMed

Hegde, Mahesh; Mantelingu, Kempegowda; Pandey, Monica; Pavankumar, Chottanahalli S; Rangappa, Kanchugarakoppal S; Raghavan, Sathees C

2016-10-01

Cancer is a multifactorial disease, which makes it difficult to cure. Since more than one defective cellular component is often involved during oncogenesis, combination therapy is gaining prominence in the field of cancer therapeutics. The purpose of this study was to investigate the combinatorial effects of a novel PARP inhibitor, P10, and HDAC inhibitor, SAHA, in leukemic cells. Combinatorial effects of P10 and SAHA were tested using propidium iodide staining in different leukemic cells. Further, flowcytometry-based assays such as calcein-AM/ethidium homodimer staining, annexin-FITC/PI staining, and JC-1 staining were carried out to elucidate the mechanism of cell death. In addition, cell-cycle analysis, immunocytochemistry studies, and western blotting analysis were conducted to check the combinatorial effect in Nalm6 cells. Propidium iodide staining showed that P10 in combination with SAHA induced cell death in Nalm6 cells, in which PARP expression and activity is high with a combination index of <0.2. Annexin-FITC/PI staining, JC-1 staining, and other biochemical assays revealed that P10 in combination with SAHA induced apoptosis by causing a change in mitochondrial membrane potential in >65 % cells. Importantly, combinatorial treatment induced S phase arrest in 40-45 % cells due to DNA damage and plausible replicative stress. Finally, we demonstrated that treatment with P10 led to DNA strand breaks, which were further potentiated by SAHA (p < 0.01), leading to activation of apoptosis and increased cell death in PARP-positive leukemic cells. Our study reveals that coadministration of PARP inhibitor with SAHA could be used as a combination therapy against leukemic cells that possess high levels of intrinsic PARP activity.

Hospital daily outpatient visits forecasting using a combinatorial model based on ARIMA and SES models.

PubMed

Luo, Li; Luo, Le; Zhang, Xinli; He, Xiaoli

2017-07-10

Accurate forecasting of hospital outpatient visits is beneficial for the reasonable planning and allocation of healthcare resource to meet the medical demands. In terms of the multiple attributes of daily outpatient visits, such as randomness, cyclicity and trend, time series methods, ARIMA, can be a good choice for outpatient visits forecasting. On the other hand, the hospital outpatient visits are also affected by the doctors' scheduling and the effects are not pure random. Thinking about the impure specialty, this paper presents a new forecasting model that takes cyclicity and the day of the week effect into consideration. We formulate a seasonal ARIMA (SARIMA) model on a daily time series and then a single exponential smoothing (SES) model on the day of the week time series, and finally establish a combinatorial model by modifying them. The models are applied to 1 year of daily visits data of urban outpatients in two internal medicine departments of a large hospital in Chengdu, for forecasting the daily outpatient visits about 1 week ahead. The proposed model is applied to forecast the cross-sectional data for 7 consecutive days of daily outpatient visits over an 8-weeks period based on 43 weeks of observation data during 1 year. The results show that the two single traditional models and the combinatorial model are simplicity of implementation and low computational intensiveness, whilst being appropriate for short-term forecast horizons. Furthermore, the combinatorial model can capture the comprehensive features of the time series data better. Combinatorial model can achieve better prediction performance than the single model, with lower residuals variance and small mean of residual errors which needs to be optimized deeply on the next research step.

Cardiac Stem Cell Hybrids Enhance Myocardial Repair

PubMed Central

Quijada, Pearl; Salunga, Hazel T.; Hariharan, Nirmala; Cubillo, Jonathan D.; El-Sayed, Farid G.; Moshref, Maryam; Bala, Kristin M.; Emathinger, Jacqueline M.; La Torre, Andrea De; Ormachea, Lucia; Alvarez, Roberto; Gude, Natalie A.; Sussman, Mark A.

2015-01-01

Rationale Dual cell transplantation of cardiac progenitor cells (CPCs) and mesenchymal stem cells (MSCs) after infarction improves myocardial repair and performance in large animal models relative to delivery of either cell population. Objective To demonstrate that CardioChimeras (CCs) formed by fusion between CPCs and MSCs have enhanced reparative potential in a mouse model of myocardial infarction relative to individual stem cells or combined cell delivery. Methods and Results Two distinct and clonally derived CCs, CC1 and CC2 were utilized for this study. CCs improved left ventricular anterior wall thickness (AWT) at 4 weeks post injury, but only CC1 treatment preserved AWT at 18 weeks. Ejection fraction was enhanced at 6 weeks in CCs, and functional improvements were maintained in CCs and CPC + MSC groups at 18 weeks. Infarct size was decreased in CCs, whereas CPC + MSC and CPC parent groups remained unchanged at 12 weeks. CCs exhibited increased persistence, engraftment, and expression of early commitment markers within the border zone relative to combinatorial and individual cell population-injected groups. CCs increased capillary density and preserved cardiomyocyte size in the infarcted regions suggesting CCs role in protective paracrine secretion. Conclusions CCs merge the application of distinct cells into a single entity for cellular therapeutic intervention in the progression of heart failure. CCs are a novel cell therapy that improves upon combinatorial cell approaches to support myocardial regeneration. PMID:26228030

Set-Based Discrete Particle Swarm Optimization Based on Decomposition for Permutation-Based Multiobjective Combinatorial Optimization Problems.

PubMed

Yu, Xue; Chen, Wei-Neng; Gu, Tianlong; Zhang, Huaxiang; Yuan, Huaqiang; Kwong, Sam; Zhang, Jun

2018-07-01

This paper studies a specific class of multiobjective combinatorial optimization problems (MOCOPs), namely the permutation-based MOCOPs. Many commonly seen MOCOPs, e.g., multiobjective traveling salesman problem (MOTSP), multiobjective project scheduling problem (MOPSP), belong to this problem class and they can be very different. However, as the permutation-based MOCOPs share the inherent similarity that the structure of their search space is usually in the shape of a permutation tree, this paper proposes a generic multiobjective set-based particle swarm optimization methodology based on decomposition, termed MS-PSO/D. In order to coordinate with the property of permutation-based MOCOPs, MS-PSO/D utilizes an element-based representation and a constructive approach. Through this, feasible solutions under constraints can be generated step by step following the permutation-tree-shaped structure. And problem-related heuristic information is introduced in the constructive approach for efficiency. In order to address the multiobjective optimization issues, the decomposition strategy is employed, in which the problem is converted into multiple single-objective subproblems according to a set of weight vectors. Besides, a flexible mechanism for diversity control is provided in MS-PSO/D. Extensive experiments have been conducted to study MS-PSO/D on two permutation-based MOCOPs, namely the MOTSP and the MOPSP. Experimental results validate that the proposed methodology is promising.

Discovery of Cationic Polymers for Non-viral Gene Delivery using Combinatorial Approaches

PubMed Central

Barua, Sutapa; Ramos, James; Potta, Thrimoorthy; Taylor, David; Huang, Huang-Chiao; Montanez, Gabriela; Rege, Kaushal

2015-01-01

Gene therapy is an attractive treatment option for diseases of genetic origin, including several cancers and cardiovascular diseases. While viruses are effective vectors for delivering exogenous genes to cells, concerns related to insertional mutagenesis, immunogenicity, lack of tropism, decay and high production costs necessitate the discovery of non-viral methods. Significant efforts have been focused on cationic polymers as non-viral alternatives for gene delivery. Recent studies have employed combinatorial syntheses and parallel screening methods for enhancing the efficacy of gene delivery, biocompatibility of the delivery vehicle, and overcoming cellular level barriers as they relate to polymer-mediated transgene uptake, transport, transcription, and expression. This review summarizes and discusses recent advances in combinatorial syntheses and parallel screening of cationic polymer libraries for the discovery of efficient and safe gene delivery systems. PMID:21843141

Programming gene expression with combinatorial promoters

PubMed Central

Cox, Robert Sidney; Surette, Michael G; Elowitz, Michael B

2007-01-01

Promoters control the expression of genes in response to one or more transcription factors (TFs). The architecture of a promoter is the arrangement and type of binding sites within it. To understand natural genetic circuits and to design promoters for synthetic biology, it is essential to understand the relationship between promoter function and architecture. We constructed a combinatorial library of random promoter architectures. We characterized 288 promoters in Escherichia coli, each containing up to three inputs from four different TFs. The library design allowed for multiple −10 and −35 boxes, and we observed varied promoter strength over five decades. To further analyze the functional repertoire, we defined a representation of promoter function in terms of regulatory range, logic type, and symmetry. Using these results, we identified heuristic rules for programming gene expression with combinatorial promoters. PMID:18004278

Analytical validation of a psychiatric pharmacogenomic test.

PubMed

Jablonski, Michael R; King, Nina; Wang, Yongbao; Winner, Joel G; Watterson, Lucas R; Gunselman, Sandra; Dechairo, Bryan M

2018-05-01

The aim of this study was to validate the analytical performance of a combinatorial pharmacogenomics test designed to aid in the appropriate medication selection for neuropsychiatric conditions. Genomic DNA was isolated from buccal swabs. Twelve genes (65 variants/alleles) associated with psychotropic medication metabolism, side effects, and mechanisms of actions were evaluated by bead array, MALDI-TOF mass spectrometry, and/or capillary electrophoresis methods (GeneSight Psychotropic, Assurex Health, Inc.). The combinatorial pharmacogenomics test has a dynamic range of 2.5-20 ng/μl of input genomic DNA, with comparable performance for all assays included in the test. Both the precision and accuracy of the test were >99.9%, with individual gene components between 99.4 and 100%. This study demonstrates that the combinatorial pharmacogenomics test is robust and reproducible, making it suitable for clinical use.

Combinatorial Histone Acetylation Patterns Are Generated by Motif-Specific Reactions.

PubMed

Blasi, Thomas; Feller, Christian; Feigelman, Justin; Hasenauer, Jan; Imhof, Axel; Theis, Fabian J; Becker, Peter B; Marr, Carsten

2016-01-27

Post-translational modifications (PTMs) are pivotal to cellular information processing, but how combinatorial PTM patterns ("motifs") are set remains elusive. We develop a computational framework, which we provide as open source code, to investigate the design principles generating the combinatorial acetylation patterns on histone H4 in Drosophila melanogaster. We find that models assuming purely unspecific or lysine site-specific acetylation rates were insufficient to explain the experimentally determined motif abundances. Rather, these abundances were best described by an ensemble of models with acetylation rates that were specific to motifs. The model ensemble converged upon four acetylation pathways; we validated three of these using independent data from a systematic enzyme depletion study. Our findings suggest that histone acetylation patterns originate through specific pathways involving motif-specific acetylation activity. Copyright © 2016 Elsevier Inc. All rights reserved.

Simulating the component counts of combinatorial structures.

PubMed

Arratia, Richard; Barbour, A D; Ewens, W J; Tavaré, Simon

2018-02-09

This article describes and compares methods for simulating the component counts of random logarithmic combinatorial structures such as permutations and mappings. We exploit the Feller coupling for simulating permutations to provide a very fast method for simulating logarithmic assemblies more generally. For logarithmic multisets and selections, this approach is replaced by an acceptance/rejection method based on a particular conditioning relationship that represents the distribution of the combinatorial structure as that of independent random variables conditioned on a weighted sum. We show how to improve its acceptance rate. We illustrate the method by estimating the probability that a random mapping has no repeated component sizes, and establish the asymptotic distribution of the difference between the number of components and the number of distinct component sizes for a very general class of logarithmic structures. Copyright © 2018. Published by Elsevier Inc.

Single cell systems biology by super-resolution imaging and combinatorial labeling

PubMed Central

Lubeck, Eric; Cai, Long

2012-01-01

Fluorescence microscopy is a powerful quantitative tool for exploring regulatory networks in single cells. However, the number of molecular species that can be measured simultaneously is limited by the spectral separability of fluorophores. Here we demonstrate a simple but general strategy to drastically increase the capacity for multiplex detection of molecules in single cells by using optical super-resolution microscopy (SRM) and combinatorial labeling. As a proof of principle, we labeled mRNAs with unique combinations of fluorophores using Fluorescence in situ Hybridization (FISH), and resolved the sequences and combinations of fluorophores with SRM. We measured the mRNA levels of 32 genes simultaneously in single S. cerevisiae cells. These experiments demonstrate that combinatorial labeling and super-resolution imaging of single cells provides a natural approach to bring systems biology into single cells. PMID:22660740

From monkey-like action recognition to human language: an evolutionary framework for neurolinguistics.

PubMed

Arbib, Michael A

2005-04-01

The article analyzes the neural and functional grounding of language skills as well as their emergence in hominid evolution, hypothesizing stages leading from abilities known to exist in monkeys and apes and presumed to exist in our hominid ancestors right through to modern spoken and signed languages. The starting point is the observation that both premotor area F5 in monkeys and Broca's area in humans contain a "mirror system" active for both execution and observation of manual actions, and that F5 and Broca's area are homologous brain regions. This grounded the mirror system hypothesis of Rizzolatti and Arbib (1998) which offers the mirror system for grasping as a key neural "missing link" between the abilities of our nonhuman ancestors of 20 million years ago and modern human language, with manual gestures rather than a system for vocal communication providing the initial seed for this evolutionary process. The present article, however, goes "beyond the mirror" to offer hypotheses on evolutionary changes within and outside the mirror systems which may have occurred to equip Homo sapiens with a language-ready brain. Crucial to the early stages of this progression is the mirror system for grasping and its extension to permit imitation. Imitation is seen as evolving via a so-called simple system such as that found in chimpanzees (which allows imitation of complex "object-oriented" sequences but only as the result of extensive practice) to a so-called complex system found in humans (which allows rapid imitation even of complex sequences, under appropriate conditions) which supports pantomime. This is hypothesized to have provided the substrate for the development of protosign, a combinatorially open repertoire of manual gestures, which then provides the scaffolding for the emergence of protospeech (which thus owes little to nonhuman vocalizations), with protosign and protospeech then developing in an expanding spiral. It is argued that these stages involve biological evolution of both brain and body. By contrast, it is argued that the progression from protosign and protospeech to languages with full-blown syntax and compositional semantics was a historical phenomenon in the development of Homo sapiens, involving few if any further biological changes.

Obfuscation Framework Based on Functionally Equivalent Combinatorial Logic Families

DTIC Science & Technology

2008-03-01

of Defense, or the United States Government . AFIT/GCS/ENG/08-12 Obfuscation Framework Based on Functionally Equivalent Combinatorial Logic Families...time, United States policy strongly encourages the sale and transfer of some military equipment to foreign governments and makes it easier for...Proceedings of the International Conference on Availability, Reliability and Security, 2007. 14. McDonald, J. Todd and Alec Yasinsac. “Of unicorns and random

Combinatorial study of degree assortativity in networks.

PubMed

Estrada, Ernesto

2011-10-01

Why are some networks degree-degree correlated (assortative), while most of the real-world ones are anticorrelated (disassortative)? Here, we prove, by combinatorial methods, that the assortativity of a network depends only on three structural factors: transitivity (clustering coefficient), intermodular connectivity, and branching. Then, a network is assortative if the contributions of the first two factors are larger than that of the third. Highly branched networks are likely to be disassortative.

Development of combinatorial chemistry methods for coatings: high-throughput adhesion evaluation and scale-up of combinatorial leads.

PubMed

Potyrailo, Radislav A; Chisholm, Bret J; Morris, William G; Cawse, James N; Flanagan, William P; Hassib, Lamyaa; Molaison, Chris A; Ezbiansky, Karin; Medford, George; Reitz, Hariklia

2003-01-01

Coupling of combinatorial chemistry methods with high-throughput (HT) performance testing and measurements of resulting properties has provided a powerful set of tools for the 10-fold accelerated discovery of new high-performance coating materials for automotive applications. Our approach replaces labor-intensive steps with automated systems for evaluation of adhesion of 8 x 6 arrays of coating elements that are discretely deposited on a single 9 x 12 cm plastic substrate. Performance of coatings is evaluated with respect to their resistance to adhesion loss, because this parameter is one of the primary considerations in end-use automotive applications. Our HT adhesion evaluation provides previously unavailable capabilities of high speed and reproducibility of testing by using a robotic automation, an expanded range of types of tested coatings by using the coating tagging strategy, and an improved quantitation by using high signal-to-noise automatic imaging. Upon testing, the coatings undergo changes that are impossible to quantitatively predict using existing knowledge. Using our HT methodology, we have developed several coatings leads. These HT screening results for the best coating compositions have been validated on the traditional scales of coating formulation and adhesion loss testing. These validation results have confirmed the superb performance of combinatorially developed coatings over conventional coatings on the traditional scale.

Enhancement of Bone-Marrow-Derived Mesenchymal Stem Cell Angiogenic Capacity by NPWT for a Combinatorial Therapy to Promote Wound Healing with Large Defect

PubMed Central

Ma, Zhanjun

2017-01-01

Poor viability of engrafted bone marrow mesenchymal stem cells (BMSCs) often hinders their application for wound healing, and the strategy of how to take full advantage of their angiogenic capacity within wounds still remains unclear. Negative pressure wound therapy (NPWT) has been demonstrated to be effective for enhancing wound healing, especially for the promotion of angiogenesis within wounds. Here we utilized combinatory strategy using the transplantation of BMSCs and NPWT to investigate whether this combinatory therapy could accelerate angiogenesis in wounds. In vitro, after 9-day culture, BMSCs proliferation significantly increased in NPWT group. Furthermore, NPWT induced their differentiation into the angiogenic related cells, which are indispensable for wound angiogenesis. In vivo, rat full-thickness cutaneous wounds treated with BMSCs combined with NPWT exhibited better viability of the cells and enhanced angiogenesis and maturation of functional blood vessels than did local BMSC injection or NPWT alone. Expression of angiogenesis markers (NG2, VEGF, CD31, and α-SMA) was upregulated in wounds treated with combined BMSCs with NPWT. Our data suggest that NPWT may act as an inductive role to enhance BMSCs angiogenic capacity and this combinatorial therapy may serve as a simple but efficient clinical solution for complex wounds with large defects. PMID:28243602

Coupled Phases and Combinatorial Selection in Fluctuating Hydrothermal Pools: A Scenario to Guide Experimental Approaches to the Origin of Cellular Life

PubMed Central

Damer, Bruce; Deamer, David

2015-01-01

Hydrothermal fields on the prebiotic Earth are candidate environments for biogenesis. We propose a model in which molecular systems driven by cycles of hydration and dehydration in such sites undergo chemical evolution in dehydrated films on mineral surfaces followed by encapsulation and combinatorial selection in a hydrated bulk phase. The dehydrated phase can consist of concentrated eutectic mixtures or multilamellar liquid crystalline matrices. Both conditions organize and concentrate potential monomers and thereby promote polymerization reactions that are driven by reduced water activity in the dehydrated phase. In the case of multilamellar lipid matrices, polymers that have been synthesized are captured in lipid vesicles upon rehydration to produce a variety of molecular systems. Each vesicle represents a protocell, an “experiment” in a natural version of combinatorial chemistry. Two kinds of selective processes can then occur. The first is a physical process in which relatively stable molecular systems will be preferentially selected. The second is a chemical process in which rare combinations of encapsulated polymers form systems capable of capturing energy and nutrients to undergo growth by catalyzed polymerization. Given continued cycling over extended time spans, such combinatorial processes will give rise to molecular systems having the fundamental properties of life. PMID:25780958

A combinatorial perspective of the protein inference problem.

PubMed

Yang, Chao; He, Zengyou; Yu, Weichuan

2013-01-01

In a shotgun proteomics experiment, proteins are the most biologically meaningful output. The success of proteomics studies depends on the ability to accurately and efficiently identify proteins. Many methods have been proposed to facilitate the identification of proteins from peptide identification results. However, the relationship between protein identification and peptide identification has not been thoroughly explained before. In this paper, we devote ourselves to a combinatorial perspective of the protein inference problem. We employ combinatorial mathematics to calculate the conditional protein probabilities (protein probability means the probability that a protein is correctly identified) under three assumptions, which lead to a lower bound, an upper bound, and an empirical estimation of protein probabilities, respectively. The combinatorial perspective enables us to obtain an analytical expression for protein inference. Our method achieves comparable results with ProteinProphet in a more efficient manner in experiments on two data sets of standard protein mixtures and two data sets of real samples. Based on our model, we study the impact of unique peptides and degenerate peptides (degenerate peptides are peptides shared by at least two proteins) on protein probabilities. Meanwhile, we also study the relationship between our model and ProteinProphet. We name our program ProteinInfer. Its Java source code, our supplementary document and experimental results are available at: >http://bioinformatics.ust.hk/proteininfer.

Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach

PubMed Central

Ye, Yusen; Gao, Lin; Zhang, Shihua

2017-01-01

Transcription factors play a key role in transcriptional regulation of genes and determination of cellular identity through combinatorial interactions. However, current studies about combinatorial regulation is deficient due to lack of experimental data in the same cellular environment and extensive existence of data noise. Here, we adopt a Bayesian CANDECOMP/PARAFAC (CP) factorization approach (BCPF) to integrate multiple datasets in a network paradigm for determining precise TF interaction landscapes. In our first application, we apply BCPF to integrate three networks built based on diverse datasets of multiple cell lines from ENCODE respectively to predict a global and precise TF interaction network. This network gives 38 novel TF interactions with distinct biological functions. In our second application, we apply BCPF to seven types of cell type TF regulatory networks and predict seven cell lineage TF interaction networks, respectively. By further exploring the dynamics and modularity of them, we find cell lineage-specific hub TFs participate in cell type or lineage-specific regulation by interacting with non-specific TFs. Furthermore, we illustrate the biological function of hub TFs by taking those of cancer lineage and blood lineage as examples. Taken together, our integrative analysis can reveal more precise and extensive description about human TF combinatorial interactions. PMID:29033978

Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach.

PubMed

Ye, Yusen; Gao, Lin; Zhang, Shihua

2017-01-01

Transcription factors play a key role in transcriptional regulation of genes and determination of cellular identity through combinatorial interactions. However, current studies about combinatorial regulation is deficient due to lack of experimental data in the same cellular environment and extensive existence of data noise. Here, we adopt a Bayesian CANDECOMP/PARAFAC (CP) factorization approach (BCPF) to integrate multiple datasets in a network paradigm for determining precise TF interaction landscapes. In our first application, we apply BCPF to integrate three networks built based on diverse datasets of multiple cell lines from ENCODE respectively to predict a global and precise TF interaction network. This network gives 38 novel TF interactions with distinct biological functions. In our second application, we apply BCPF to seven types of cell type TF regulatory networks and predict seven cell lineage TF interaction networks, respectively. By further exploring the dynamics and modularity of them, we find cell lineage-specific hub TFs participate in cell type or lineage-specific regulation by interacting with non-specific TFs. Furthermore, we illustrate the biological function of hub TFs by taking those of cancer lineage and blood lineage as examples. Taken together, our integrative analysis can reveal more precise and extensive description about human TF combinatorial interactions.

A Key Pre-Distribution Scheme Based on µ-PBIBD for Enhancing Resilience in Wireless Sensor Networks.

PubMed

Yuan, Qi; Ma, Chunguang; Yu, Haitao; Bian, Xuefen

2018-05-12

Many key pre-distribution (KPD) schemes based on combinatorial design were proposed for secure communication of wireless sensor networks (WSNs). Due to complexity of constructing the combinatorial design, it is infeasible to generate key rings using the corresponding combinatorial design in large scale deployment of WSNs. In this paper, we present a definition of new combinatorial design, termed “µ-partially balanced incomplete block design (µ-PBIBD)”, which is a refinement of partially balanced incomplete block design (PBIBD), and then describe a 2-D construction of µ-PBIBD which is mapped to KPD in WSNs. Our approach is of simple construction which provides a strong key connectivity and a poor network resilience. To improve the network resilience of KPD based on 2-D µ-PBIBD, we propose a KPD scheme based on 3-D Ex-µ-PBIBD which is a construction of µ-PBIBD from 2-D space to 3-D space. Ex-µ-PBIBD KPD scheme improves network scalability and resilience while has better key connectivity. Theoretical analysis and comparison with the related schemes show that key pre-distribution scheme based on Ex-µ-PBIBD provides high network resilience and better key scalability, while it achieves a trade-off between network resilience and network connectivity.

Diversity-oriented combinatorial biosynthesis of benzenediol lactone scaffolds by subunit shuffling of fungal polyketide synthases.

PubMed

Xu, Yuquan; Zhou, Tong; Zhang, Shuwei; Espinosa-Artiles, Patricia; Wang, Luoyi; Zhang, Wei; Lin, Min; Gunatilaka, A A Leslie; Zhan, Jixun; Molnár, István

2014-08-26

Combinatorial biosynthesis aspires to exploit the promiscuity of microbial anabolic pathways to engineer the synthesis of new chemical entities. Fungal benzenediol lactone (BDL) polyketides are important pharmacophores with wide-ranging bioactivities, including heat shock response and immune system modulatory effects. Their biosynthesis on a pair of sequentially acting iterative polyketide synthases (iPKSs) offers a test case for the modularization of secondary metabolic pathways into "build-couple-pair" combinatorial synthetic schemes. Expression of random pairs of iPKS subunits from four BDL model systems in a yeast heterologous host created a diverse library of BDL congeners, including a polyketide with an unnatural skeleton and heat shock response-inducing activity. Pairwise heterocombinations of the iPKS subunits also helped to illuminate the innate, idiosyncratic programming of these enzymes. Even in combinatorial contexts, these biosynthetic programs remained largely unchanged, so that the iPKSs built their cognate biosynthons, coupled these building blocks into chimeric polyketide intermediates, and catalyzed intramolecular pairing to release macrocycles or α-pyrones. However, some heterocombinations also provoked stuttering, i.e., the relaxation of iPKSs chain length control to assemble larger homologous products. The success of such a plug and play approach to biosynthesize novel chemical diversity bodes well for bioprospecting unnatural polyketides for drug discovery.

High-throughput flow injection analysis mass spectroscopy with networked delivery of color-rendered results. 2. Three-dimensional spectral mapping of 96-well combinatorial chemistry racks.

PubMed

Görlach, E; Richmond, R; Lewis, I

1998-08-01

For the last two years, the mass spectroscopy section of the Novartis Pharma Research Core Technology group has analyzed tens of thousands of multiple parallel synthesis samples from the Novartis Pharma Combinatorial Chemistry program, using an in-house developed automated high-throughput flow injection analysis electrospray ionization mass spectroscopy system. The electrospray spectra of these samples reflect the many structures present after the cleavage step from the solid support. The overall success of the sequential synthesis is mirrored in the purity of the expected end product, but the partial success of individual synthesis steps is evident in the impurities in the mass spectrum. However this latter reaction information, which is of considerable utility to the combinatorial chemist, is effectively hidden from view by the very large number of analyzed samples. This information is now revealed at the workbench of the combinatorial chemist by a novel three-dimensional display of each rack's complete mass spectral ion current using the in-house RackViewer Visual Basic application. Colorization of "forbidden loss" and "forbidden gas-adduct" zones, normalization to expected monoisotopic molecular weight, colorization of ionization intensity, and sorting by row or column were used in combination to highlight systematic patterns in the mass spectroscopy data.

Successful application of the dual-vector system II in creating a reliable phage-displayed combinatorial Fab library.

PubMed

Song, Suk-yoon; Hur, Byung-ung; Lee, Kyung-woo; Choi, Hyo-jung; Kim, Sung-soo; Kang, Goo; Cha, Sang-hoon

2009-03-31

The dual-vector system-II (DVS-II), which allows efficient display of Fab antibodies on phage, has been reported previously, but its practical applicability in a phage-displayed antibody library has not been verified. To resolve this issue, we created two small combinatorial human Fab antibody libraries using the DVS-II, and isolation of target-specific antibodies was attempted. Biopanning of one antibody library, termed DVFAB-1L library, which has a 1.3 x 10(7) combinatorial antibody complexity, against fluorescein-BSA resulted in successful isolation of human Fab clones specific for the antigen despite the presence of only a single light chain in the library. By using the unique feature of the DVS-II, an antibody library of a larger size, named DVFAB-131L, which has a 1.5 x 10(9) combinatorial antibody complexity, was also generated in a rapid manner by combining 1.3 x 10(7) heavy chains and 131 light chains and more diverse anti-fluorescein-BSA Fab antibody clones were successfully obtained. Our results demonstrate that the DVS-II can be applied readily in creating phage-displayed antibody libraries with much less effort, and target-specific antibody clones can be isolated reliably via light chain promiscuity of antibody molecule.

A Key Pre-Distribution Scheme Based on µ-PBIBD for Enhancing Resilience in Wireless Sensor Networks

PubMed Central

Yuan, Qi; Ma, Chunguang; Yu, Haitao; Bian, Xuefen

2018-01-01

Many key pre-distribution (KPD) schemes based on combinatorial design were proposed for secure communication of wireless sensor networks (WSNs). Due to complexity of constructing the combinatorial design, it is infeasible to generate key rings using the corresponding combinatorial design in large scale deployment of WSNs. In this paper, we present a definition of new combinatorial design, termed “µ-partially balanced incomplete block design (µ-PBIBD)”, which is a refinement of partially balanced incomplete block design (PBIBD), and then describe a 2-D construction of µ-PBIBD which is mapped to KPD in WSNs. Our approach is of simple construction which provides a strong key connectivity and a poor network resilience. To improve the network resilience of KPD based on 2-D µ-PBIBD, we propose a KPD scheme based on 3-D Ex-µ-PBIBD which is a construction of µ-PBIBD from 2-D space to 3-D space. Ex-µ-PBIBD KPD scheme improves network scalability and resilience while has better key connectivity. Theoretical analysis and comparison with the related schemes show that key pre-distribution scheme based on Ex-µ-PBIBD provides high network resilience and better key scalability, while it achieves a trade-off between network resilience and network connectivity. PMID:29757244

The Orbital precession around oblate spheroids

NASA Astrophysics Data System (ADS)

Montanus, J. M. C.

2006-07-01

An exact series will be given for the gravitational potential generated by an oblate gravitating source. To this end the corresponding Epstein-Hubbell type elliptic integral is evaluated. The procedure is based on the Legendre polynomial expansion method and on combinatorial techniques. The result is of interest for gravitational models based on the linearity of the gravitational potential. The series approximation for such potentials is of use for the analysis of orbital motions around a nonspherical source. It can be considered advantageous that the analysis is purely algebraic. Numerical approximations are not required. As an important example, the expression for the orbital precession will be derived for an object orbiting around an oblate homogeneous spheroid.

Fermionic Field Theory for Trees and Forests

NASA Astrophysics Data System (ADS)

Caracciolo, Sergio; Jacobsen, Jesper Lykke; Saleur, Hubert; Sokal, Alan D.; Sportiello, Andrea

2004-08-01

We prove a generalization of Kirchhoff’s matrix-tree theorem in which a large class of combinatorial objects are represented by non-Gaussian Grassmann integrals. As a special case, we show that unrooted spanning forests, which arise as a q→0 limit of the Potts model, can be represented by a Grassmann theory involving a Gaussian term and a particular bilocal four-fermion term. We show that this latter model can be mapped, to all orders in perturbation theory, onto the N-vector model at N=-1 or, equivalently, onto the σ model taking values in the unit supersphere in R1|2. It follows that, in two dimensions, this fermionic model is perturbatively asymptotically free.

Computer Description of the Field Artillery Ammunition Supply Vehicle

DTIC Science & Technology

1983-04-01

Combinatorial Geometry (COM-GEOM) GIFT Computer Code Computer Target Description 2& AfTNACT (Cmne M feerve shb N ,neemssalyan ify by block number) A...input to the GIFT computer code to generate target vulnerability data. F.a- 4 ono OF I NOV 5S OLETE UNCLASSIFIED SECUOITY CLASSIFICATION OF THIS PAGE...Combinatorial Geometry (COM-GEOM) desrription. The "Geometric Information for Tarqets" ( GIFT ) computer code accepts the CO!-GEOM description and

Sin(x)**2 + cos(x)**2 = 1. [programming identities using comparative combinatorial substitutions

NASA Technical Reports Server (NTRS)

Stoutemyer, D. R.

1977-01-01

Attempts to achieve tasteful automatic employment of the identities sin sq x + cos sq x = 1 and cos sq h x -sin sq h x = 1 in a manner which truly minimizes the complexity of the resulting expression are described. The disappointments of trigonometric reduction, trigonometric expansion, pattern matching, Poisson series, and Demoivre's theorem are related. The advantages of using the method of comparative combinatorial substitutions are illustrated.

Optimization of Highway Work Zone Decisions Considering Short-Term and Long-Term Impacts

DTIC Science & Technology

2010-01-01

strategies which can minimize the one-time work zone cost. Considering the complex and combinatorial nature of this optimization problem, a heuristic...combination of lane closure and traffic control strategies which can minimize the one-time work zone cost. Considering the complex and combinatorial nature ...zone) NV # the number of vehicle classes NPV $ Net Present Value p’(t) % Adjusted traffic diversion rate at time t p(t) % Natural diversion rate

Thermal analysis of combinatorial solid geometry models using SINDA

NASA Technical Reports Server (NTRS)

Gerencser, Diane; Radke, George; Introne, Rob; Klosterman, John; Miklosovic, Dave

1993-01-01

Algorithms have been developed using Monte Carlo techniques to determine the thermal network parameters necessary to perform a finite difference analysis on Combinatorial Solid Geometry (CSG) models. Orbital and laser fluxes as well as internal heat generation are modeled to facilitate satellite modeling. The results of the thermal calculations are used to model the infrared (IR) images of targets and assess target vulnerability. Sample analyses and validation are presented which demonstrate code products.

Combinatorial study of Ni-Ti-Pt ternary metal gate electrodes on HfO{sub 2} for the advanced gate stack

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

Chang, K.-S.; Green, M. L.; Suehle, J.

2006-10-02

The authors have fabricated combinatorial Ni-Ti-Pt ternary metal gate thin film libraries on HfO{sub 2} using magnetron co-sputtering to investigate flatband voltage shift ({delta}V{sub fb}), work function ({phi}{sub m}), and leakage current density (J{sub L}) variations. A more negative {delta}V{sub fb} is observed close to the Ti-rich corner than at the Ni- and Pt-rich corners, implying smaller {phi}{sub m} near the Ti-rich corners and higher {phi}{sub m} near the Ni- and Pt-rich corners. In addition, measured J{sub L} values can be explained consistently with the observed {phi}{sub m} variations. Combinatorial methodologies prove to be useful in surveying the large compositionalmore » space of ternary alloy metal gate electrode systems.« less

DNA-Encoded Dynamic Combinatorial Chemical Libraries.

PubMed

Reddavide, Francesco V; Lin, Weilin; Lehnert, Sarah; Zhang, Yixin

2015-06-26

Dynamic combinatorial chemistry (DCC) explores the thermodynamic equilibrium of reversible reactions. Its application in the discovery of protein binders is largely limited by difficulties in the analysis of complex reaction mixtures. DNA-encoded chemical library (DECL) technology allows the selection of binders from a mixture of up to billions of different compounds; however, experimental results often show low a signal-to-noise ratio and poor correlation between enrichment factor and binding affinity. Herein we describe the design and application of DNA-encoded dynamic combinatorial chemical libraries (EDCCLs). Our experiments have shown that the EDCCL approach can be used not only to convert monovalent binders into high-affinity bivalent binders, but also to cause remarkably enhanced enrichment of potent bivalent binders by driving their in situ synthesis. We also demonstrate the application of EDCCLs in DNA-templated chemical reactions. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Learning to Predict Combinatorial Structures

NASA Astrophysics Data System (ADS)

Vembu, Shankar

2009-12-01

The major challenge in designing a discriminative learning algorithm for predicting structured data is to address the computational issues arising from the exponential size of the output space. Existing algorithms make different assumptions to ensure efficient, polynomial time estimation of model parameters. For several combinatorial structures, including cycles, partially ordered sets, permutations and other graph classes, these assumptions do not hold. In this thesis, we address the problem of designing learning algorithms for predicting combinatorial structures by introducing two new assumptions: (i) The first assumption is that a particular counting problem can be solved efficiently. The consequence is a generalisation of the classical ridge regression for structured prediction. (ii) The second assumption is that a particular sampling problem can be solved efficiently. The consequence is a new technique for designing and analysing probabilistic structured prediction models. These results can be applied to solve several complex learning problems including but not limited to multi-label classification, multi-category hierarchical classification, and label ranking.

Discovery of Antibiotics-derived Polymers for Gene Delivery using Combinatorial Synthesis and Cheminformatics Modeling

PubMed Central

Potta, Thrimoorthy; Zhen, Zhuo; Grandhi, Taraka Sai Pavan; Christensen, Matthew D.; Ramos, James; Breneman, Curt M.; Rege, Kaushal

2014-01-01

We describe the combinatorial synthesis and cheminformatics modeling of aminoglycoside antibiotics-derived polymers for transgene delivery and expression. Fifty-six polymers were synthesized by polymerizing aminoglycosides with diglycidyl ether cross-linkers. Parallel screening resulted in identification of several lead polymers that resulted in high transgene expression levels in cells. The role of polymer physicochemical properties in determining efficacy of transgene expression was investigated using Quantitative Structure-Activity Relationship (QSAR) cheminformatics models based on Support Vector Regression (SVR) and ‘building block’ polymer structures. The QSAR model exhibited high predictive ability, and investigation of descriptors in the model, using molecular visualization and correlation plots, indicated that physicochemical attributes related to both, aminoglycosides and diglycidyl ethers facilitated transgene expression. This work synergistically combines combinatorial synthesis and parallel screening with cheminformatics-based QSAR models for discovery and physicochemical elucidation of effective antibiotics-derived polymers for transgene delivery in medicine and biotechnology. PMID:24331709

Optimal weighted combinatorial forecasting model of QT dispersion of ECGs in Chinese adults.

PubMed

Wen, Zhang; Miao, Ge; Xinlei, Liu; Minyi, Cen

2016-07-01

This study aims to provide a scientific basis for unifying the reference value standard of QT dispersion of ECGs in Chinese adults. Three predictive models including regression model, principal component model, and artificial neural network model are combined to establish the optimal weighted combination model. The optimal weighted combination model and single model are verified and compared. Optimal weighted combinatorial model can reduce predicting risk of single model and improve the predicting precision. The reference value of geographical distribution of Chinese adults' QT dispersion was precisely made by using kriging methods. When geographical factors of a particular area are obtained, the reference value of QT dispersion of Chinese adults in this area can be estimated by using optimal weighted combinatorial model and reference value of the QT dispersion of Chinese adults anywhere in China can be obtained by using geographical distribution figure as well.

Development of New Sensing Materials Using Combinatorial and High-Throughput Experimentation

NASA Astrophysics Data System (ADS)

Potyrailo, Radislav A.; Mirsky, Vladimir M.

New sensors with improved performance characteristics are needed for applications as diverse as bedside continuous monitoring, tracking of environmental pollutants, monitoring of food and water quality, monitoring of chemical processes, and safety in industrial, consumer, and automotive settings. Typical requirements in sensor improvement are selectivity, long-term stability, sensitivity, response time, reversibility, and reproducibility. Design of new sensing materials is the important cornerstone in the effort to develop new sensors. Often, sensing materials are too complex to predict their performance quantitatively in the design stage. Thus, combinatorial and high-throughput experimentation methodologies provide an opportunity to generate new required data to discover new sensing materials and/or to optimize existing material compositions. The goal of this chapter is to provide an overview of the key concepts of experimental development of sensing materials using combinatorial and high-throughput experimentation tools, and to promote additional fruitful interactions between computational scientists and experimentalists.

Fast Modeling of Binding Affinities by Means of Superposing Significant Interaction Rules (SSIR) Method

PubMed Central

Besalú, Emili

2016-01-01

The Superposing Significant Interaction Rules (SSIR) method is described. It is a general combinatorial and symbolic procedure able to rank compounds belonging to combinatorial analogue series. The procedure generates structure-activity relationship (SAR) models and also serves as an inverse SAR tool. The method is fast and can deal with large databases. SSIR operates from statistical significances calculated from the available library of compounds and according to the previously attached molecular labels of interest or non-interest. The required symbolic codification allows dealing with almost any combinatorial data set, even in a confidential manner, if desired. The application example categorizes molecules as binding or non-binding, and consensus ranking SAR models are generated from training and two distinct cross-validation methods: leave-one-out and balanced leave-two-out (BL2O), the latter being suited for the treatment of binary properties. PMID:27240346

Review of high-throughput techniques for detecting solid phase Transformation from material libraries produced by combinatorial methods

NASA Technical Reports Server (NTRS)

Lee, Jonathan A.

2005-01-01

High-throughput measurement techniques are reviewed for solid phase transformation from materials produced by combinatorial methods, which are highly efficient concepts to fabricate large variety of material libraries with different compositional gradients on a single wafer. Combinatorial methods hold high potential for reducing the time and costs associated with the development of new materials, as compared to time-consuming and labor-intensive conventional methods that test large batches of material, one- composition at a time. These high-throughput techniques can be automated to rapidly capture and analyze data, using the entire material library on a single wafer, thereby accelerating the pace of materials discovery and knowledge generation for solid phase transformations. The review covers experimental techniques that are applicable to inorganic materials such as shape memory alloys, graded materials, metal hydrides, ferric materials, semiconductors and industrial alloys.

Exploiting Quantum Resonance to Solve Combinatorial Problems

NASA Technical Reports Server (NTRS)

Zak, Michail; Fijany, Amir

2006-01-01

Quantum resonance would be exploited in a proposed quantum-computing approach to the solution of combinatorial optimization problems. In quantum computing in general, one takes advantage of the fact that an algorithm cannot be decoupled from the physical effects available to implement it. Prior approaches to quantum computing have involved exploitation of only a subset of known quantum physical effects, notably including parallelism and entanglement, but not including resonance. In the proposed approach, one would utilize the combinatorial properties of tensor-product decomposability of unitary evolution of many-particle quantum systems for physically simulating solutions to NP-complete problems (a class of problems that are intractable with respect to classical methods of computation). In this approach, reinforcement and selection of a desired solution would be executed by means of quantum resonance. Classes of NP-complete problems that are important in practice and could be solved by the proposed approach include planning, scheduling, search, and optimal design.

Combinatorial studies of (1-x)Na0.5Bi0.5TiO3-xBaTiO3 thin-film chips

NASA Astrophysics Data System (ADS)

Cheng, Hong-Wei; Zhang, Xue-Jin; Zhang, Shan-Tao; Feng, Yan; Chen, Yan-Feng; Liu, Zhi-Guo; Cheng, Guang-Xi

2004-09-01

Applying a combinatorial methodology, (1-x)Na0.5Bi0.5TiO3-xBaTiO3 (NBT-BT) thin-film chips were fabricated on (001)-LaAlO3 substrates by pulsed laser deposition with a few quaternary masks. A series of NBT-BT library with the composition of BT ranged from 0 to 44% was obtained with uniform composition and well crystallinity. The relation between the concentration of NBT-BT and their structural and dielectric properties were investigated by x-ray diffraction (XRD), evanescent microwave probe, atomic force microscopy, and Raman spectroscopy. An obvious morphotropic phase boundary (MPB) was established to be about 9% BT by XRD, Raman frequency shift, and dielectric anomaly, different from the well-known MPB of the materials. The result shows the high efficiency of combinatorial method in searching new relaxor ferroelectrics.

A combinatorial code for pattern formation in Drosophila oogenesis.

PubMed

Yakoby, Nir; Bristow, Christopher A; Gong, Danielle; Schafer, Xenia; Lembong, Jessica; Zartman, Jeremiah J; Halfon, Marc S; Schüpbach, Trudi; Shvartsman, Stanislav Y

2008-11-01

Two-dimensional patterning of the follicular epithelium in Drosophila oogenesis is required for the formation of three-dimensional eggshell structures. Our analysis of a large number of published gene expression patterns in the follicle cells suggests that they follow a simple combinatorial code based on six spatial building blocks and the operations of union, difference, intersection, and addition. The building blocks are related to the distribution of inductive signals, provided by the highly conserved epidermal growth factor receptor and bone morphogenetic protein signaling pathways. We demonstrate the validity of the code by testing it against a set of patterns obtained in a large-scale transcriptional profiling experiment. Using the proposed code, we distinguish 36 distinct patterns for 81 genes expressed in the follicular epithelium and characterize their joint dynamics over four stages of oogenesis. The proposed combinatorial framework allows systematic analysis of the diversity and dynamics of two-dimensional transcriptional patterns and guides future studies of gene regulation.

A noisy chaotic neural network for solving combinatorial optimization problems: stochastic chaotic simulated annealing.

PubMed

Wang, Lipo; Li, Sa; Tian, Fuyu; Fu, Xiuju

2004-10-01

Recently Chen and Aihara have demonstrated both experimentally and mathematically that their chaotic simulated annealing (CSA) has better search ability for solving combinatorial optimization problems compared to both the Hopfield-Tank approach and stochastic simulated annealing (SSA). However, CSA may not find a globally optimal solution no matter how slowly annealing is carried out, because the chaotic dynamics are completely deterministic. In contrast, SSA tends to settle down to a global optimum if the temperature is reduced sufficiently slowly. Here we combine the best features of both SSA and CSA, thereby proposing a new approach for solving optimization problems, i.e., stochastic chaotic simulated annealing, by using a noisy chaotic neural network. We show the effectiveness of this new approach with two difficult combinatorial optimization problems, i.e., a traveling salesman problem and a channel assignment problem for cellular mobile communications.

A new multi-objective optimization model for preventive maintenance and replacement scheduling of multi-component systems

NASA Astrophysics Data System (ADS)

Moghaddam, Kamran S.; Usher, John S.

2011-07-01

In this article, a new multi-objective optimization model is developed to determine the optimal preventive maintenance and replacement schedules in a repairable and maintainable multi-component system. In this model, the planning horizon is divided into discrete and equally-sized periods in which three possible actions must be planned for each component, namely maintenance, replacement, or do nothing. The objective is to determine a plan of actions for each component in the system while minimizing the total cost and maximizing overall system reliability simultaneously over the planning horizon. Because of the complexity, combinatorial and highly nonlinear structure of the mathematical model, two metaheuristic solution methods, generational genetic algorithm, and a simulated annealing are applied to tackle the problem. The Pareto optimal solutions that provide good tradeoffs between the total cost and the overall reliability of the system can be obtained by the solution approach. Such a modeling approach should be useful for maintenance planners and engineers tasked with the problem of developing recommended maintenance plans for complex systems of components.

Performance Analysis of an Actor-Based Distributed Simulation

NASA Technical Reports Server (NTRS)

Schoeffler, James D.

1998-01-01

Object-oriented design of simulation programs appears to be very attractive because of the natural association of components in the simulated system with objects. There is great potential in distributing the simulation across several computers for the purpose of parallel computation and its consequent handling of larger problems in less elapsed time. One approach to such a design is to use "actors", that is, active objects with their own thread of control. Because these objects execute concurrently, communication is via messages. This is in contrast to an object-oriented design using passive objects where communication between objects is via method calls (direct calls when they are in the same address space and remote procedure calls when they are in different address spaces or different machines). This paper describes a performance analysis program for the evaluation of a design for distributed simulations based upon actors.

Breast cancer prognosis by combinatorial analysis of gene expression data.

PubMed

Alexe, Gabriela; Alexe, Sorin; Axelrod, David E; Bonates, Tibérius O; Lozina, Irina I; Reiss, Michael; Hammer, Peter L

2006-01-01

The potential of applying data analysis tools to microarray data for diagnosis and prognosis is illustrated on the recent breast cancer dataset of van 't Veer and coworkers. We re-examine that dataset using the novel technique of logical analysis of data (LAD), with the double objective of discovering patterns characteristic for cases with good or poor outcome, using them for accurate and justifiable predictions; and deriving novel information about the role of genes, the existence of special classes of cases, and other factors. Data were analyzed using the combinatorics and optimization-based method of LAD, recently shown to provide highly accurate diagnostic and prognostic systems in cardiology, cancer proteomics, hematology, pulmonology, and other disciplines. LAD identified a subset of 17 of the 25,000 genes, capable of fully distinguishing between patients with poor, respectively good prognoses. An extensive list of 'patterns' or 'combinatorial biomarkers' (that is, combinations of genes and limitations on their expression levels) was generated, and 40 patterns were used to create a prognostic system, shown to have 100% and 92.9% weighted accuracy on the training and test sets, respectively. The prognostic system uses fewer genes than other methods, and has similar or better accuracy than those reported in other studies. Out of the 17 genes identified by LAD, three (respectively, five) were shown to play a significant role in determining poor (respectively, good) prognosis. Two new classes of patients (described by similar sets of covering patterns, gene expression ranges, and clinical features) were discovered. As a by-product of the study, it is shown that the training and the test sets of van 't Veer have differing characteristics. The study shows that LAD provides an accurate and fully explanatory prognostic system for breast cancer using genomic data (that is, a system that, in addition to predicting good or poor prognosis, provides an individualized explanation of the reasons for that prognosis for each patient). Moreover, the LAD model provides valuable insights into the roles of individual and combinatorial biomarkers, allows the discovery of new classes of patients, and generates a vast library of biomedical research hypotheses.

Switched Systems and Motion Coordination: Combinatorial Challenges

NASA Technical Reports Server (NTRS)

Sadovsky, Alexander V.

2016-01-01

Problems of routing commercial air traffic in a terminal airspace encounter different constraints: separation assurance, aircraft performance limitations, regulations. The general setting of these problems is that of a switched control system. Such a system combines the differentiable motion of the aircraft with the combinatorial choices of choosing precedence when traffic routes merge and choosing branches when the routes diverge. This presentation gives an overview of the problem, the ATM context, related literature, and directions for future research.

Hybrid Self-Adaptive Evolution Strategies Guided by Neighborhood Structures for Combinatorial Optimization Problems.

PubMed

Coelho, V N; Coelho, I M; Souza, M J F; Oliveira, T A; Cota, L P; Haddad, M N; Mladenovic, N; Silva, R C P; Guimarães, F G

2016-01-01

This article presents an Evolution Strategy (ES)--based algorithm, designed to self-adapt its mutation operators, guiding the search into the solution space using a Self-Adaptive Reduced Variable Neighborhood Search procedure. In view of the specific local search operators for each individual, the proposed population-based approach also fits into the context of the Memetic Algorithms. The proposed variant uses the Greedy Randomized Adaptive Search Procedure with different greedy parameters for generating its initial population, providing an interesting exploration-exploitation balance. To validate the proposal, this framework is applied to solve three different [Formula: see text]-Hard combinatorial optimization problems: an Open-Pit-Mining Operational Planning Problem with dynamic allocation of trucks, an Unrelated Parallel Machine Scheduling Problem with Setup Times, and the calibration of a hybrid fuzzy model for Short-Term Load Forecasting. Computational results point out the convergence of the proposed model and highlight its ability in combining the application of move operations from distinct neighborhood structures along the optimization. The results gathered and reported in this article represent a collective evidence of the performance of the method in challenging combinatorial optimization problems from different application domains. The proposed evolution strategy demonstrates an ability of adapting the strength of the mutation disturbance during the generations of its evolution process. The effectiveness of the proposal motivates the application of this novel evolutionary framework for solving other combinatorial optimization problems.

Neural correlates of implicit and explicit combinatorial semantic processing

PubMed Central

Graves, William W.; Binder, Jeffrey R.; Desai, Rutvik H.; Conant, Lisa L.; Seidenberg, Mark S.

2010-01-01

Language consists of sequences of words, but comprehending phrases involves more than concatenating meanings: A boat house is a shelter for boats, whereas a summer house is a house used during summer, and a ghost house is typically uninhabited. Little is known about the brain bases of combinatorial semantic processes. We performed two fMRI experiments using familiar, highly meaningful phrases (LAKE HOUSE) and unfamiliar phrases with minimal meaning created by reversing the word order of the familiar items (HOUSE LAKE). The first experiment used a 1-back matching task to assess implicit semantic processing, and the second used a classification task to engage explicit semantic processing. These conditions required processing of the same words, but with more effective combinatorial processing in the meaningful condition. The contrast of meaningful versus reversed phrases revealed activation primarily during the classification task, to a greater extent in the right hemisphere, including right angular gyrus, dorsomedial prefrontal cortex, and bilateral posterior cingulate/precuneus, areas previously implicated in semantic processing. Positive correlations of fMRI signal with lexical (word-level) frequency occurred exclusively with the 1-back task and to a greater spatial extent on the left, including left posterior middle temporal gyrus and bilateral parahippocampus. These results reveal strong effects of task demands on engagement of lexical versus combinatorial processing and suggest a hemispheric dissociation between these levels of semantic representation. PMID:20600969

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks.

PubMed

Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing

2017-07-19

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.

Emergent latent symbol systems in recurrent neural networks

NASA Astrophysics Data System (ADS)

Monner, Derek; Reggia, James A.

2012-12-01

Fodor and Pylyshyn [(1988). Connectionism and cognitive architecture: A critical analysis. Cognition, 28(1-2), 3-71] famously argued that neural networks cannot behave systematically short of implementing a combinatorial symbol system. A recent response from Frank et al. [(2009). Connectionist semantic systematicity. Cognition, 110(3), 358-379] claimed to have trained a neural network to behave systematically without implementing a symbol system and without any in-built predisposition towards combinatorial representations. We believe systems like theirs may in fact implement a symbol system on a deeper and more interesting level: one where the symbols are latent - not visible at the level of network structure. In order to illustrate this possibility, we demonstrate our own recurrent neural network that learns to understand sentence-level language in terms of a scene. We demonstrate our model's learned understanding by testing it on novel sentences and scenes. By paring down our model into an architecturally minimal version, we demonstrate how it supports combinatorial computation over distributed representations by using the associative memory operations of Vector Symbolic Architectures. Knowledge of the model's memory scheme gives us tools to explain its errors and construct superior future models. We show how the model designs and manipulates a latent symbol system in which the combinatorial symbols are patterns of activation distributed across the layers of a neural network, instantiating a hybrid of classical symbolic and connectionist representations that combines advantages of both.

Combinatorial Pharmacophore-Based 3D-QSAR Analysis and Virtual Screening of FGFR1 Inhibitors

PubMed Central

Zhou, Nannan; Xu, Yuan; Liu, Xian; Wang, Yulan; Peng, Jianlong; Luo, Xiaomin; Zheng, Mingyue; Chen, Kaixian; Jiang, Hualiang

2015-01-01

The fibroblast growth factor/fibroblast growth factor receptor (FGF/FGFR) signaling pathway plays crucial roles in cell proliferation, angiogenesis, migration, and survival. Aberration in FGFRs correlates with several malignancies and disorders. FGFRs have proved to be attractive targets for therapeutic intervention in cancer, and it is of high interest to find FGFR inhibitors with novel scaffolds. In this study, a combinatorial three-dimensional quantitative structure-activity relationship (3D-QSAR) model was developed based on previously reported FGFR1 inhibitors with diverse structural skeletons. This model was evaluated for its prediction performance on a diverse test set containing 232 FGFR inhibitors, and it yielded a SD value of 0.75 pIC50 units from measured inhibition affinities and a Pearson’s correlation coefficient R2 of 0.53. This result suggests that the combinatorial 3D-QSAR model could be used to search for new FGFR1 hit structures and predict their potential activity. To further evaluate the performance of the model, a decoy set validation was used to measure the efficiency of the model by calculating EF (enrichment factor). Based on the combinatorial pharmacophore model, a virtual screening against SPECS database was performed. Nineteen novel active compounds were successfully identified, which provide new chemical starting points for further structural optimization of FGFR1 inhibitors. PMID:26110383

Combinatorial treatments enhance recovery following facial nerve crush.

PubMed

Sharma, Nijee; Moeller, Carl W; Marzo, Sam J; Jones, Kathryn J; Foecking, Eileen M

2010-08-01

To investigate the effects of various combinatorial treatments, consisting of a tapering dose of prednisone (P), a brief period of nerve electrical stimulation (ES), and systemic testosterone propionate (TP) on improving functional recovery following an intratemporal facial nerve crush injury. Prospective, controlled animal study. After a right intratemporal facial nerve crush, adult male Sprague-Dawley rats were divided into the following eight treatment groups: 1) no treatment, 2) P only, 3) ES only, 4) ES + P, 5) TP only, 6) TP + P, 7) ES + TP, and 8) ES + TP + P. For each group n = 4-8. Recovery of the eyeblink reflex and vibrissae orientation and movement were assessed. Changes in peak amplitude and latency of evoked response, in response to facial nerve stimulation, was also recorded weekly. : Brief ES of the proximal nerve stump most effectively accelerated the initiation of functional recovery. Also, ES or TP treatments enhanced recovery of some functional parameters more than P treatment. When administered alone, none of the three treatments improved recovery of complete facial function. Only the combinatorial treatment of ES + TP, regardless of the presence of P, accelerated complete functional recovery and return of normal motor nerve conduction. Our findings suggest that a combinatorial treatment strategy of using brief ES and TP together promises to be an effective therapeutic intervention for promoting regeneration following facial nerve injury. Administration of P neither augments nor hinders recovery.

A novel computational model to probe visual search deficits during motor performance

PubMed Central

Singh, Tarkeshwar; Fridriksson, Julius; Perry, Christopher M.; Tryon, Sarah C.; Ross, Angela; Fritz, Stacy

2016-01-01

Successful execution of many motor skills relies on well-organized visual search (voluntary eye movements that actively scan the environment for task-relevant information). Although impairments of visual search that result from brain injuries are linked to diminished motor performance, the neural processes that guide visual search within this context remain largely unknown. The first objective of this study was to examine how visual search in healthy adults and stroke survivors is used to guide hand movements during the Trail Making Test (TMT), a neuropsychological task that is a strong predictor of visuomotor and cognitive deficits. Our second objective was to develop a novel computational model to investigate combinatorial interactions between three underlying processes of visual search (spatial planning, working memory, and peripheral visual processing). We predicted that stroke survivors would exhibit deficits in integrating the three underlying processes, resulting in deteriorated overall task performance. We found that normal TMT performance is associated with patterns of visual search that primarily rely on spatial planning and/or working memory (but not peripheral visual processing). Our computational model suggested that abnormal TMT performance following stroke is associated with impairments of visual search that are characterized by deficits integrating spatial planning and working memory. This innovative methodology provides a novel framework for studying how the neural processes underlying visual search interact combinatorially to guide motor performance. NEW & NOTEWORTHY Visual search has traditionally been studied in cognitive and perceptual paradigms, but little is known about how it contributes to visuomotor performance. We have developed a novel computational model to examine how three underlying processes of visual search (spatial planning, working memory, and peripheral visual processing) contribute to visual search during a visuomotor task. We show that deficits integrating spatial planning and working memory underlie abnormal performance in stroke survivors with frontoparietal damage. PMID:27733596

Minimizing distortion and internal forces in truss structures by simulated annealing

NASA Technical Reports Server (NTRS)

Kincaid, Rex K.

1989-01-01

Inaccuracies in the length of members and the diameters of joints of large truss reflector backup structures may produce unacceptable levels of surface distortion and member forces. However, if the member lengths and joint diameters can be measured accurately it is possible to configure the members and joints so that root-mean-square (rms) surface error and/or rms member forces is minimized. Following Greene and Haftka (1989) it is assumed that the force vector f is linearly proportional to the member length errors e(sub M) of dimension NMEMB (the number of members) and joint errors e(sub J) of dimension NJOINT (the number of joints), and that the best-fit displacement vector d is a linear function of f. Let NNODES denote the number of positions on the surface of the truss where error influences are measured. The solution of the problem is discussed. To classify, this problem was compared to a similar combinatorial optimization problem. In particular, when only the member length errors are considered, minimizing d(sup 2)(sub rms) is equivalent to the quadratic assignment problem. The quadratic assignment problem is a well known NP-complete problem in operations research literature. Hence minimizing d(sup 2)(sub rms) is is also an NP-complete problem. The focus of the research is the development of a simulated annealing algorithm to reduce d(sup 2)(sub rms). The plausibility of this technique is its recent success on a variety of NP-complete combinatorial optimization problems including the quadratic assignment problem. A physical analogy for simulated annealing is the way liquids freeze and crystallize. All computational experiments were done on a MicroVAX. The two interchange heuristic is very fast but produces widely varying results. The two and three interchange heuristic provides less variability in the final objective function values but runs much more slowly. Simulated annealing produced the best objective function values for every starting configuration and was faster than the two and three interchange heuristic.

Combinatorial screening of halide perovskite thin films and solar cells by mask-defined IR laser molecular beam epitaxy

NASA Astrophysics Data System (ADS)

Kawashima, Kazuhiro; Okamoto, Yuji; Annayev, Orazmuhammet; Toyokura, Nobuo; Takahashi, Ryota; Lippmaa, Mikk; Itaka, Kenji; Suzuki, Yoshikazu; Matsuki, Nobuyuki; Koinuma, Hideomi

2017-12-01

As an extension of combinatorial molecular layer epitaxy via ablation of perovskite oxides by a pulsed excimer laser, we have developed a laser molecular beam epitaxy (MBE) system for parallel integration of nano-scaled thin films of organic-inorganic hybrid materials. A pulsed infrared (IR) semiconductor laser was adopted for thermal evaporation of organic halide (A-site: CH3NH3I) and inorganic halide (B-site: PbI2) powder targets to deposit repeated A/B bilayer films where the thickness of each layer was controlled on molecular layer scale by programming the evaporation IR laser pulse number, length, or power. The layer thickness was monitored with an in situ quartz crystal microbalance and calibrated against ex situ stylus profilometer measurements. A computer-controlled movable mask system enabled the deposition of combinatorial thin film libraries, where each library contains a vertically homogeneous film with spatially programmable A- and B-layer thicknesses. On the composition gradient film, a hole transport Spiro-OMeTAD layer was spin-coated and dried followed by the vacuum evaporation of Ag electrodes to form the solar cell. The preliminary cell performance was evaluated by measuring I-V characteristics at seven different positions on the 12.5 mm × 12.5 mm combinatorial library sample with seven 2 mm × 4 mm slits under a solar simulator irradiation. The combinatorial solar cell library clearly demonstrated that the energy conversion efficiency sharply changes from nearly zero to 10.2% as a function of the illumination area in the library. The exploration of deposition parameters for obtaining optimum performance could thus be greatly accelerated. Since the thickness ratio of PbI2 and CH3NH3I can be freely chosen along the shadow mask movement, these experiments show the potential of this system for high-throughput screening of optimum chemical composition in the binary film library and application to halide perovskite solar cell.

The combinatorial control of alternative splicing in C. elegans

PubMed Central

2017-01-01

Normal development requires the right splice variants to be made in the right tissues at the right time. The core splicing machinery is engaged in all splicing events, but which precise splice variant is made requires the choice between alternative splice sites—for this to occur, a set of splicing factors (SFs) must recognize and bind to short RNA motifs in the pre-mRNA. In C. elegans, there is known to be extensive variation in splicing patterns across development, but little is known about the targets of each SF or how multiple SFs combine to regulate splicing. Here we combine RNA-seq with in vitro binding assays to study how 4 different C. elegans SFs, ASD-1, FOX-1, MEC-8, and EXC-7, regulate splicing. The 4 SFs chosen all have well-characterised biology and well-studied loss-of-function genetic alleles, and all contain RRM domains. Intriguingly, while the SFs we examined have varied roles in C. elegans development, they show an unexpectedly high overlap in their targets. We also find that binding sites for these SFs occur on the same pre-mRNAs more frequently than expected suggesting extensive combinatorial control of splicing. We confirm that regulation of splicing by multiple SFs is often combinatorial and show that this is functionally significant. We also find that SFs appear to combine to affect splicing in two modes—they either bind in close proximity within the same intron or they appear to bind to separate regions of the intron in a conserved order. Finally, we find that the genes whose splicing are regulated by multiple SFs are highly enriched for genes involved in the cytoskeleton and in ion channels that are key for neurotransmission. Together, this shows that specific classes of genes have complex combinatorial regulation of splicing and that this combinatorial regulation is critical for normal development to occur. PMID:29121637

ChIP-less analysis of chromatin states.

PubMed

Su, Zhangli; Boersma, Melissa D; Lee, Jin-Hee; Oliver, Samuel S; Liu, Shichong; Garcia, Benjamin A; Denu, John M

2014-01-01

Histone post-translational modifications (PTMs) are key epigenetic regulators in chromatin-based processes. Increasing evidence suggests that vast combinations of PTMs exist within chromatin histones. These complex patterns, rather than individual PTMs, are thought to define functional chromatin states. However, the ability to interrogate combinatorial histone PTM patterns at the nucleosome level has been limited by the lack of direct molecular tools. Here we demonstrate an efficient, quantitative, antibody-free, chromatin immunoprecipitation-less (ChIP-less) method for interrogating diverse epigenetic states. At the heart of the workflow are recombinant chromatin reader domains, which target distinct chromatin states with combinatorial PTM patterns. Utilizing a newly designed combinatorial histone peptide microarray, we showed that three reader domains (ATRX-ADD, ING2-PHD and AIRE-PHD) displayed greater specificity towards combinatorial PTM patterns than corresponding commercial histone antibodies. Such specific recognitions were employed to develop a chromatin reader-based affinity enrichment platform (matrix-assisted reader chromatin capture, or MARCC). We successfully applied the reader-based platform to capture unique chromatin states, which were quantitatively profiled by mass spectrometry to reveal interconnections between nucleosomal histone PTMs. Specifically, a highly enriched signature that harbored H3K4me0, H3K9me2/3, H3K79me0 and H4K20me2/3 within the same nucleosome was identified from chromatin enriched by ATRX-ADD. This newly reported PTM combination was enriched in heterochromatin, as revealed by the associated DNA. Our results suggest the broad utility of recombinant reader domains as an enrichment tool specific to combinatorial PTM patterns, which are difficult to probe directly by antibody-based approaches. The reader affinity platform is compatible with several downstream analyses to investigate the physical coexistence of nucleosomal PTM states associated with specific genomic loci. Collectively, the reader-based workflow will greatly facilitate our understanding of how distinct chromatin states and reader domains function in gene regulatory mechanisms.

Novel Modeling of Combinatorial miRNA Targeting Identifies SNP with Potential Role in Bone Density

PubMed Central

Coronnello, Claudia; Hartmaier, Ryan; Arora, Arshi; Huleihel, Luai; Pandit, Kusum V.; Bais, Abha S.; Butterworth, Michael; Kaminski, Naftali; Stormo, Gary D.; Oesterreich, Steffi; Benos, Panayiotis V.

2012-01-01

MicroRNAs (miRNAs) are post-transcriptional regulators that bind to their target mRNAs through base complementarity. Predicting miRNA targets is a challenging task and various studies showed that existing algorithms suffer from high number of false predictions and low to moderate overlap in their predictions. Until recently, very few algorithms considered the dynamic nature of the interactions, including the effect of less specific interactions, the miRNA expression level, and the effect of combinatorial miRNA binding. Addressing these issues can result in a more accurate miRNA:mRNA modeling with many applications, including efficient miRNA-related SNP evaluation. We present a novel thermodynamic model based on the Fermi-Dirac equation that incorporates miRNA expression in the prediction of target occupancy and we show that it improves the performance of two popular single miRNA target finders. Modeling combinatorial miRNA targeting is a natural extension of this model. Two other algorithms show improved prediction efficiency when combinatorial binding models were considered. ComiR (Combinatorial miRNA targeting), a novel algorithm we developed, incorporates the improved predictions of the four target finders into a single probabilistic score using ensemble learning. Combining target scores of multiple miRNAs using ComiR improves predictions over the naïve method for target combination. ComiR scoring scheme can be used for identification of SNPs affecting miRNA binding. As proof of principle, ComiR identified rs17737058 as disruptive to the miR-488-5p:NCOA1 interaction, which we confirmed in vitro. We also found rs17737058 to be significantly associated with decreased bone mineral density (BMD) in two independent cohorts indicating that the miR-488-5p/NCOA1 regulatory axis is likely critical in maintaining BMD in women. With increasing availability of comprehensive high-throughput datasets from patients ComiR is expected to become an essential tool for miRNA-related studies. PMID:23284279

A Combinatorial Platform for the Optimization of Peptidomimetic Methyl-Lysine Reader Antagonists

NASA Astrophysics Data System (ADS)

Barnash, Kimberly D.

Post-translational modification of histone N-terminal tails mediates chromatin compaction and, consequently, DNA replication, transcription, and repair. While numerous post-translational modifications decorate histone tails, lysine methylation is an abundant mark important for both gene activation and repression. Methyl-lysine (Kme) readers function through binding mono-, di-, or trimethyl-lysine. Chemical intervention of Kme readers faces numerous challenges due to the broad surface-groove interactions between readers and their cognate histone peptides; yet, the increasing interest in understanding chromatin-modifying complexes suggests tractable lead compounds for Kme readers are critical for elucidating the mechanisms of chromatin dysregulation in disease states and validating the druggability of these domains and complexes. The successful discovery of a peptide-derived chemical probe, UNC3866, for the Polycomb repressive complex 1 (PRC1) chromodomain Kme readers has proven the potential for selective peptidomimetic inhibition of reader function. Unfortunately, the systematic modification of peptides-to-peptidomimetics is a costly and inefficient strategy for target-class hit discovery against Kme readers. Through the exploration of biased chemical space via combinatorial on-bead libraries, we have developed two concurrent methodologies for Kme reader chemical probe discovery. We employ biased peptide combinatorial libraries as a hit discovery strategy with subsequent optimization via iterative targeted libraries. Peptide-to-peptidomimetic optimization through targeted library design was applied based on structure-guided library design around the interaction of the endogenous peptide ligand with three target Kme readers. Efforts targeting the WD40 reader EED led to the discovery of the 3-mer peptidomimetic ligand UNC5115 while combinatorial repurposing of UNC3866 for off-target chromodomains resulted in the discovery of UNC4991, a CDYL/2-selective ligand, and UNC4848, a MPP8 and CDYL/2 ligand. Ultimately, our efforts demonstrate the generalizability of a peptidomimetic combinatorial platform for the optimization of Kme reader ligands in a target class manner.

Combinatorial screening of halide perovskite thin films and solar cells by mask-defined IR laser molecular beam epitaxy.

PubMed

Kawashima, Kazuhiro; Okamoto, Yuji; Annayev, Orazmuhammet; Toyokura, Nobuo; Takahashi, Ryota; Lippmaa, Mikk; Itaka, Kenji; Suzuki, Yoshikazu; Matsuki, Nobuyuki; Koinuma, Hideomi

2017-01-01

As an extension of combinatorial molecular layer epitaxy via ablation of perovskite oxides by a pulsed excimer laser, we have developed a laser molecular beam epitaxy (MBE) system for parallel integration of nano-scaled thin films of organic-inorganic hybrid materials. A pulsed infrared (IR) semiconductor laser was adopted for thermal evaporation of organic halide (A-site: CH 3 NH 3 I) and inorganic halide (B-site: PbI 2 ) powder targets to deposit repeated A/B bilayer films where the thickness of each layer was controlled on molecular layer scale by programming the evaporation IR laser pulse number, length, or power. The layer thickness was monitored with an in situ quartz crystal microbalance and calibrated against ex situ stylus profilometer measurements. A computer-controlled movable mask system enabled the deposition of combinatorial thin film libraries, where each library contains a vertically homogeneous film with spatially programmable A- and B-layer thicknesses. On the composition gradient film, a hole transport Spiro-OMeTAD layer was spin-coated and dried followed by the vacuum evaporation of Ag electrodes to form the solar cell. The preliminary cell performance was evaluated by measuring I - V characteristics at seven different positions on the 12.5 mm × 12.5 mm combinatorial library sample with seven 2 mm × 4 mm slits under a solar simulator irradiation. The combinatorial solar cell library clearly demonstrated that the energy conversion efficiency sharply changes from nearly zero to 10.2% as a function of the illumination area in the library. The exploration of deposition parameters for obtaining optimum performance could thus be greatly accelerated. Since the thickness ratio of PbI 2 and CH 3 NH 3 I can be freely chosen along the shadow mask movement, these experiments show the potential of this system for high-throughput screening of optimum chemical composition in the binary film library and application to halide perovskite solar cell.

Two projects in theoretical neuroscience: A convolution-based metric for neural membrane potentials and a combinatorial connectionist semantic network method

NASA Astrophysics Data System (ADS)

Evans, Garrett Nolan

In this work, I present two projects that both contribute to the aim of discovering how intelligence manifests in the brain. The first project is a method for analyzing recorded neural signals, which takes the form of a convolution-based metric on neural membrane potential recordings. Relying only on integral and algebraic operations, the metric compares the timing and number of spikes within recordings as well as the recordings' subthreshold features: summarizing differences in these with a single "distance" between the recordings. Like van Rossum's (2001) metric for spike trains, the metric is based on a convolution operation that it performs on the input data. The kernel used for the convolution is carefully chosen such that it produces a desirable frequency space response and, unlike van Rossum's kernel, causes the metric to be first order both in differences between nearby spike times and in differences between same-time membrane potential values: an important trait. The second project is a combinatorial syntax method for connectionist semantic network encoding. Combinatorial syntax has been a point on which those who support a symbol-processing view of intelligent processing and those who favor a connectionist view have had difficulty seeing eye-to-eye. Symbol-processing theorists have persuasively argued that combinatorial syntax is necessary for certain intelligent mental operations, such as reasoning by analogy. Connectionists have focused on the versatility and adaptability offered by self-organizing networks of simple processing units. With this project, I show that there is a way to reconcile the two perspectives and to ascribe a combinatorial syntax to a connectionist network. The critical principle is to interpret nodes, or units, in the connectionist network as bound integrations of the interpretations for nodes that they share links with. Nodes need not correspond exactly to neurons and may correspond instead to distributed sets, or assemblies, of neurons.

Co-LncRNA: investigating the lncRNA combinatorial effects in GO annotations and KEGG pathways based on human RNA-Seq data.

PubMed

Zhao, Zheng; Bai, Jing; Wu, Aiwei; Wang, Yuan; Zhang, Jinwen; Wang, Zishan; Li, Yongsheng; Xu, Juan; Li, Xia

2015-01-01

Long non-coding RNAs (lncRNAs) are emerging as key regulators of diverse biological processes and diseases. However, the combinatorial effects of these molecules in a specific biological function are poorly understood. Identifying co-expressed protein-coding genes of lncRNAs would provide ample insight into lncRNA functions. To facilitate such an effort, we have developed Co-LncRNA, which is a web-based computational tool that allows users to identify GO annotations and KEGG pathways that may be affected by co-expressed protein-coding genes of a single or multiple lncRNAs. LncRNA co-expressed protein-coding genes were first identified in publicly available human RNA-Seq datasets, including 241 datasets across 6560 total individuals representing 28 tissue types/cell lines. Then, the lncRNA combinatorial effects in a given GO annotations or KEGG pathways are taken into account by the simultaneous analysis of multiple lncRNAs in user-selected individual or multiple datasets, which is realized by enrichment analysis. In addition, this software provides a graphical overview of pathways that are modulated by lncRNAs, as well as a specific tool to display the relevant networks between lncRNAs and their co-expressed protein-coding genes. Co-LncRNA also supports users in uploading their own lncRNA and protein-coding gene expression profiles to investigate the lncRNA combinatorial effects. It will be continuously updated with more human RNA-Seq datasets on an annual basis. Taken together, Co-LncRNA provides a web-based application for investigating lncRNA combinatorial effects, which could shed light on their biological roles and could be a valuable resource for this community. Database URL: http://www.bio-bigdata.com/Co-LncRNA/. © The Author(s) 2015. Published by Oxford University Press.

Priming of the Cells: Hypoxic Preconditioning for Stem Cell Therapy

PubMed Central

Wei, Zheng Z; Zhu, Yan-Bing; Zhang, James Y; McCrary, Myles R; Wang, Song; Zhang, Yong-Bo; Yu, Shan-Ping; Wei, Ling

2017-01-01

Objective: Stem cell-based therapies are promising in regenerative medicine for protecting and repairing damaged brain tissues after injury or in the context of chronic diseases. Hypoxia can induce physiological and pathological responses. A hypoxic insult might act as a double-edged sword, it induces cell death and brain damage, but on the other hand, sublethal hypoxia can trigger an adaptation response called hypoxic preconditioning or hypoxic tolerance that is of immense importance for the survival of cells and tissues. Data Sources: This review was based on articles published in PubMed databases up to August 16, 2017, with the following keywords: “stem cells,” “hypoxic preconditioning,” “ischemic preconditioning,” and “cell transplantation.” Study Selection: Original articles and critical reviews on the topics were selected. Results: Hypoxic preconditioning has been investigated as a primary endogenous protective mechanism and possible treatment against ischemic injuries. Many cellular and molecular mechanisms underlying the protective effects of hypoxic preconditioning have been identified. Conclusions: In cell transplantation therapy, hypoxic pretreatment of stem cells and neural progenitors markedly increases the survival and regenerative capabilities of these cells in the host environment, leading to enhanced therapeutic effects in various disease models. Regenerative treatments can mobilize endogenous stem cells for neurogenesis and angiogenesis in the adult brain. Furthermore, transplantation of stem cells/neural progenitors achieves therapeutic benefits via cell replacement and/or increased trophic support. Combinatorial approaches of cell-based therapy with additional strategies such as neuroprotective protocols, anti-inflammatory treatment, and rehabilitation therapy can significantly improve therapeutic benefits. In this review, we will discuss the recent progress regarding cell types and applications in regenerative medicine as well as future applications. PMID:28937044

In vitro synergistic effect of Hibiscus sabdariffa aqueous extract in combination with standard antibiotics against Helicobacter pylori clinical isolates.

PubMed

Hassan, Sherif T S; Berchová, Kateřina; Majerová, Michaela; Pokorná, Marie; Švajdlenka, Emil

2016-09-01

Context The increasing problem of drug-resistant strains has led to the failure of current treatment regimens of Helicobacter pylori (HP) infection. Recently, a new treatment strategy has been developed to overcome the problem by using natural products in combination with antibiotics to enhance the treatment efficacy. Objective The antimicrobial combinatory effect of the aqueous extract of Hibiscus sabdariffa L. (Malvaceae) (AEHS) with antibiotics (clarithromycin, CLA; amoxicillin, AMX; metronidazole, MTZ) has been evaluated in vitro against HP strains. Materials and methods Hibiscus calyces (35 g) were brewed in 250 mL of boiled water for 30 min, and minimum inhibitory concentrations (MICs) were determined by agar dilution method. The checkerboard assay was used to evaluate the antimicrobial combinatory effect according to the sum of fractional inhibitory concentration (∑FIC) indices. Results In this study, AEHS exerted remarkable bacteriostatic effect against all HP strains tested with MICs values ranging from 9.18 to 16.68 μg/mL. Synergy effect of AEHS with CLA or MTZ was obtained against four of seven HP strains tested with ∑FIC ranging from 0.21 to 0.39. The additive effect of AEHS with AMX was obtained against five of seven HP strains tested with ∑FIC ranging from 0.61 to 0.91. Conclusion This study presents AEHS as a potent therapeutic candidate alone, or in combination with antibiotics for the treatment of HP infection.

Applications of Derandomization Theory in Coding

NASA Astrophysics Data System (ADS)

Cheraghchi, Mahdi

2011-07-01

Randomized techniques play a fundamental role in theoretical computer science and discrete mathematics, in particular for the design of efficient algorithms and construction of combinatorial objects. The basic goal in derandomization theory is to eliminate or reduce the need for randomness in such randomized constructions. In this thesis, we explore some applications of the fundamental notions in derandomization theory to problems outside the core of theoretical computer science, and in particular, certain problems related to coding theory. First, we consider the wiretap channel problem which involves a communication system in which an intruder can eavesdrop a limited portion of the transmissions, and construct efficient and information-theoretically optimal communication protocols for this model. Then we consider the combinatorial group testing problem. In this classical problem, one aims to determine a set of defective items within a large population by asking a number of queries, where each query reveals whether a defective item is present within a specified group of items. We use randomness condensers to explicitly construct optimal, or nearly optimal, group testing schemes for a setting where the query outcomes can be highly unreliable, as well as the threshold model where a query returns positive if the number of defectives pass a certain threshold. Finally, we design ensembles of error-correcting codes that achieve the information-theoretic capacity of a large class of communication channels, and then use the obtained ensembles for construction of explicit capacity achieving codes. [This is a shortened version of the actual abstract in the thesis.

MASM: a market architecture for sensor management in distributed sensor networks

NASA Astrophysics Data System (ADS)

Viswanath, Avasarala; Mullen, Tracy; Hall, David; Garga, Amulya

2005-03-01

Rapid developments in sensor technology and its applications have energized research efforts towards devising a firm theoretical foundation for sensor management. Ubiquitous sensing, wide bandwidth communications and distributed processing provide both opportunities and challenges for sensor and process control and optimization. Traditional optimization techniques do not have the ability to simultaneously consider the wildly non-commensurate measures involved in sensor management in a single optimization routine. Market-oriented programming provides a valuable and principled paradigm to designing systems to solve this dynamic and distributed resource allocation problem. We have modeled the sensor management scenario as a competitive market, wherein the sensor manager holds a combinatorial auction to sell the various items produced by the sensors and the communication channels. However, standard auction mechanisms have been found not to be directly applicable to the sensor management domain. For this purpose, we have developed a specialized market architecture MASM (Market architecture for Sensor Management). In MASM, the mission manager is responsible for deciding task allocations to the consumers and their corresponding budgets and the sensor manager is responsible for resource allocation to the various consumers. In addition to having a modified combinatorial winner determination algorithm, MASM has specialized sensor network modules that address commensurability issues between consumers and producers in the sensor network domain. A preliminary multi-sensor, multi-target simulation environment has been implemented to test the performance of the proposed system. MASM outperformed the information theoretic sensor manager in meeting the mission objectives in the simulation experiments.

A Combinatorial Geometry Target Description of the High Mobility Multipurpose Wheeled Vehicle (HMMWV)

DTIC Science & Technology

1985-10-01

NOTE3 1W. KFY OORDS (Continwo =n reverse aide If necesesar aid ldwttlfy by" block ntmber) •JW7 Regions, COM-EOM Region Ident• fication GIFT Material...technique of mobna.tcri• i Geometr- (Com-Geom). The Com-Gem data is used as input to the Geometric Inf• •cation for Targets ( GIFT ) computer code to... GIFT ) 2 3 computer code. This report documents the combinatorial geometry (Com-Geom) target description data which is the input data for the GIFT code

Combinatorial interpretation of Haldane-Wu fractional exclusion statistics.

PubMed

Aringazin, A K; Mazhitov, M I

2002-08-01

Assuming that the maximal allowed number of identical particles in a state is an integer parameter, q, we derive the statistical weight and analyze the associated equation that defines the statistical distribution. The derived distribution covers Fermi-Dirac and Bose-Einstein ones in the particular cases q=1 and q--> infinity (n(i)/q-->1), respectively. We show that the derived statistical weight provides a natural combinatorial interpretation of Haldane-Wu fractional exclusion statistics, and present exact solutions of the distribution equation.

Research on parallel combinatory spread spectrum communication system with double information matching

NASA Astrophysics Data System (ADS)

Xue, Wei; Wang, Qi; Wang, Tianyu

2018-04-01

This paper presents an improved parallel combinatory spread spectrum (PC/SS) communication system with the method of double information matching (DIM). Compared with conventional PC/SS system, the new model inherits the advantage of high transmission speed, large information capacity and high security. Besides, the problem traditional system will face is the high bit error rate (BER) and since its data-sequence mapping algorithm. Hence the new model presented shows lower BER and higher efficiency by its optimization of mapping algorithm.

Mapping protein-protein interactions with phage-displayed combinatorial peptide libraries.

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

Kay, B. K.; Castagnoli, L.; Biosciences Division

This unit describes the process and analysis of affinity selecting bacteriophage M13 from libraries displaying combinatorial peptides fused to either a minor or major capsid protein. Direct affinity selection uses target protein bound to a microtiter plate followed by purification of selected phage by ELISA. Alternatively, there is a bead-based affinity selection method. These methods allow one to readily isolate peptide ligands that bind to a protein target of interest and use the consensus sequence to search proteomic databases for putative interacting proteins.

Distributed Combinatorial Optimization Using Privacy on Mobile Phones

NASA Astrophysics Data System (ADS)

Ono, Satoshi; Katayama, Kimihiro; Nakayama, Shigeru

This paper proposes a method for distributed combinatorial optimization which uses mobile phones as computers. In the proposed method, an ordinary computer generates solution candidates and mobile phones evaluates them by referring privacy — private information and preferences. Users therefore does not have to send their privacy to any other computers and does not have to refrain from inputting their preferences. They therefore can obtain satisfactory solution. Experimental results have showed the proposed method solved room assignment problems without sending users' privacy to a server.

Combinatorial FSK modulation for power-efficient high-rate communications

NASA Technical Reports Server (NTRS)

Wagner, Paul K.; Budinger, James M.; Vanderaar, Mark J.

1991-01-01

Deep-space and satellite communications systems must be capable of conveying high-rate data accurately with low transmitter power, often through dispersive channels. A class of noncoherent Combinatorial Frequency Shift Keying (CFSK) modulation schemes is investigated which address these needs. The bit error rate performance of this class of modulation formats is analyzed and compared to the more traditional modulation types. Candidate modulator, demodulator, and digital signal processing (DSP) hardware structures are examined in detail. System-level issues are also discussed.

Statistical Mechanics of Combinatorial Auctions

NASA Astrophysics Data System (ADS)

Galla, Tobias; Leone, Michele; Marsili, Matteo; Sellitto, Mauro; Weigt, Martin; Zecchina, Riccardo

2006-09-01

Combinatorial auctions are formulated as frustrated lattice gases on sparse random graphs, allowing the determination of the optimal revenue by methods of statistical physics. Transitions between computationally easy and hard regimes are found and interpreted in terms of the geometric structure of the space of solutions. We introduce an iterative algorithm to solve intermediate and large instances, and discuss competing states of optimal revenue and maximal number of satisfied bidders. The algorithm can be generalized to the hard phase and to more sophisticated auction protocols.

Aerospace applications of integer and combinatorial optimization

NASA Technical Reports Server (NTRS)

Padula, S. L.; Kincaid, R. K.

1995-01-01

Research supported by NASA Langley Research Center includes many applications of aerospace design optimization and is conducted by teams of applied mathematicians and aerospace engineers. This paper investigates the benefits from this combined expertise in solving combinatorial optimization problems. Applications range from the design of large space antennas to interior noise control. A typical problem, for example, seeks the optimal locations for vibration-damping devices on a large space structure and is expressed as a mixed/integer linear programming problem with more than 1500 design variables.

Linkage of Recognition and Replication Functions by Assembling Combinatorial Antibody Fab Libraries Along Phage Surfaces

NASA Astrophysics Data System (ADS)

Kang, Angray S.; Barbas, Carlos F.; Janda, Kim D.; Benkovic, Stephen J.; Lerner, Richard A.

1991-05-01

We describe a method based on a phagemid vector with helper phage rescue for the construction and rapid analysis of combinatorial antibody Fab libraries. This approach should allow the generation and selection of many monoclonal antibodies. Antibody genes are expressed in concert with phage morphogenesis, thereby allowing incorporation of functional Fab molecules along the surface of filamentous phage. The power of the method depends upon the linkage of recognition and replication functions and is not limited to antibody molecules.

Sensibilization of polymer/fullerene photovoltaic cells using Zinc Phtalocyanine studied by combinatorial technique

NASA Astrophysics Data System (ADS)

Godovsky, D.; Chen, L.; Petterson, L.; Inganäs, O.

2000-11-01

The influence of Zinc Phtalocyanine admixture to fullerene layers on top of PTOPT to the photovoltaic cells performance was studied. In order to investigate all the possible combinations of ZnPc and C60 the combinatorial technique was developed consisting in thermal co-evaporation of ZnPc and C60 from two different boats. The significant increase in solar cells photocurrent was observed, coming from ZnPc absorbance bands, especially for the layers containing 1:1 molar ratio of the components.

SLIDER: a generic metaheuristic for the discovery of correlated motifs in protein-protein interaction networks.

PubMed

Boyen, Peter; Van Dyck, Dries; Neven, Frank; van Ham, Roeland C H J; van Dijk, Aalt D J

2011-01-01

Correlated motif mining (cmm) is the problem of finding overrepresented pairs of patterns, called motifs, in sequences of interacting proteins. Algorithmic solutions for cmm thereby provide a computational method for predicting binding sites for protein interaction. In this paper, we adopt a motif-driven approach where the support of candidate motif pairs is evaluated in the network. We experimentally establish the superiority of the Chi-square-based support measure over other support measures. Furthermore, we obtain that cmm is an np-hard problem for a large class of support measures (including Chi-square) and reformulate the search for correlated motifs as a combinatorial optimization problem. We then present the generic metaheuristic slider which uses steepest ascent with a neighborhood function based on sliding motifs and employs the Chi-square-based support measure. We show that slider outperforms existing motif-driven cmm methods and scales to large protein-protein interaction networks. The slider-implementation and the data used in the experiments are available on http://bioinformatics.uhasselt.be.

Bifurcation-based adiabatic quantum computation with a nonlinear oscillator network

PubMed Central

Goto, Hayato

2016-01-01

The dynamics of nonlinear systems qualitatively change depending on their parameters, which is called bifurcation. A quantum-mechanical nonlinear oscillator can yield a quantum superposition of two oscillation states, known as a Schrödinger cat state, via quantum adiabatic evolution through its bifurcation point. Here we propose a quantum computer comprising such quantum nonlinear oscillators, instead of quantum bits, to solve hard combinatorial optimization problems. The nonlinear oscillator network finds optimal solutions via quantum adiabatic evolution, where nonlinear terms are increased slowly, in contrast to conventional adiabatic quantum computation or quantum annealing, where quantum fluctuation terms are decreased slowly. As a result of numerical simulations, it is concluded that quantum superposition and quantum fluctuation work effectively to find optimal solutions. It is also notable that the present computer is analogous to neural computers, which are also networks of nonlinear components. Thus, the present scheme will open new possibilities for quantum computation, nonlinear science, and artificial intelligence. PMID:26899997

APG: an Active Protein-Gene network model to quantify regulatory signals in complex biological systems.

PubMed

Wang, Jiguang; Sun, Yidan; Zheng, Si; Zhang, Xiang-Sun; Zhou, Huarong; Chen, Luonan

2013-01-01

Synergistic interactions among transcription factors (TFs) and their cofactors collectively determine gene expression in complex biological systems. In this work, we develop a novel graphical model, called Active Protein-Gene (APG) network model, to quantify regulatory signals of transcription in complex biomolecular networks through integrating both TF upstream-regulation and downstream-regulation high-throughput data. Firstly, we theoretically and computationally demonstrate the effectiveness of APG by comparing with the traditional strategy based only on TF downstream-regulation information. We then apply this model to study spontaneous type 2 diabetic Goto-Kakizaki (GK) and Wistar control rats. Our biological experiments validate the theoretical results. In particular, SP1 is found to be a hidden TF with changed regulatory activity, and the loss of SP1 activity contributes to the increased glucose production during diabetes development. APG model provides theoretical basis to quantitatively elucidate transcriptional regulation by modelling TF combinatorial interactions and exploiting multilevel high-throughput information.

APG: an Active Protein-Gene Network Model to Quantify Regulatory Signals in Complex Biological Systems

PubMed Central

Wang, Jiguang; Sun, Yidan; Zheng, Si; Zhang, Xiang-Sun; Zhou, Huarong; Chen, Luonan

2013-01-01

Synergistic interactions among transcription factors (TFs) and their cofactors collectively determine gene expression in complex biological systems. In this work, we develop a novel graphical model, called Active Protein-Gene (APG) network model, to quantify regulatory signals of transcription in complex biomolecular networks through integrating both TF upstream-regulation and downstream-regulation high-throughput data. Firstly, we theoretically and computationally demonstrate the effectiveness of APG by comparing with the traditional strategy based only on TF downstream-regulation information. We then apply this model to study spontaneous type 2 diabetic Goto-Kakizaki (GK) and Wistar control rats. Our biological experiments validate the theoretical results. In particular, SP1 is found to be a hidden TF with changed regulatory activity, and the loss of SP1 activity contributes to the increased glucose production during diabetes development. APG model provides theoretical basis to quantitatively elucidate transcriptional regulation by modelling TF combinatorial interactions and exploiting multilevel high-throughput information. PMID:23346354

On-the-fly machine-learning for high-throughput experiments: search for rare-earth-free permanent magnets

PubMed Central

Kusne, Aaron Gilad; Gao, Tieren; Mehta, Apurva; Ke, Liqin; Nguyen, Manh Cuong; Ho, Kai-Ming; Antropov, Vladimir; Wang, Cai-Zhuang; Kramer, Matthew J.; Long, Christian; Takeuchi, Ichiro

2014-01-01

Advanced materials characterization techniques with ever-growing data acquisition speed and storage capabilities represent a challenge in modern materials science, and new procedures to quickly assess and analyze the data are needed. Machine learning approaches are effective in reducing the complexity of data and rapidly homing in on the underlying trend in multi-dimensional data. Here, we show that by employing an algorithm called the mean shift theory to a large amount of diffraction data in high-throughput experimentation, one can streamline the process of delineating the structural evolution across compositional variations mapped on combinatorial libraries with minimal computational cost. Data collected at a synchrotron beamline are analyzed on the fly, and by integrating experimental data with the inorganic crystal structure database (ICSD), we can substantially enhance the accuracy in classifying the structural phases across ternary phase spaces. We have used this approach to identify a novel magnetic phase with enhanced magnetic anisotropy which is a candidate for rare-earth free permanent magnet. PMID:25220062

Locality for quantum systems on graphs depends on the number field

NASA Astrophysics Data System (ADS)

Hall, H. Tracy; Severini, Simone

2013-07-01

Adapting a definition of Aaronson and Ambainis (2005 Theory Comput. 1 47-79), we call a quantum dynamics on a digraph saturated Z-local if the nonzero transition amplitudes specifying the unitary evolution are in exact correspondence with the directed edges (including loops) of the digraph. This idea appears recurrently in a variety of contexts including angular momentum, quantum chaos, and combinatorial matrix theory. Complete characterization of the digraph properties that allow such a process to exist is a long-standing open question that can also be formulated in terms of minimum rank problems. We prove that saturated Z-local dynamics involving complex amplitudes occur on a proper superset of the digraphs that allow restriction to the real numbers or, even further, the rationals. Consequently, among these fields, complex numbers guarantee the largest possible choice of topologies supporting a discrete quantum evolution. A similar construction separates complex numbers from the skew field of quaternions. The result proposes a concrete ground for distinguishing between complex and quaternionic quantum mechanics.

AI techniques for a space application scheduling problem

NASA Technical Reports Server (NTRS)

Thalman, N.; Sparn, T.; Jaffres, L.; Gablehouse, D.; Judd, D.; Russell, C.

1991-01-01

Scheduling is a very complex optimization problem which can be categorized as an NP-complete problem. NP-complete problems are quite diverse, as are the algorithms used in searching for an optimal solution. In most cases, the best solutions that can be derived for these combinatorial explosive problems are near-optimal solutions. Due to the complexity of the scheduling problem, artificial intelligence (AI) can aid in solving these types of problems. Some of the factors are examined which make space application scheduling problems difficult and presents a fairly new AI-based technique called tabu search as applied to a real scheduling application. the specific problem is concerned with scheduling application. The specific problem is concerned with scheduling solar and stellar observations for the SOLar-STellar Irradiance Comparison Experiment (SOLSTICE) instrument in a constrained environment which produces minimum impact on the other instruments and maximizes target observation times. The SOLSTICE instrument will gly on-board the Upper Atmosphere Research Satellite (UARS) in 1991, and a similar instrument will fly on the earth observing system (Eos).

Experimental Design for Estimating Unknown Hydraulic Conductivity in a Confined Aquifer using a Genetic Algorithm and a Reduced Order Model

NASA Astrophysics Data System (ADS)

Ushijima, T.; Yeh, W.

2013-12-01

An optimal experimental design algorithm is developed to select locations for a network of observation wells that provides the maximum information about unknown hydraulic conductivity in a confined, anisotropic aquifer. The design employs a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. Because that the formulated problem is non-convex and contains integer variables (necessitating a combinatorial search), for a realistically-scaled model, the problem may be difficult, if not impossible, to solve through traditional mathematical programming techniques. Genetic Algorithms (GAs) are designed to search out the global optimum; however because a GA requires a large number of calls to a groundwater model, the formulated optimization problem may still be infeasible to solve. To overcome this, Proper Orthogonal Decomposition (POD) is applied to the groundwater model to reduce its dimension. The information matrix in the full model space can then be searched without solving the full model.

Directed Bee Colony Optimization Algorithm to Solve the Nurse Rostering Problem.

PubMed

Rajeswari, M; Amudhavel, J; Pothula, Sujatha; Dhavachelvan, P

2017-01-01

The Nurse Rostering Problem is an NP-hard combinatorial optimization, scheduling problem for assigning a set of nurses to shifts per day by considering both hard and soft constraints. A novel metaheuristic technique is required for solving Nurse Rostering Problem (NRP). This work proposes a metaheuristic technique called Directed Bee Colony Optimization Algorithm using the Modified Nelder-Mead Method for solving the NRP. To solve the NRP, the authors used a multiobjective mathematical programming model and proposed a methodology for the adaptation of a Multiobjective Directed Bee Colony Optimization (MODBCO). MODBCO is used successfully for solving the multiobjective problem of optimizing the scheduling problems. This MODBCO is an integration of deterministic local search, multiagent particle system environment, and honey bee decision-making process. The performance of the algorithm is assessed using the standard dataset INRC2010, and it reflects many real-world cases which vary in size and complexity. The experimental analysis uses statistical tools to show the uniqueness of the algorithm on assessment criteria.

Linear reduction methods for tag SNP selection.

PubMed

He, Jingwu; Zelikovsky, Alex

2004-01-01

It is widely hoped that constructing a complete human haplotype map will help to associate complex diseases with certain SNP's. Unfortunately, the number of SNP's is huge and it is very costly to sequence many individuals. Therefore, it is desirable to reduce the number of SNP's that should be sequenced to considerably small number of informative representatives, so called tag SNP's. In this paper, we propose a new linear algebra based method for selecting and using tag SNP's. Our method is purely combinatorial and can be combined with linkage disequilibrium (LD) and block based methods. We measure the quality of our tag SNP selection algorithm by comparing actual SNP's with SNP's linearly predicted from linearly chosen tag SNP's. We obtain an extremely good compression and prediction rates. For example, for long haplotypes (>25000 SNP's), knowing only 0.4% of all SNP's we predict the entire unknown haplotype with 2% accuracy while the prediction method is based on a 10% sample of the population.

Tug-Of-War Model for Two-Bandit Problem

NASA Astrophysics Data System (ADS)

Kim, Song-Ju; Aono, Masashi; Hara, Masahiko

The amoeba of the true slime mold Physarum polycephalum shows high computational capabilities. In the so-called amoeba-based computing, some computing tasks including combinatorial optimization are performed by the amoeba instead of a digital computer. We expect that there must be problems living organisms are good at solving. The “multi-armed bandit problem” would be the one of such problems. Consider a number of slot machines. Each of the machines has an arm which gives a player a reward with a certain probability when pulled. The problem is to determine the optimal strategy for maximizing the total reward sum after a certain number of trials. To maximize the total reward sum, it is necessary to judge correctly and quickly which machine has the highest reward probability. Therefore, the player should explore many machines to gather much knowledge on which machine is the best, but should not fail to exploit the reward from the known best machine. We consider that living organisms follow some efficient method to solve the problem.

Directed Bee Colony Optimization Algorithm to Solve the Nurse Rostering Problem

PubMed Central

Amudhavel, J.; Pothula, Sujatha; Dhavachelvan, P.

2017-01-01

The Nurse Rostering Problem is an NP-hard combinatorial optimization, scheduling problem for assigning a set of nurses to shifts per day by considering both hard and soft constraints. A novel metaheuristic technique is required for solving Nurse Rostering Problem (NRP). This work proposes a metaheuristic technique called Directed Bee Colony Optimization Algorithm using the Modified Nelder-Mead Method for solving the NRP. To solve the NRP, the authors used a multiobjective mathematical programming model and proposed a methodology for the adaptation of a Multiobjective Directed Bee Colony Optimization (MODBCO). MODBCO is used successfully for solving the multiobjective problem of optimizing the scheduling problems. This MODBCO is an integration of deterministic local search, multiagent particle system environment, and honey bee decision-making process. The performance of the algorithm is assessed using the standard dataset INRC2010, and it reflects many real-world cases which vary in size and complexity. The experimental analysis uses statistical tools to show the uniqueness of the algorithm on assessment criteria. PMID:28473849

Engineered knottin peptides as diagnostics, therapeutics, and drug delivery vehicles.

PubMed

Kintzing, James R; Cochran, Jennifer R

2016-10-01

Inhibitor cystine-knots, also known as knottins, are a structural family of ultra-stable peptides with diverse functions. Knottins and related backbone-cyclized peptides called cyclotides contain three disulfide bonds connected in a particular arrangement that endows these peptides with high thermal, proteolytic, and chemical stability. Knottins have gained interest as candidates for non-invasive molecular imaging and for drug development as they can possess the pharmacological properties of small molecules and the target affinity and selectively of protein biologics. Naturally occurring knottins are clinically approved for treating chronic pain and GI disorders. Combinatorial methods are being used to engineer knottins that can bind to other clinically relevant targets in cancer, and inflammatory and cardiac disease. This review details recent examples of engineered knottin peptides; their use as molecular imaging agents, therapeutics, and drug delivery vehicles; modifications that can be introduced to improve peptide folding and bioactivity; and future perspectives and challenges in the field. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cognitive architecture of perceptual organization: from neurons to gnosons.

PubMed

van der Helm, Peter A

2012-02-01

What, if anything, is cognitive architecture and how is it implemented in neural architecture? Focusing on perceptual organization, this question is addressed by way of a pluralist approach which, supported by metatheoretical considerations, combines complementary insights from representational, connectionist, and dynamic systems approaches to cognition. This pluralist approach starts from a representationally inspired model which implements the intertwined but functionally distinguishable subprocesses of feedforward feature encoding, horizontal feature binding, and recurrent feature selection. As sustained by a review of neuroscientific evidence, these are the subprocesses that are believed to take place in the visual hierarchy in the brain. Furthermore, the model employs a special form of processing, called transparallel processing, whose neural signature is proposed to be gamma-band synchronization in transient horizontal neural assemblies. In neuroscience, such assemblies are believed to mediate binding of similar features. Their formal counterparts in the model are special input-dependent distributed representations, called hyperstrings, which allow many similar features to be processed in a transparallel fashion, that is, simultaneously as if only one feature were concerned. This form of processing does justice to both the high combinatorial capacity and the high speed of the perceptual organization process. A naturally following proposal is that those temporarily synchronized neural assemblies are "gnosons", that is, constituents of flexible self-organizing cognitive architecture in between the relatively rigid level of neurons and the still elusive level of consciousness.

Punctuated evolution and robustness in morphogenesis

PubMed Central

Grigoriev, D.; Reinitz, J.; Vakulenko, S.; Weber, A.

2014-01-01

This paper presents an analytic approach to the pattern stability and evolution problem in morphogenesis. The approach used here is based on the ideas from the gene and neural network theory. We assume that gene networks contain a number of small groups of genes (called hubs) controlling morphogenesis process. Hub genes represent an important element of gene network architecture and their existence is empirically confirmed. We show that hubs can stabilize morphogenetic pattern and accelerate the morphogenesis. The hub activity exhibits an abrupt change depending on the mutation frequency. When the mutation frequency is small, these hubs suppress all mutations and gene product concentrations do not change, thus, the pattern is stable. When the environmental pressure increases and the population needs new genotypes, the genetic drift and other effects increase the mutation frequency. For the frequencies that are larger than a critical amount the hubs turn off; and as a result, many mutations can affect phenotype. This effect can serve as an engine for evolution. We show that this engine is very effective: the evolution acceleration is an exponential function of gene redundancy. Finally, we show that the Eldredge-Gould concept of punctuated evolution results from the network architecture, which provides fast evolution, control of evolvability, and pattern robustness. To describe analytically the effect of exponential acceleration, we use mathematical methods developed recently for hard combinatorial problems, in particular, for so-called k-SAT problem, and numerical simulations. PMID:24996115

A statistical approach to understanding reproductive isolation in two sympatric species of tree crickets.

PubMed

Bhattacharya, Monisha; Isvaran, Kavita; Balakrishnan, Rohini

2017-04-01

In acoustically communicating animals, reproductive isolation between sympatric species is usually maintained through species-specific calls. This requires that the receiver be tuned to the conspecific signal. Mapping the response space of the receiver onto the signal space of the conspecific investigates this tuning. A combinatorial approach to investigating the response space is more informative as the influence on the receiver of the interactions between the features is also elucidated. However, most studies have examined individual preference functions rather than the multivariate response space. We studied the maintenance of reproductive isolation between two sympatric tree cricket species ( Oecanthus henryi and Oecanthus indicus ) through the temporal features of the calls. Individual response functions were determined experimentally for O. henryi , the results from which were combined in a statistical framework to generate a multivariate quantitative receiver response space. The predicted response was higher for the signals of the conspecific than for signals of the sympatric heterospecific, indicating maintenance of reproductive isolation through songs. The model allows prediction of response to untested combinations of temporal features as well as delineation of the evolutionary constraints on the signal space. The model can also be used to predict the response of O. henryi to other heterospecific signals, making it a useful tool for the study of the evolution and maintenance of reproductive isolation via long-range acoustic signals. © 2017. Published by The Company of Biologists Ltd.

ChemBrowser: a flexible framework for mining chemical documents.

PubMed

Wu, Xian; Zhang, Li; Chen, Ying; Rhodes, James; Griffin, Thomas D; Boyer, Stephen K; Alba, Alfredo; Cai, Keke

2010-01-01

The ability to extract chemical and biological entities and relations from text documents automatically has great value to biochemical research and development activities. The growing maturity of text mining and artificial intelligence technologies shows promise in enabling such automatic chemical entity extraction capabilities (called "Chemical Annotation" in this paper). Many techniques have been reported in the literature, ranging from dictionary and rule-based techniques to machine learning approaches. In practice, we found that no single technique works well in all cases. A combinatorial approach that allows one to quickly compose different annotation techniques together for a given situation is most effective. In this paper, we describe the key challenges we face in real-world chemical annotation scenarios. We then present a solution called ChemBrowser which has a flexible framework for chemical annotation. ChemBrowser includes a suite of customizable processing units that might be utilized in a chemical annotator, a high-level language that describes the composition of various processing units that would form a chemical annotator, and an execution engine that translates the composition language to an actual annotator that can generate annotation results for a given set of documents. We demonstrate the impact of this approach by tailoring an annotator for extracting chemical names from patent documents and show how this annotator can be easily modified with simple configuration alone.

Tanglegrams: A Reduction Tool for Mathematical Phylogenetics.

PubMed

Matsen, Frederick A; Billey, Sara C; Kas, Arnold; Konvalinka, Matjaz

2018-01-01

Many discrete mathematics problems in phylogenetics are defined in terms of the relative labeling of pairs of leaf-labeled trees. These relative labelings are naturally formalized as tanglegrams, which have previously been an object of study in coevolutionary analysis. Although there has been considerable work on planar drawings of tanglegrams, they have not been fully explored as combinatorial objects until recently. In this paper, we describe how many discrete mathematical questions on trees "factor" through a problem on tanglegrams, and how understanding that factoring can simplify analysis. Depending on the problem, it may be useful to consider a unordered version of tanglegrams, and/or their unrooted counterparts. For all of these definitions, we show how the isomorphism types of tanglegrams can be understood in terms of double cosets of the symmetric group, and we investigate their automorphisms. Understanding tanglegrams better will isolate the distinct problems on leaf-labeled pairs of trees and reveal natural symmetries of spaces associated with such problems.

SMITHERS: An object-oriented modular mapping methodology for MCNP-based neutronic–thermal hydraulic multiphysics

DOE PAGES

Richard, Joshua; Galloway, Jack; Fensin, Michael; ...

2015-04-04

A novel object-oriented modular mapping methodology for externally coupled neutronics–thermal hydraulics multiphysics simulations was developed. The Simulator using MCNP with Integrated Thermal-Hydraulics for Exploratory Reactor Studies (SMITHERS) code performs on-the-fly mapping of material-wise power distribution tallies implemented by MCNP-based neutron transport/depletion solvers for use in estimating coolant temperature and density distributions with a separate thermal-hydraulic solver. The key development of SMITHERS is that it reconstructs the hierarchical geometry structure of the material-wise power generation tallies from the depletion solver automatically, with only a modicum of additional information required from the user. In addition, it performs the basis mapping from themore » combinatorial geometry of the depletion solver to the required geometry of the thermal-hydraulic solver in a generalizable manner, such that it can transparently accommodate varying levels of thermal-hydraulic solver geometric fidelity, from the nodal geometry of multi-channel analysis solvers to the pin-cell level of discretization for sub-channel analysis solvers.« less

Large scale tracking algorithms

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

Hansen, Ross L.; Love, Joshua Alan; Melgaard, David Kennett

2015-01-01

Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For highermore » resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.« less

Nouns, verbs, objects, actions, and abstractions: Local fMRI activity indexes semantics, not lexical categories

PubMed Central

Moseley, Rachel L.; Pulvermüller, Friedemann

2014-01-01

Noun/verb dissociations in the literature defy interpretation due to the confound between lexical category and semantic meaning; nouns and verbs typically describe concrete objects and actions. Abstract words, pertaining to neither, are a critical test case: dissociations along lexical-grammatical lines would support models purporting lexical category as the principle governing brain organisation, whilst semantic models predict dissociation between concrete words but not abstract items. During fMRI scanning, participants read orthogonalised word categories of nouns and verbs, with or without concrete, sensorimotor meaning. Analysis of inferior frontal/insula, precentral and central areas revealed an interaction between lexical class and semantic factors with clear category differences between concrete nouns and verbs but not abstract ones. Though the brain stores the combinatorial and lexical-grammatical properties of words, our data show that topographical differences in brain activation, especially in the motor system and inferior frontal cortex, are driven by semantics and not by lexical class. PMID:24727103

Computation of the area in the discrete plane: Green's theorem revisited

NASA Astrophysics Data System (ADS)

Chalifour, Alain; Nouboud, Fathallah; Voisin, Yvon

2017-11-01

The detection of the contour of a binary object is a common problem; however, the area of a region, and its moments, can be a significant parameter. In several metrology applications, the area of planar objects must be measured. The area is obtained by counting the pixels inside the contour or using a discrete version of Green's formula. Unfortunately, we obtain the area enclosed by the polygonal line passing through the centers of the pixels along the contour. We present a modified version of Green's theorem in the discrete plane, which allows for the computation of the exact area of a two-dimensional region in the class of polyominoes. Penalties are introduced and associated with each successive pair of Freeman displacements along the contour in an eight-connectivity system. The proposed equation is shown to be true and properties of the equation related to the topology of the regions are presented. The proposed approach is adapted for faster computation than the combinatorial approach proposed in the literature.

Nouns, verbs, objects, actions, and abstractions: local fMRI activity indexes semantics, not lexical categories.

PubMed

Moseley, Rachel L; Pulvermüller, Friedemann

2014-05-01

Noun/verb dissociations in the literature defy interpretation due to the confound between lexical category and semantic meaning; nouns and verbs typically describe concrete objects and actions. Abstract words, pertaining to neither, are a critical test case: dissociations along lexical-grammatical lines would support models purporting lexical category as the principle governing brain organisation, whilst semantic models predict dissociation between concrete words but not abstract items. During fMRI scanning, participants read orthogonalised word categories of nouns and verbs, with or without concrete, sensorimotor meaning. Analysis of inferior frontal/insula, precentral and central areas revealed an interaction between lexical class and semantic factors with clear category differences between concrete nouns and verbs but not abstract ones. Though the brain stores the combinatorial and lexical-grammatical properties of words, our data show that topographical differences in brain activation, especially in the motor system and inferior frontal cortex, are driven by semantics and not by lexical class. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Graph-theoretic approach to quantum correlations.

PubMed

Cabello, Adán; Severini, Simone; Winter, Andreas

2014-01-31

Correlations in Bell and noncontextuality inequalities can be expressed as a positive linear combination of probabilities of events. Exclusive events can be represented as adjacent vertices of a graph, so correlations can be associated to a subgraph. We show that the maximum value of the correlations for classical, quantum, and more general theories is the independence number, the Lovász number, and the fractional packing number of this subgraph, respectively. We also show that, for any graph, there is always a correlation experiment such that the set of quantum probabilities is exactly the Grötschel-Lovász-Schrijver theta body. This identifies these combinatorial notions as fundamental physical objects and provides a method for singling out experiments with quantum correlations on demand.

Identification of avocado (Persea americana) pulp proteins by nano-LC-MS/MS via combinatorial peptide ligand libraries.

PubMed

Esteve, Clara; D'Amato, Alfonsina; Marina, María Luisa; García, María Concepción; Righetti, Pier Giorgio

2012-09-01

Avocado (Persea americana) proteins have been scarcely studied despite their importance, especially in food related allergies. The proteome of avocado pulp was explored in depth by extracting proteins with capture by combinatorial peptide ligand libraries at pH 7.4 and under conditions mimicking reverse-phase capture at pH 2.2. The total number of unique gene products identified amounts to 1012 proteins, of which 174 are in common with the control, untreated sample, 190 are present only in the control and 648 represent the new species detected via combinatorial peptide ligand libraries of all combined eluates and likely represent low-abundance proteins. Among the 1012 proteins, it was possible to identify the already known avocado allergen Pers a 1 and different proteins susceptible to be allergens such as a profilin, a polygalacturonase, a thaumatin-like protein, a glucanase, and an isoflavone reductase like protein. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A path-oriented knowledge representation system: Defusing the combinatorial system

NASA Technical Reports Server (NTRS)

Karamouzis, Stamos T.; Barry, John S.; Smith, Steven L.; Feyock, Stefan

1995-01-01

LIMAP is a programming system oriented toward efficient information manipulation over fixed finite domains, and quantification over paths and predicates. A generalization of Warshall's Algorithm to precompute paths in a sparse matrix representation of semantic nets is employed to allow questions involving paths between components to be posed and answered easily. LIMAP's ability to cache all paths between two components in a matrix cell proved to be a computational obstacle, however, when the semantic net grew to realistic size. The present paper describes a means of mitigating this combinatorial explosion to an extent that makes the use of the LIMAP representation feasible for problems of significant size. The technique we describe radically reduces the size of the search space in which LIMAP must operate; semantic nets of more than 500 nodes have been attacked successfully. Furthermore, it appears that the procedure described is applicable not only to LIMAP, but to a number of other combinatorially explosive search space problems found in AI as well.

Combinatorial selection of molecular conformations and supramolecular synthons in quercetin cocrystal landscapes: a route to ternary solids

PubMed Central

Dubey, Ritesh; Desiraju, Gautam R.

2015-01-01

The crystallization of 28 binary and ternary cocrystals of quercetin with dibasic coformers is analyzed in terms of a combinatorial selection from a solution of preferred molecular conformations and supramolecular synthons. The crystal structures are characterized by distinctive O—H⋯N and O—H⋯O based synthons and are classified as nonporous, porous and helical. Variability in molecular conformation and synthon structure led to an increase in the energetic and structural space around the crystallization event. This space is the crystal structure landscape of the compound and is explored by fine-tuning the experimental conditions of crystallization. In the landscape context, we develop a strategy for the isolation of ternary cocrystals with the use of auxiliary template molecules to reduce the molecular and supramolecular ‘confusion’ that is inherent in a molecule like quercetin. The absence of concomitant polymorphism in this study highlights the selectivity in conformation and synthon choice from the virtual combinatorial library in solution. PMID:26175900

Nucleophilic catalysis of acylhydrazone equilibration for protein-directed dynamic covalent chemistry

PubMed Central

Bhat, Venugopal T.; Caniard, Anne M.; Luksch, Torsten; Brenk, Ruth; Campopiano, Dominic J.; Greaney, Michael F.

2010-01-01

Dynamic covalent chemistry uses reversible chemical reactions to set up an equilibrating network of molecules at thermodynamic equilibrium, which can adjust its composition in response to any agent capable of altering the free energy of the system. When the target is a biological macromolecule, such as a protein, the process corresponds to the protein directing the synthesis of its own best ligand. Here, we demonstrate that reversible acylhydrazone formation is an effective chemistry for biological dynamic combinatorial library formation. In the presence of aniline as a nucleophilic catalyst, dynamic combinatorial libraries equilibrate rapidly at pH 6.2, are fully reversible, and may be switched on or off by means of a change in pH. We have interfaced these hydrazone dynamic combinatorial libraries with two isozymes from the glutathione S-transferase class of enzyme, and observed divergent amplification effects, where each protein selects the best-fitting hydrazone for the hydrophobic region of its active site. PMID:20489719

Evaluating the Effect of Peptoid Lipophilicity on Antimicrobial Potency, Cytotoxicity, and Combinatorial Library Design.

PubMed

Turkett, Jeremy A; Bicker, Kevin L

2017-04-10

Growing prevalence of antibiotic resistant bacterial infections necessitates novel antimicrobials, which could be rapidly identified from combinatorial libraries. We report the use of the peptoid library agar diffusion (PLAD) assay to screen peptoid libraries against the ESKAPE pathogens, including the optimization of assay conditions for each pathogen. Work presented here focuses on the tailoring of combinatorial peptoid library design through a detailed study of how peptoid lipophilicity relates to antibacterial potency and mammalian cell toxicity. The information gleaned from this optimization was then applied using the aforementioned screening method to examine the relative potency of peptoid libraries against Staphylococcus aureus, Acinetobacter baumannii, and Enterococcus faecalis prior to and following functionalization with long alkyl tails. The data indicate that overall peptoid hydrophobicity and not simply alkyl tail length is strongly correlated with mammalian cell toxicity. Furthermore, this work demonstrates the utility of the PLAD assay in rapidly evaluating the effect of molecular property changes in similar libraries.

Combinatorial delivery of small interfering RNAs reduces RNAi efficacy by selective incorporation into RISC

PubMed Central

Castanotto, Daniela; Sakurai, Kumi; Lingeman, Robert; Li, Haitang; Shively, Louise; Aagaard, Lars; Soifer, Harris; Gatignol, Anne; Riggs, Arthur; Rossi, John J.

2007-01-01

Despite the great potential of RNAi, ectopic expression of shRNA or siRNAs holds the inherent risk of competition for critical RNAi components, thus altering the regulatory functions of some cellular microRNAs. In addition, specific siRNA sequences can potentially hinder incorporation of other siRNAs when used in a combinatorial approach. We show that both synthetic siRNAs and expressed shRNAs compete against each other and with the endogenous microRNAs for transport and for incorporation into the RNA induced silencing complex (RISC). The same siRNA sequences do not display competition when expressed from a microRNA backbone. We also show that TAR RNA binding protein (TRBP) is one of the sensors for selection and incorporation of the guide sequence of interfering RNAs. These findings reveal that combinatorial siRNA approaches can be problematic and have important implications for the methodology of expression and use of therapeutic interfering RNAs. PMID:17660190

Similarity searching and scaffold hopping in synthetically accessible combinatorial chemistry spaces.

PubMed

Boehm, Markus; Wu, Tong-Ying; Claussen, Holger; Lemmen, Christian

2008-04-24

Large collections of combinatorial libraries are an integral element in today's pharmaceutical industry. It is of great interest to perform similarity searches against all virtual compounds that are synthetically accessible by any such library. Here we describe the successful application of a new software tool CoLibri on 358 combinatorial libraries based on validated reaction protocols to create a single chemistry space containing over 10 (12) possible products. Similarity searching with FTrees-FS allows the systematic exploration of this space without the need to enumerate all product structures. The search result is a set of virtual hits which are synthetically accessible by one or more of the existing reaction protocols. Grouping these virtual hits by their synthetic protocols allows the rapid design and synthesis of multiple follow-up libraries. Such library ideas support hit-to-lead design efforts for tasks like follow-up from high-throughput screening hits or scaffold hopping from one hit to another attractive series.

Iterative optimization of xylose catabolism in Saccharomyces cerevisiae using combinatorial expression tuning.

PubMed

Latimer, Luke N; Dueber, John E

2017-06-01

A common challenge in metabolic engineering is rapidly identifying rate-controlling enzymes in heterologous pathways for subsequent production improvement. We demonstrate a workflow to address this challenge and apply it to improving xylose utilization in Saccharomyces cerevisiae. For eight reactions required for conversion of xylose to ethanol, we screened enzymes for functional expression in S. cerevisiae, followed by a combinatorial expression analysis to achieve pathway flux balancing and identification of limiting enzymatic activities. In the next round of strain engineering, we increased the copy number of these limiting enzymes and again tested the eight-enzyme combinatorial expression library in this new background. This workflow yielded a strain that has a ∼70% increase in biomass yield and ∼240% increase in xylose utilization. Finally, we chromosomally integrated the expression library. This library enriched for strains with multiple integrations of the pathway, which likely were the result of tandem integrations mediated by promoter homology. Biotechnol. Bioeng. 2017;114: 1301-1309. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Device for preparing combinatorial libraries in powder metallurgy.

PubMed

Yang, Shoufeng; Evans, Julian R G

2004-01-01

This paper describes a powder-metering, -mixing, and -dispensing mechanism that can be used as a method for producing large numbers of samples for metallurgical evaluation or electrical or mechanical testing from multicomponent metal and cermet powder systems. It is designed to make use of the same commercial powders that are used in powder metallurgy and, therefore, to produce samples that are faithful to the microstructure of finished products. The particle assemblies produced by the device could be consolidated by die pressing, isostatic pressing, laser sintering, or direct melting. The powder metering valve provides both on/off and flow rate control of dry powders in open capillaries using acoustic vibration. The valve is simple and involves no relative movement, avoiding seizure with fine powders. An orchestra of such valves can be arranged on a building platform to prepare multicomponent combinatorial libraries. As with many combinatorial devices, identification and evaluation of sources of mixing error as a function of sample size is mandatory. Such an analysis is presented.

Polymeric nanofiber coating with tunable combinatorial antibiotic delivery prevents biofilm-associated infection in vivo

PubMed Central

Ashbaugh, Alyssa G.; Jiang, Xuesong; Zheng, Jesse; Tsai, Andrew S.; Kim, Woo-Shin; Thompson, John M.; Miller, Robert J.; Shahbazian, Jonathan H.; Wang, Yu; Dillen, Carly A.; Ordonez, Alvaro A.; Chang, Yong S.; Jain, Sanjay K.; Jones, Lynne C.; Sterling, Robert S.; Mao, Hai-Quan; Miller, Lloyd S.

2016-01-01

Bacterial biofilm formation is a major complication of implantable medical devices that results in therapeutically challenging chronic infections, especially in cases involving antibiotic-resistant bacteria. As an approach to prevent these infections, an electrospun composite coating comprised of poly(lactic-coglycolic acid) (PLGA) nanofibers embedded in a poly(ε-caprolactone) (PCL) film was developed to locally codeliver combinatorial antibiotics from the implant surface. The release of each antibiotic could be adjusted by loading each drug into the different polymers or by varying PLGA:PCL polymer ratios. In a mouse model of biofilm-associated orthopedic-implant infection, three different combinations of antibiotic-loaded coatings were highly effective in preventing infection of the bone/joint tissue and implant biofilm formation and were biocompatible with enhanced osseointegration. This nanofiber composite-coating technology could be used to tailor the delivery of combinatorial antimicrobial agents from various metallic implantable devices or prostheses to effectively decrease biofilm-associated infections in patients. PMID:27791154

Combinatorial Screening for Transgenic Yeasts with High Cellulase Activities in Combination with a Tunable Expression System

PubMed Central

Ito, Yoichiro; Yamanishi, Mamoru; Ikeuchi, Akinori; Imamura, Chie; Matsuyama, Takashi

2015-01-01

Combinatorial screening used together with a broad library of gene expression cassettes is expected to produce a powerful tool for the optimization of the simultaneous expression of multiple enzymes. Recently, we proposed a highly tunable protein expression system that utilized multiple genome-integrated target genes to fine-tune enzyme expression in yeast cells. This tunable system included a library of expression cassettes each composed of three gene-expression control elements that in different combinations produced a wide range of protein expression levels. In this study, four gene expression cassettes with graded protein expression levels were applied to the expression of three cellulases: cellobiohydrolase 1, cellobiohydrolase 2, and endoglucanase 2. After combinatorial screening for transgenic yeasts simultaneously secreting these three cellulases, we obtained strains with higher cellulase expressions than a strain harboring three cellulase-expression constructs within one high-performance gene expression cassette. These results show that our method will be of broad use throughout the field of metabolic engineering. PMID:26692026

Combinatorial Strategies for the Development of Bulk Metallic Glasses

NASA Astrophysics Data System (ADS)

Ding, Shiyan

The systematic identification of multi-component alloys out of the vast composition space is still a daunting task, especially in the development of bulk metallic glasses that are typically based on three or more elements. In order to address this challenge, combinatorial approaches have been proposed. However, previous attempts have not successfully coupled the synthesis of combinatorial libraries with high-throughput characterization methods. The goal of my dissertation is to develop efficient high-throughput characterization methods, optimized to identify glass formers systematically. Here, two innovative approaches have been invented. One is to measure the nucleation temperature in parallel for up-to 800 compositions. The composition with the lowest nucleation temperature has a reasonable agreement with the best-known glass forming composition. In addition, the thermoplastic formability of a metallic glass forming system is determined through blow molding a compositional library. Our results reveal that the composition with the largest thermoplastic deformation correlates well with the best-known formability composition. I have demonstrated both methods as powerful tools to develop new bulk metallic glasses.

High-flexibility combinatorial peptide synthesis with laser-based transfer of monomers in solid matrix material.

PubMed

Loeffler, Felix F; Foertsch, Tobias C; Popov, Roman; Mattes, Daniela S; Schlageter, Martin; Sedlmayr, Martyna; Ridder, Barbara; Dang, Florian-Xuan; von Bojničić-Kninski, Clemens; Weber, Laura K; Fischer, Andrea; Greifenstein, Juliane; Bykovskaya, Valentina; Buliev, Ivan; Bischoff, F Ralf; Hahn, Lothar; Meier, Michael A R; Bräse, Stefan; Powell, Annie K; Balaban, Teodor Silviu; Breitling, Frank; Nesterov-Mueller, Alexander

2016-06-14

Laser writing is used to structure surfaces in many different ways in materials and life sciences. However, combinatorial patterning applications are still limited. Here we present a method for cost-efficient combinatorial synthesis of very-high-density peptide arrays with natural and synthetic monomers. A laser automatically transfers nanometre-thin solid material spots from different donor slides to an acceptor. Each donor bears a thin polymer film, embedding one type of monomer. Coupling occurs in a separate heating step, where the matrix becomes viscous and building blocks diffuse and couple to the acceptor surface. Furthermore, we can consecutively deposit two material layers of activation reagents and amino acids. Subsequent heat-induced mixing facilitates an in situ activation and coupling of the monomers. This allows us to incorporate building blocks with click chemistry compatibility or a large variety of commercially available non-activated, for example, posttranslationally modified building blocks into the array's peptides with >17,000 spots per cm(2).

Thermoelectric properties of the LaCoO3-LaCrO3 system using a high-throughput combinatorial approach

NASA Astrophysics Data System (ADS)

Talley, K. R.; Barron, S. C.; Nguyen, N.; Wong-Ng, W.; Martin, J.; Zhang, Y. L.; Song, X.

2017-02-01

A combinatorial film of the LaCo1-xCrxO3 system was fabricated using the LaCoO3 and LaCrO3 targets at the NIST Pulsed Laser Deposition (PLD) facility. As the ionic size of Cr3+ is greater than that of Co3+, the unit cell volume of the series increases with increasing x. Using a custom screening tool, the Seebeck coefficient of LaCo1-xCrxO3 approaches a measured maximum of 286 μV/K, near to the cobalt-rich end of the film library (with x ≈ 0.49). The resistivity value increases continuously with increasing x. The measured power factor, PF, of this series, which is related to the efficiency of energy conversion, also exhibits a maximum at the composition of x ≈ 0.49, which corresponds to the maximum value of the Seebeck coefficient. Our results illustrate the efficiency of applying the high-throughput combinatorial technique to study thermoelectric materials.

BioPartsBuilder: a synthetic biology tool for combinatorial assembly of biological parts.

PubMed

Yang, Kun; Stracquadanio, Giovanni; Luo, Jingchuan; Boeke, Jef D; Bader, Joel S

2016-03-15

Combinatorial assembly of DNA elements is an efficient method for building large-scale synthetic pathways from standardized, reusable components. These methods are particularly useful because they enable assembly of multiple DNA fragments in one reaction, at the cost of requiring that each fragment satisfies design constraints. We developed BioPartsBuilder as a biologist-friendly web tool to design biological parts that are compatible with DNA combinatorial assembly methods, such as Golden Gate and related methods. It retrieves biological sequences, enforces compliance with assembly design standards and provides a fabrication plan for each fragment. BioPartsBuilder is accessible at http://public.biopartsbuilder.org and an Amazon Web Services image is available from the AWS Market Place (AMI ID: ami-508acf38). Source code is released under the MIT license, and available for download at https://github.com/baderzone/biopartsbuilder joel.bader@jhu.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Bioengineering Strategies for Designing Targeted Cancer Therapies

PubMed Central

Wen, Xuejun

2014-01-01

The goals of bioengineering strategies for targeted cancer therapies are (1) to deliver a high dose of an anticancer drug directly to a cancer tumor, (2) to enhance drug uptake by malignant cells, and (3) to minimize drug uptake by nonmalignant cells. Effective cancer-targeting therapies will require both passive- and active targeting strategies and a thorough understanding of physiologic barriers to targeted drug delivery. Designing a targeted therapy includes the selection and optimization of a nanoparticle delivery vehicle for passive accumulation in tumors, a targeting moiety for active receptor-mediated uptake, and stimuli-responsive polymers for control of drug release. The future direction of cancer targeting is a combinatorial approach, in which targeting therapies are designed to use multiple targeting strategies. The combinatorial approach will enable combination therapy for delivery of multiple drugs and dual ligand targeting to improve targeting specificity. Targeted cancer treatments in development and the new combinatorial approaches show promise for improving targeted anticancer drug delivery and improving treatment outcomes. PMID:23768509

Application of Multi-Hypothesis Sequential Monte Carlo for Breakup Analysis

NASA Astrophysics Data System (ADS)

Faber, W. R.; Zaidi, W.; Hussein, I. I.; Roscoe, C. W. T.; Wilkins, M. P.; Schumacher, P. W., Jr.

As more objects are launched into space, the potential for breakup events and space object collisions is ever increasing. These events create large clouds of debris that are extremely hazardous to space operations. Providing timely, accurate, and statistically meaningful Space Situational Awareness (SSA) data is crucial in order to protect assets and operations in space. The space object tracking problem, in general, is nonlinear in both state dynamics and observations, making it ill-suited to linear filtering techniques such as the Kalman filter. Additionally, given the multi-object, multi-scenario nature of the problem, space situational awareness requires multi-hypothesis tracking and management that is combinatorially challenging in nature. In practice, it is often seen that assumptions of underlying linearity and/or Gaussianity are used to provide tractable solutions to the multiple space object tracking problem. However, these assumptions are, at times, detrimental to tracking data and provide statistically inconsistent solutions. This paper details a tractable solution to the multiple space object tracking problem applicable to space object breakup events. Within this solution, simplifying assumptions of the underlying probability density function are relaxed and heuristic methods for hypothesis management are avoided. This is done by implementing Sequential Monte Carlo (SMC) methods for both nonlinear filtering as well as hypothesis management. This goal of this paper is to detail the solution and use it as a platform to discuss computational limitations that hinder proper analysis of large breakup events.

Solubility limits in quaternary SnTe-based alloys [Metastability and solubility limits in quaternary SnTe-based alloys guided by combinatorial sputtering

DOE PAGES

Siol, Sebastian; Holder, Aaron; Ortiz, Brenden R.; ...

2017-05-09

Here, the controlled decomposition of metastable alloys is an attractive route to form nanostructured thermoelectric materials with reduced thermal conductivity. The ternary SnTe–MnTe and SnTe–SnSe heterostructural alloys have been demonstrated as promising materials for thermoelectric applications. In this work, the quaternary Sn 1–yMnyTe 1–xSe x phase space serves as a relevant model system to explore how a combination of computational and combinatorial-growth methods can be used to study equilibrium and non-equilibrium solubility limits. Results from first principle calculations indicate low equilibrium solubility for x,y < 0.05 that are in good agreement with results obtained from bulk equilibrium synthesis experiments andmore » predict significantly higher spinodal limits. An experimental screening using sputtered combinatorial thin film sample libraries showed a remarkable increase in non-equilibrium solubility for x,y > 0.2. These theoretical and experimental results were used to guide the bulk synthesis of metastable alloys. The ability to reproduce the non-equilibrium solubility levels in bulk materials indicates that such theoretical calculations and combinatorial growth can inform bulk synthetic routes. Further, the large difference between equilibrium and non-equilibrium solubility limits in Sn 1–yMn yTe 1–xSe x indicates these metastable alloys are attractive in terms of nano-precipitate formation for potential thermoelectric applications.« less

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks

PubMed Central

Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Li, Baoqing; Yuan, Xiaobing

2017-01-01

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum–minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms. PMID:28753962

Spread the word: MMN brain response reveals whole-form access of discontinuous particle verbs.

PubMed

Hanna, Jeff; Cappelle, Bert; Pulvermüller, Friedemann

2017-12-01

The status of particle verbs such as rise (…) up as either lexically stored or combinatorially assembled is an issue which so far has not been settled decisively. In this study, we use the mismatch negativity (MMN) brain response to observe neurophysiological responses to discontinuous particle verbs. The MMN can be used to distinguish between whole-form storage and combinatorial processes, as it is enhanced to stored words compared to unknown pseudowords, whereas combinatorially legal strings elicit a reduced MMN relative to ungrammatical ones. Earlier work had found larger MMNs to congruent than to incongruent verb-particle combinations when particle and verb appeared as adjacent elements, thus suggesting whole-form storage at least in this case. However, it is still possible that particle verbs discontinuously spread out across a sentence would elicit the combinatorial, grammar-violation response pattern instead. Here, we tested the brain signatures of discontinuous verb-particle combinations, orthogonally varying congruence and semantic transparency. The results show for the first time brain indices of whole-form storage for discontinuous constituents, thus arguing in favour of access to whole-form-stored lexical elements in the processing of particle verbs, irrespective of their semantic opacity. Results are discussed in the context of linguistic debates about the status of particle verbs as words, lexical elements or syntactically generated combinations. The explanation of the pattern of results within a neurobiological language model is highlighted. Copyright © 2017 Elsevier Inc. All rights reserved.

Combinatorial Study of the Li-Ni-Mn-Co Oxide Pseudoquaternary System for Use in Li-Ion Battery Materials Research.

PubMed

Brown, Colby R; McCalla, Eric; Watson, Cody; Dahn, J R

2015-06-08

Combinatorial synthesis has proven extremely effective in screening for new battery materials for Li-ion battery electrodes. Here, a study in the Li-Ni-Mn-Co-O system is presented, wherein samples with nearly 800 distinct compositions were prepared using a combinatorial and high-throughput method to screen for single-phase materials of high interest as next generation positive electrode materials. X-ray diffraction is used to determine the crystal structure of each sample. The Gibbs' pyramid representing the pseudoquaternary system was studied by making samples within three distinct pseudoternary planes defined at fractional cobalt metal contents of 10%, 20%, and 30% within the Li-Ni-Mn-Co-O system. Two large single-phase regions were observed in the system: the layered region (ordered rocksalt) and cubic spinel region; both of which are of interest for next-generation positive electrodes in lithium-ion batteries. These regions were each found to stretch over a wide range of compositions within the Li-Ni-Mn-Co-O pseudoquaternary system and had complex coexistence regions existing between them. The sample cooling rate was found to have a significant effect on the position of the phase boundaries of the single-phase regions. The results of this work are intended to guide further research by narrowing the composition ranges worthy of study and to illustrate the broad range of applications where solution-based combinatorial synthesis can have significant impact.

Host-directed combinatorial RNAi improves inhibition of diverse strains of influenza A virus in human respiratory epithelial cells.

PubMed

Estrin, Michael A; Hussein, Islam T M; Puryear, Wendy B; Kuan, Anne C; Artim, Stephen C; Runstadler, Jonathan A

2018-01-01

Influenza A virus infections are important causes of morbidity and mortality worldwide, and currently available prevention and treatment methods are suboptimal. In recent years, genome-wide investigations have revealed numerous host factors that are required for influenza to successfully complete its life cycle. However, only a select, small number of influenza strains were evaluated using this platform, and there was considerable variation in the genes identified across different investigations. In an effort to develop a universally efficacious therapeutic strategy with limited potential for the emergence of resistance, this study was performed to investigate the effect of combinatorial RNA interference (RNAi) on inhibiting the replication of diverse influenza A virus subtypes and strains. Candidate genes were selected for targeting based on the results of multiple previous independent genome-wide studies. The effect of single and combinatorial RNAi on the replication of 12 diverse influenza A viruses, including three strains isolated from birds and one strain isolated from seals, was then evaluated in primary normal human bronchial epithelial cells. After excluding overly toxic siRNA, two siRNA combinations were identified that reduced mean viral replication by greater than 79 percent in all mammalian strains, and greater than 68 percent in all avian strains. Host-directed combinatorial RNAi effectively prevents growth of a broad range of influenza virus strains in vitro, and is a potential therapeutic candidate for further development and future in vivo studies.

Associating optical measurements of MEO and GEO objects using Population-Based Meta-Heuristic methods

NASA Astrophysics Data System (ADS)

Zittersteijn, M.; Vananti, A.; Schildknecht, T.; Dolado Perez, J. C.; Martinot, V.

2016-11-01

Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. The problem faced in this framework is that of Multiple Target Tracking (MTT). The MTT problem quickly becomes an NP-hard combinatorial optimization problem. This means that the effort required to solve the MTT problem increases exponentially with the number of tracked objects. In an attempt to find an approximate solution of sufficient quality, several Population-Based Meta-Heuristic (PBMH) algorithms are implemented and tested on simulated optical measurements. These first results show that one of the tested algorithms, namely the Elitist Genetic Algorithm (EGA), consistently displays the desired behavior of finding good approximate solutions before reaching the optimum. The results further suggest that the algorithm possesses a polynomial time complexity, as the computation times are consistent with a polynomial model. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the association and orbit determination problems simultaneously, and is able to efficiently process large data sets with minimal manual intervention.

Segmentation of whole cells and cell nuclei from 3-D optical microscope images using dynamic programming.

PubMed

McCullough, D P; Gudla, P R; Harris, B S; Collins, J A; Meaburn, K J; Nakaya, M A; Yamaguchi, T P; Misteli, T; Lockett, S J

2008-05-01

Communications between cells in large part drive tissue development and function, as well as disease-related processes such as tumorigenesis. Understanding the mechanistic bases of these processes necessitates quantifying specific molecules in adjacent cells or cell nuclei of intact tissue. However, a major restriction on such analyses is the lack of an efficient method that correctly segments each object (cell or nucleus) from 3-D images of an intact tissue specimen. We report a highly reliable and accurate semi-automatic algorithmic method for segmenting fluorescence-labeled cells or nuclei from 3-D tissue images. Segmentation begins with semi-automatic, 2-D object delineation in a user-selected plane, using dynamic programming (DP) to locate the border with an accumulated intensity per unit length greater that any other possible border around the same object. Then the two surfaces of the object in planes above and below the selected plane are found using an algorithm that combines DP and combinatorial searching. Following segmentation, any perceived errors can be interactively corrected. Segmentation accuracy is not significantly affected by intermittent labeling of object surfaces, diffuse surfaces, or spurious signals away from surfaces. The unique strength of the segmentation method was demonstrated on a variety of biological tissue samples where all cells, including irregularly shaped cells, were accurately segmented based on visual inspection.

Structure and Possible Functions of Constant-Frequency Calls in Ariopsis seemanni (Osteichthyes, Ariidae)

PubMed Central

Schmidtke, Daniel; Schulz, Jochen; Hartung, Jörg; Esser, Karl-Heinz

2013-01-01

In the 1970s, Tavolga conducted a series of experiments in which he found behavioral evidence that the vocalizations of the catfish species Ariopsis felis may play a role in a coarse form of echolocation. Based on his findings, he postulated a similar function for the calls of closely related catfish species. Here, we describe the physical characteristics of the predominant call-type of Ariopsis seemanni. In two behavioral experiments, we further explore whether A. seemanni uses these calls for acoustic obstacle detection by testing the hypothesis that the call-emission rate of individual fish should increase when subjects are confronted with novel objects, as it is known from other vertebrate species that use pulse-type signals to actively probe the environment. Audio-video monitoring of the fish under different obstacle conditions did not reveal a systematic increase in the number of emitted calls in the presence of novel objects or in dependence on the proximity between individual fish and different objects. These negative findings in combination with our current understanding of directional hearing in fishes (which is a prerequisite for acoustic obstacle detection) make it highly unlikely that A. seemanni uses its calls for acoustic obstacle detection. We argue that the calls are more likely to play a role in intra- or interspecific communication (e.g. in school formation or predator deterrence) and present results from a preliminary Y-maze experiment that are indicative for a positive phonotaxis of A. seemanni towards the calls of conspecifics. PMID:23741408

Gene-network inference by message passing

NASA Astrophysics Data System (ADS)

Braunstein, A.; Pagnani, A.; Weigt, M.; Zecchina, R.

2008-01-01

The inference of gene-regulatory processes from gene-expression data belongs to the major challenges of computational systems biology. Here we address the problem from a statistical-physics perspective and develop a message-passing algorithm which is able to infer sparse, directed and combinatorial regulatory mechanisms. Using the replica technique, the algorithmic performance can be characterized analytically for artificially generated data. The algorithm is applied to genome-wide expression data of baker's yeast under various environmental conditions. We find clear cases of combinatorial control, and enrichment in common functional annotations of regulated genes and their regulators.

The identification of high-affinity G protein-coupled receptor ligands from large combinatorial libraries using multicolor quantum dot-labeled cell-based screening

PubMed Central

Fu, Junjie; Lee, Timothy; Qi, Xin

2014-01-01

G protein-coupled receptors (GPCRs), which are involved in virtually every biological process, constitute the largest family of transmembrane receptors. Many top-selling and newly approved drugs target GPCRs. In this review, we aim to recapitulate efforts and progress in combinatorial library-assisted GPCR ligand discovery, particularly focusing on one-bead-one-compound library synthesis and quantum dot-labeled cell-based assays, which both effectively enhance the rapid identification of GPCR ligands with higher affinity and specificity. PMID:24941874

Design of diversity and focused combinatorial libraries in drug discovery.

PubMed

Young, S Stanley; Ge, Nanxiang

2004-05-01

Using well-characterized chemical reactions and readily available monomers, chemists are able to create sets of compounds, termed libraries, which are useful in drug discovery processes. The design of combinatorial chemical libraries can be complex and there has been much information recently published offering suggestions on how the design process can be carried out. This review focuses on literature with the goal of organizing current thinking. At this point in time, it is clear that benchmarking of current suggested methods is required as opposed to further new methods.

Modulating weak interactions for molecular recognition: a dynamic combinatorial analysis for assessing the contribution of electrostatics to the stability of CH-π bonds in water.

PubMed

Jiménez-Moreno, Ester; Gómez, Ana M; Bastida, Agatha; Corzana, Francisco; Jiménez-Oses, Gonzalo; Jiménez-Barbero, Jesús; Asensio, Juan Luis

2015-03-27

Electrostatic and charge-transfer contributions to CH-π complexes can be modulated by attaching electron-withdrawing substituents to the carbon atom. While clearly stabilizing in the gas phase, the outcome of this chemical modification in water is more difficult to predict. Herein we provide a definitive and quantitative answer to this question employing a simple strategy based on dynamic combinatorial chemistry. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Learning to generate combinatorial action sequences utilizing the initial sensitivity of deterministic dynamical systems.

PubMed

Nishimoto, Ryu; Tani, Jun

2004-09-01

This study shows how sensory-action sequences of imitating finite state machines (FSMs) can be learned by utilizing the deterministic dynamics of recurrent neural networks (RNNs). Our experiments indicated that each possible combinatorial sequence can be recalled by specifying its respective initial state value and also that fractal structures appear in this initial state mapping after the learning converges. We also observed that the sequences of mimicking FSMs are encoded utilizing the transient regions rather than the invariant sets of the evolved dynamical systems of the RNNs.

Extremal problems for topological indices in combinatorial chemistry.

PubMed

Tichy, Robert F; Wagner, Stephan

2005-09-01

Topological indices of molecular graphs are related to several physicochemical characteristics; recently, the inverse problem for some of these indices has been studied, and it has some applications in the design of combinatorial libraries for drug discovery. It is thus very natural to study also extremal problems for these indices, i.e., finding graphs having minimal or maximal index. In this paper, these questions will be discussed for three different indices, namely the sigma-index, the c-index and the Z-index, with emphasis on the sigma-index.

Toward a characterization of landscapes of combinatorial optimization problems, with special attention to the phylogeny problem.

PubMed

Charleston, M A

1995-01-01

This article introduces a coherent language base for describing and working with characteristics of combinatorial optimization problems, which is at once general enough to be used in all such problems and precise enough to allow subtle concepts in this field to be discussed unambiguously. An example is provided of how this nomenclature is applied to an instance of the phylogeny problem. Also noted is the beneficial effect, on the landscape of the solution space, of transforming the observed data to account for multiple changes of character state.

A Winner Determination Algorithm for Combinatorial Auctions Based on Hybrid Artificial Fish Swarm Algorithm

NASA Astrophysics Data System (ADS)

Zheng, Genrang; Lin, ZhengChun

The problem of winner determination in combinatorial auctions is a hotspot electronic business, and a NP hard problem. A Hybrid Artificial Fish Swarm Algorithm(HAFSA), which is combined with First Suite Heuristic Algorithm (FSHA) and Artificial Fish Swarm Algorithm (AFSA), is proposed to solve the problem after probing it base on the theories of AFSA. Experiment results show that the HAFSA is a rapidly and efficient algorithm for The problem of winner determining. Compared with Ant colony Optimization Algorithm, it has a good performance with broad and prosperous application.

Real-time monitoring of surface-initiated atom transfer radical polymerization using silicon photonic microring resonators: implications for combinatorial screening of polymer brush growth conditions.

PubMed

Limpoco, F Ted; Bailey, Ryan C

2011-09-28

We directly monitor in parallel and in real time the temporal profiles of polymer brushes simultaneously grown via multiple ATRP reaction conditions on a single substrate using arrays of silicon photonic microring resonators. In addition to probing relative polymerization rates, we show the ability to evaluate the dynamic properties of the in situ grown polymers. This presents a powerful new platform for studying modified interfaces that may allow for the combinatorial optimization of surface-initiated polymerization conditions.