Recognition of Yeast Species from Gene Sequence Comparisons

USDA-ARS?s Scientific Manuscript database

This review discusses recognition of yeast species from gene sequence comparisons, which have been responsible for doubling the number of known yeasts over the past decade. The resolution provided by various single gene sequences is examined for both ascomycetous and basidiomycetous species, and th...

Haloarcula hispanica CRISPR authenticates PAM of a target sequence to prime discriminative adaptation

PubMed Central

Li, Ming; Wang, Rui; Xiang, Hua

2014-01-01

The prokaryotic immune system CRISPR/Cas (Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated genes) adapts to foreign invaders by acquiring their short deoxyribonucleic acid (DNA) fragments as spacers, which guide subsequent interference to foreign nucleic acids based on sequence matching. The adaptation mechanism avoiding acquiring ‘self’ DNA fragments is poorly understood. In Haloarcula hispanica, we previously showed that CRISPR adaptation requires being primed by a pre-existing spacer partially matching the invader DNA. Here, we further demonstrate that flanking a fully-matched target sequence, a functional PAM (protospacer adjacent motif) is still required to prime adaptation. Interestingly, interference utilizes only four PAM sequences, whereas adaptation-priming tolerates as many as 23 PAM sequences. This relaxed PAM selectivity explains how adaptation-priming maximizes its tolerance of PAM mutations (that escape interference) while avoiding mis-targeting the spacer DNA within CRISPR locus. We propose that the primed adaptation, which hitches and cooperates with the interference pathway, distinguishes target from non-target by CRISPR ribonucleic acid guidance and PAM recognition. PMID:24803673

Active Multimodal Sensor System for Target Recognition and Tracking

PubMed Central

Zhang, Guirong; Zou, Zhaofan; Liu, Ziyue; Mao, Jiansen

2017-01-01

High accuracy target recognition and tracking systems using a single sensor or a passive multisensor set are susceptible to external interferences and exhibit environmental dependencies. These difficulties stem mainly from limitations to the available imaging frequency bands, and a general lack of coherent diversity of the available target-related data. This paper proposes an active multimodal sensor system for target recognition and tracking, consisting of a visible, an infrared, and a hyperspectral sensor. The system makes full use of its multisensor information collection abilities; furthermore, it can actively control different sensors to collect additional data, according to the needs of the real-time target recognition and tracking processes. This level of integration between hardware collection control and data processing is experimentally shown to effectively improve the accuracy and robustness of the target recognition and tracking system. PMID:28657609

Fast cat-eye effect target recognition based on saliency extraction

NASA Astrophysics Data System (ADS)

Li, Li; Ren, Jianlin; Wang, Xingbin

2015-09-01

Background complexity is a main reason that results in false detection in cat-eye target recognition. Human vision has selective attention property which can help search the salient target from complex unknown scenes quickly and precisely. In the paper, we propose a novel cat-eye effect target recognition method named Multi-channel Saliency Processing before Fusion (MSPF). This method combines traditional cat-eye target recognition with the selective characters of visual attention. Furthermore, parallel processing enables it to achieve fast recognition. Experimental results show that the proposed method performs better in accuracy, robustness and speed compared to other methods.

Invariant recognition drives neural representations of action sequences

PubMed Central

Poggio, Tomaso

2017-01-01

Recognizing the actions of others from visual stimuli is a crucial aspect of human perception that allows individuals to respond to social cues. Humans are able to discriminate between similar actions despite transformations, like changes in viewpoint or actor, that substantially alter the visual appearance of a scene. This ability to generalize across complex transformations is a hallmark of human visual intelligence. Advances in understanding action recognition at the neural level have not always translated into precise accounts of the computational principles underlying what representations of action sequences are constructed by human visual cortex. Here we test the hypothesis that invariant action discrimination might fill this gap. Recently, the study of artificial systems for static object perception has produced models, Convolutional Neural Networks (CNNs), that achieve human level performance in complex discriminative tasks. Within this class, architectures that better support invariant object recognition also produce image representations that better match those implied by human and primate neural data. However, whether these models produce representations of action sequences that support recognition across complex transformations and closely follow neural representations of actions remains unknown. Here we show that spatiotemporal CNNs accurately categorize video stimuli into action classes, and that deliberate model modifications that improve performance on an invariant action recognition task lead to data representations that better match human neural recordings. Our results support our hypothesis that performance on invariant discrimination dictates the neural representations of actions computed in the brain. These results broaden the scope of the invariant recognition framework for understanding visual intelligence from perception of inanimate objects and faces in static images to the study of human perception of action sequences. PMID:29253864

Constraints in distortion-invariant target recognition system simulation

NASA Astrophysics Data System (ADS)

Iftekharuddin, Khan M.; Razzaque, Md A.

2000-11-01

Automatic target recognition (ATR) is a mature but active research area. In an earlier paper, we proposed a novel ATR approach for recognition of targets varying in fine details, rotation, and translation using a Learning Vector Quantization (LVQ) Neural Network (NN). The proposed approach performed segmentation of multiple objects and the identification of the objects using LVQNN. In this current paper, we extend the previous approach for recognition of targets varying in rotation, translation, scale, and combination of all three distortions. We obtain the analytical results of the system level design to show that the approach performs well with some constraints. The first constraint determines the size of the input images and input filters. The second constraint shows the limits on amount of rotation, translation, and scale of input objects. We present the simulation verification of the constraints using DARPA's Moving and Stationary Target Recognition (MSTAR) images with different depression and pose angles. The simulation results using MSTAR images verify the analytical constraints of the system level design.

Attention-Based Recurrent Temporal Restricted Boltzmann Machine for Radar High Resolution Range Profile Sequence Recognition.

PubMed

Zhang, Yifan; Gao, Xunzhang; Peng, Xuan; Ye, Jiaqi; Li, Xiang

2018-05-16

The High Resolution Range Profile (HRRP) recognition has attracted great concern in the field of Radar Automatic Target Recognition (RATR). However, traditional HRRP recognition methods failed to model high dimensional sequential data efficiently and have a poor anti-noise ability. To deal with these problems, a novel stochastic neural network model named Attention-based Recurrent Temporal Restricted Boltzmann Machine (ARTRBM) is proposed in this paper. RTRBM is utilized to extract discriminative features and the attention mechanism is adopted to select major features. RTRBM is efficient to model high dimensional HRRP sequences because it can extract the information of temporal and spatial correlation between adjacent HRRPs. The attention mechanism is used in sequential data recognition tasks including machine translation and relation classification, which makes the model pay more attention to the major features of recognition. Therefore, the combination of RTRBM and the attention mechanism makes our model effective for extracting more internal related features and choose the important parts of the extracted features. Additionally, the model performs well with the noise corrupted HRRP data. Experimental results on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset show that our proposed model outperforms other traditional methods, which indicates that ARTRBM extracts, selects, and utilizes the correlation information between adjacent HRRPs effectively and is suitable for high dimensional data or noise corrupted data.

Shape and texture fused recognition of flying targets

NASA Astrophysics Data System (ADS)

Kovács, Levente; Utasi, Ákos; Kovács, Andrea; Szirányi, Tamás

2011-06-01

This paper presents visual detection and recognition of flying targets (e.g. planes, missiles) based on automatically extracted shape and object texture information, for application areas like alerting, recognition and tracking. Targets are extracted based on robust background modeling and a novel contour extraction approach, and object recognition is done by comparisons to shape and texture based query results on a previously gathered real life object dataset. Application areas involve passive defense scenarios, including automatic object detection and tracking with cheap commodity hardware components (CPU, camera and GPS).

Test Sequence Priming in Recognition Memory

ERIC Educational Resources Information Center

Johns, Elizabeth E.; Mewhort, D. J. K.

2009-01-01

The authors examined priming within the test sequence in 3 recognition memory experiments. A probe primed its successor whenever both probes shared a feature with the same studied item ("interjacent priming"), indicating that the study item like the probe is central to the decision. Interjacent priming occurred even when the 2 probes did…

Component-based target recognition inspired by human vision

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Agyepong, Kwabena

2009-05-01

In contrast with machine vision, human can recognize an object from complex background with great flexibility. For example, given the task of finding and circling all cars (no further information) in a picture, you may build a virtual image in mind from the task (or target) description before looking at the picture. Specifically, the virtual car image may be composed of the key components such as driver cabin and wheels. In this paper, we propose a component-based target recognition method by simulating the human recognition process. The component templates (equivalent to the virtual image in mind) of the target (car) are manually decomposed from the target feature image. Meanwhile, the edges of the testing image can be extracted by using a difference of Gaussian (DOG) model that simulates the spatiotemporal response in visual process. A phase correlation matching algorithm is then applied to match the templates with the testing edge image. If all key component templates are matched with the examining object, then this object is recognized as the target. Besides the recognition accuracy, we will also investigate if this method works with part targets (half cars). In our experiments, several natural pictures taken on streets were used to test the proposed method. The preliminary results show that the component-based recognition method is very promising.

Identification of Biomolecular Building Blocks by Recognition Tunneling: Stride towards Nanopore Sequencing of Biomolecules

NASA Astrophysics Data System (ADS)

Sen, Suman

DNA, RNA and Protein are three pivotal biomolecules in human and other organisms, playing decisive roles in functionality, appearance, diseases development and other physiological phenomena. Hence, sequencing of these biomolecules acquires the prime interest in the scientific community. Single molecular identification of their building blocks can be done by a technique called Recognition Tunneling (RT) based on Scanning Tunneling Microscope (STM). A single layer of specially designed recognition molecule is attached to the STM electrodes, which trap the targeted molecules (DNA nucleoside monophosphates, RNA nucleoside monophosphates or amino acids) inside the STM nanogap. Depending on their different binding interactions with the recognition molecules, the analyte molecules generate stochastic signal trains accommodating their "electronic fingerprints". Signal features are used to detect the molecules using a machine learning algorithm and different molecules can be identified with significantly high accuracy. This, in turn, paves the way for rapid, economical nanopore sequencing platform, overcoming the drawbacks of Next Generation Sequencing (NGS) techniques. To read DNA nucleotides with high accuracy in an STM tunnel junction a series of nitrogen-based heterocycles were designed and examined to check their capabilities to interact with naturally occurring DNA nucleotides by hydrogen bonding in the tunnel junction. These recognition molecules are Benzimidazole, Imidazole, Triazole and Pyrrole. Benzimidazole proved to be best among them showing DNA nucleotide classification accuracy close to 99%. Also, Imidazole reader can read an abasic monophosphate (AP), a product from depurination or depyrimidination that occurs 10,000 times per human cell per day. In another study, I have investigated a new universal reader, 1-(2-mercaptoethyl)pyrene (Pyrene reader) based on stacking interactions, which should be more specific to the canonical DNA nucleosides. In addition

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures

PubMed Central

Pi, Yiming

2017-01-01

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar. PMID:29267249

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures.

PubMed

Zhou, Zhi; Cao, Zongjie; Pi, Yiming

2017-12-21

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar.

Automated target recognition and tracking using an optical pattern recognition neural network

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

1991-01-01

The on-going development of an automatic target recognition and tracking system at the Jet Propulsion Laboratory is presented. This system is an optical pattern recognition neural network (OPRNN) that is an integration of an innovative optical parallel processor and a feature extraction based neural net training algorithm. The parallel optical processor provides high speed and vast parallelism as well as full shift invariance. The neural network algorithm enables simultaneous discrimination of multiple noisy targets in spite of their scales, rotations, perspectives, and various deformations. This fully developed OPRNN system can be effectively utilized for the automated spacecraft recognition and tracking that will lead to success in the Automated Rendezvous and Capture (AR&C) of the unmanned Cargo Transfer Vehicle (CTV). One of the most powerful optical parallel processors for automatic target recognition is the multichannel correlator. With the inherent advantages of parallel processing capability and shift invariance, multiple objects can be simultaneously recognized and tracked using this multichannel correlator. This target tracking capability can be greatly enhanced by utilizing a powerful feature extraction based neural network training algorithm such as the neocognitron. The OPRNN, currently under investigation at JPL, is constructed with an optical multichannel correlator where holographic filters have been prepared using the neocognitron training algorithm. The computation speed of the neocognitron-type OPRNN is up to 10(exp 14) analog connections/sec that enabling the OPRNN to outperform its state-of-the-art electronics counterpart by at least two orders of magnitude.

Composite Wavelet Filters for Enhanced Automated Target Recognition

NASA Technical Reports Server (NTRS)

Chiang, Jeffrey N.; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2012-01-01

Automated Target Recognition (ATR) systems aim to automate target detection, recognition, and tracking. The current project applies a JPL ATR system to low-resolution sonar and camera videos taken from unmanned vehicles. These sonar images are inherently noisy and difficult to interpret, and pictures taken underwater are unreliable due to murkiness and inconsistent lighting. The ATR system breaks target recognition into three stages: 1) Videos of both sonar and camera footage are broken into frames and preprocessed to enhance images and detect Regions of Interest (ROIs). 2) Features are extracted from these ROIs in preparation for classification. 3) ROIs are classified as true or false positives using a standard Neural Network based on the extracted features. Several preprocessing, feature extraction, and training methods are tested and discussed in this paper.

Noise-robust speech recognition through auditory feature detection and spike sequence decoding.

PubMed

Schafer, Phillip B; Jin, Dezhe Z

2014-03-01

Speech recognition in noisy conditions is a major challenge for computer systems, but the human brain performs it routinely and accurately. Automatic speech recognition (ASR) systems that are inspired by neuroscience can potentially bridge the performance gap between humans and machines. We present a system for noise-robust isolated word recognition that works by decoding sequences of spikes from a population of simulated auditory feature-detecting neurons. Each neuron is trained to respond selectively to a brief spectrotemporal pattern, or feature, drawn from the simulated auditory nerve response to speech. The neural population conveys the time-dependent structure of a sound by its sequence of spikes. We compare two methods for decoding the spike sequences--one using a hidden Markov model-based recognizer, the other using a novel template-based recognition scheme. In the latter case, words are recognized by comparing their spike sequences to template sequences obtained from clean training data, using a similarity measure based on the length of the longest common sub-sequence. Using isolated spoken digits from the AURORA-2 database, we show that our combined system outperforms a state-of-the-art robust speech recognizer at low signal-to-noise ratios. Both the spike-based encoding scheme and the template-based decoding offer gains in noise robustness over traditional speech recognition methods. Our system highlights potential advantages of spike-based acoustic coding and provides a biologically motivated framework for robust ASR development.

Detection and recognition of targets by using signal polarization properties

NASA Astrophysics Data System (ADS)

Ponomaryov, Volodymyr I.; Peralta-Fabi, Ricardo; Popov, Anatoly V.; Babakov, Mikhail F.

1999-08-01

The quality of radar target recognition can be enhanced by exploiting its polarization signatures. A specialized X-band polarimetric radar was used for target recognition in experimental investigations. The following polarization characteristics connected to the object geometrical properties were investigated: the amplitudes of the polarization matrix elements; an anisotropy coefficient; depolarization coefficient; asymmetry coefficient; the energy of a backscattering signal; object shape factor. A large quantity of polarimetric radar data was measured and processed to form a database of different object and different weather conditions. The histograms of polarization signatures were approximated by a Nakagami distribution, then used for real- time target recognition. The Neyman-Pearson criterion was used for the target detection, and the criterion of the maximum of a posterior probability was used for recognition problem. Some results of experimental verification of pattern recognition and detection of objects with different electrophysical and geometrical characteristics urban in clutter are presented in this paper.

Use of designed sequences in protein structure recognition.

PubMed

Kumar, Gayatri; Mudgal, Richa; Srinivasan, Narayanaswamy; Sandhya, Sankaran

2018-05-09

Knowledge of the protein structure is a pre-requisite for improved understanding of molecular function. The gap in the sequence-structure space has increased in the post-genomic era. Grouping related protein sequences into families can aid in narrowing the gap. In the Pfam database, structure description is provided for part or full-length proteins of 7726 families. For the remaining 52% of the families, information on 3-D structure is not yet available. We use the computationally designed sequences that are intermediately related to two protein domain families, which are already known to share the same fold. These strategically designed sequences enable detection of distant relationships and here, we have employed them for the purpose of structure recognition of protein families of yet unknown structure. We first measured the success rate of our approach using a dataset of protein families of known fold and achieved a success rate of 88%. Next, for 1392 families of yet unknown structure, we made structural assignments for part/full length of the proteins. Fold association for 423 domains of unknown function (DUFs) are provided as a step towards functional annotation. The results indicate that knowledge-based filling of gaps in protein sequence space is a lucrative approach for structure recognition. Such sequences assist in traversal through protein sequence space and effectively function as 'linkers', where natural linkers between distant proteins are unavailable. This article was reviewed by Oliviero Carugo, Christine Orengo and Srikrishna Subramanian.

Extended target recognition in cognitive radar networks.

PubMed

Wei, Yimin; Meng, Huadong; Liu, Yimin; Wang, Xiqin

2010-01-01

We address the problem of adaptive waveform design for extended target recognition in cognitive radar networks. A closed-loop active target recognition radar system is extended to the case of a centralized cognitive radar network, in which a generalized likelihood ratio (GLR) based sequential hypothesis testing (SHT) framework is employed. Using Doppler velocities measured by multiple radars, the target aspect angle for each radar is calculated. The joint probability of each target hypothesis is then updated using observations from different radar line of sights (LOS). Based on these probabilities, a minimum correlation algorithm is proposed to adaptively design the transmit waveform for each radar in an amplitude fluctuation situation. Simulation results demonstrate performance improvements due to the cognitive radar network and adaptive waveform design. Our minimum correlation algorithm outperforms the eigen-waveform solution and other non-cognitive waveform design approaches.

Target recognition based on convolutional neural network

NASA Astrophysics Data System (ADS)

Wang, Liqiang; Wang, Xin; Xi, Fubiao; Dong, Jian

2017-11-01

One of the important part of object target recognition is the feature extraction, which can be classified into feature extraction and automatic feature extraction. The traditional neural network is one of the automatic feature extraction methods, while it causes high possibility of over-fitting due to the global connection. The deep learning algorithm used in this paper is a hierarchical automatic feature extraction method, trained with the layer-by-layer convolutional neural network (CNN), which can extract the features from lower layers to higher layers. The features are more discriminative and it is beneficial to the object target recognition.

Laser range profiling for small target recognition

NASA Astrophysics Data System (ADS)

Steinvall, Ove; Tulldahl, Michael

2016-05-01

The detection and classification of small surface and airborne targets at long ranges is a growing need for naval security. Long range ID or ID at closer range of small targets has its limitations in imaging due to the demand on very high transverse sensor resolution. It is therefore motivated to look for 1D laser techniques for target ID. These include vibrometry, and laser range profiling. Vibrometry can give good results but is also sensitive to certain vibrating parts on the target being in the field of view. Laser range profiling is attractive because the maximum range can be substantial, especially for a small laser beam width. A range profiler can also be used in a scanning mode to detect targets within a certain sector. The same laser can also be used for active imaging when the target comes closer and is angular resolved. The present paper will show both experimental and simulated results for laser range profiling of small boats out to 6-7 km range and a UAV mockup at close range (1.3 km). We obtained good results with the profiling system both for target detection and recognition. Comparison of experimental and simulated range waveforms based on CAD models of the target support the idea of having a profiling system as a first recognition sensor and thus narrowing the search space for the automatic target recognition based on imaging at close ranges. The naval experiments took place in the Baltic Sea with many other active and passive EO sensors beside the profiling system. Discussion of data fusion between laser profiling and imaging systems will be given. The UAV experiments were made from the rooftop laboratory at FOI.

Microfluidic droplet enrichment for targeted sequencing

PubMed Central

Eastburn, Dennis J.; Huang, Yong; Pellegrino, Maurizio; Sciambi, Adam; Ptáček, Louis J.; Abate, Adam R.

2015-01-01

Targeted sequence enrichment enables better identification of genetic variation by providing increased sequencing coverage for genomic regions of interest. Here, we report the development of a new target enrichment technology that is highly differentiated from other approaches currently in use. Our method, MESA (Microfluidic droplet Enrichment for Sequence Analysis), isolates genomic DNA fragments in microfluidic droplets and performs TaqMan PCR reactions to identify droplets containing a desired target sequence. The TaqMan positive droplets are subsequently recovered via dielectrophoretic sorting, and the TaqMan amplicons are removed enzymatically prior to sequencing. We demonstrated the utility of this approach by generating an average 31.6-fold sequence enrichment across 250 kb of targeted genomic DNA from five unique genomic loci. Significantly, this enrichment enabled a more comprehensive identification of genetic polymorphisms within the targeted loci. MESA requires low amounts of input DNA, minimal prior locus sequence information and enriches the target region without PCR bias or artifacts. These features make it well suited for the study of genetic variation in a number of research and diagnostic applications. PMID:25873629

Simian T Lymphotropic Virus 1 Infection of Papio anubis: tax Sequence Heterogeneity and T Cell Recognition.

PubMed

Termini, James M; Magnani, Diogo M; Maxwell, Helen S; Lauer, William; Castro, Iris; Pecotte, Jerilyn; Barber, Glen N; Watkins, David I; Desrosiers, Ronald C

2017-10-15

Baboons naturally infected with simian T lymphotropic virus (STLV) are a potentially useful model system for the study of vaccination against human T lymphotropic virus (HTLV). Here we expanded the number of available full-length baboon STLV-1 sequences from one to three and related the T cell responses that recognize the immunodominant Tax protein to the tax sequences present in two individual baboons. Continuously growing T cell lines were established from two baboons, animals 12141 and 12752. Next-generation sequencing (NGS) of complete STLV genome sequences from these T cell lines revealed them to be closely related but distinct from each other and from the baboon STLV-1 sequence in the NCBI sequence database. Overlapping peptides corresponding to each unique Tax sequence and to the reference baboon Tax sequence were used to analyze recognition by T cells from each baboon using intracellular cytokine staining (ICS). Individual baboons expressed more gamma interferon and tumor necrosis factor alpha in response to Tax peptides corresponding to their own STLV-1 sequence than in response to Tax peptides corresponding to the reference baboon STLV-1 sequence. Thus, our analyses revealed distinct but closely related STLV-1 genome sequences in two baboons, extremely low heterogeneity of STLV sequences within each baboon, no evidence for superinfection within each baboon, and a ready ability of T cells in each baboon to recognize circulating Tax sequences. While amino acid substitutions that result in escape from CD8 + T cell recognition were not observed, premature stop codons were observed in 7% and 56% of tax sequences from peripheral blood mononuclear cells from animals 12141 and 12752, respectively. IMPORTANCE It has been estimated that approximately 100,000 people suffer serious morbidity and 10,000 people die each year from the consequences associated with human T lymphotropic virus (HTLV) infection. There are no antiviral drugs and no preventive vaccine. A

Protospacer Adjacent Motif (PAM)-Distal Sequences Engage CRISPR Cas9 DNA Target Cleavage

PubMed Central

Ethier, Sylvain; Schmeing, T. Martin; Dostie, Josée; Pelletier, Jerry

2014-01-01

The clustered regularly interspaced short palindromic repeat (CRISPR)-associated enzyme Cas9 is an RNA-guided nuclease that has been widely adapted for genome editing in eukaryotic cells. However, the in vivo target specificity of Cas9 is poorly understood and most studies rely on in silico predictions to define the potential off-target editing spectrum. Using chromatin immunoprecipitation followed by sequencing (ChIP-seq), we delineate the genome-wide binding panorama of catalytically inactive Cas9 directed by two different single guide (sg) RNAs targeting the Trp53 locus. Cas9:sgRNA complexes are able to load onto multiple sites with short seed regions adjacent to 5′NGG3′ protospacer adjacent motifs (PAM). Yet among 43 ChIP-seq sites harboring seed regions analyzed for mutational status, we find editing only at the intended on-target locus and one off-target site. In vitro analysis of target site recognition revealed that interactions between the 5′ end of the guide and PAM-distal target sequences are necessary to efficiently engage Cas9 nucleolytic activity, providing an explanation for why off-target editing is significantly lower than expected from ChIP-seq data. PMID:25275497

Assembly and analysis of eukaryotic Argonaute–RNA complexes in microRNA-target recognition

PubMed Central

Gan, Hin Hark; Gunsalus, Kristin C.

2015-01-01

Experimental studies have uncovered a variety of microRNA (miRNA)–target duplex structures that include perfect, imperfect and seedless duplexes. However, non-canonical binding modes from imperfect/seedless duplexes are not well predicted by computational approaches, which rely primarily on sequence and secondary structural features, nor have their tertiary structures been characterized because solved structures to date are limited to near perfect, straight duplexes in Argonautes (Agos). Here, we use structural modeling to examine the role of Ago dynamics in assembling viable eukaryotic miRNA-induced silencing complexes (miRISCs). We show that combinations of low-frequency, global modes of motion of Ago domains are required to accommodate RNA duplexes in model human and C. elegans Ago structures. Models of viable miRISCs imply that Ago adopts variable conformations at distinct target sites that generate distorted, imperfect miRNA-target duplexes. Ago's ability to accommodate a duplex is dependent on the region where structural distortions occur: distortions in solvent-exposed seed and 3′-end regions are less likely to produce steric clashes than those in the central duplex region. Energetic analyses of assembled miRISCs indicate that target recognition is also driven by favorable Ago-duplex interactions. Such structural insights into Ago loading and target recognition mechanisms may provide a more accurate assessment of miRNA function. PMID:26432829

Examination of soldier target recognition with direct view optics

NASA Astrophysics Data System (ADS)

Long, Frederick H.; Larkin, Gabriella; Bisordi, Danielle; Dorsey, Shauna; Marianucci, Damien; Goss, Lashawnta; Bastawros, Michael; Misiuda, Paul; Rodgers, Glenn; Mazz, John P.

2017-10-01

Target recognition and identification is a problem of great military and scientific importance. To examine the correlation between target recognition and optical magnification, ten U.S. Army soldiers were tasked with identifying letters on targets at 800 and 1300 meters away. Letters were used since they are a standard method for measuring visual acuity. The letters were approximately 90 cm high, which is the size of a well-known rifle. Four direct view optics with angular magnifications of 1.5x, 4x, 6x, and 9x were used. The goal of this approach was to measure actual probabilities for correct target identification. Previous scientific literature suggests that target recognition can be modeled as a linear response problem in angular frequency space using the established values for the contrast sensitivity function for a healthy human eye and the experimentally measured modulation transfer function of the optic. At the 9x magnification, the soldiers could identify the letters with almost no errors (i.e., 97% probability of correct identification). At lower magnification, errors in letter identification were more frequent. The identification errors were not random but occurred most frequently with a few pairs of letters (e.g., O and Q), which is consistent with the literature for letter recognition. In addition, in the small subject sample of ten soldiers, there was considerable variation in the observer recognition capability at 1.5x and a range of 800 meters. This can be directly attributed to the variation in the observer visual acuity.

Target recognitions in multiple-camera closed-circuit television using color constancy

NASA Astrophysics Data System (ADS)

Soori, Umair; Yuen, Peter; Han, Ji Wen; Ibrahim, Izzati; Chen, Wentao; Hong, Kan; Merfort, Christian; James, David; Richardson, Mark

2013-04-01

People tracking in crowded scenes from closed-circuit television (CCTV) footage has been a popular and challenging task in computer vision. Due to the limited spatial resolution in the CCTV footage, the color of people's dress may offer an alternative feature for their recognition and tracking. However, there are many factors, such as variable illumination conditions, viewing angles, and camera calibration, that may induce illusive modification of intrinsic color signatures of the target. Our objective is to recognize and track targets in multiple camera views using color as the detection feature, and to understand if a color constancy (CC) approach may help to reduce these color illusions due to illumination and camera artifacts and thereby improve target recognition performance. We have tested a number of CC algorithms using various color descriptors to assess the efficiency of target recognition from a real multicamera Imagery Library for Intelligent Detection Systems (i-LIDS) data set. Various classifiers have been used for target detection, and the figure of merit to assess the efficiency of target recognition is achieved through the area under the receiver operating characteristics (AUROC). We have proposed two modifications of luminance-based CC algorithms: one with a color transfer mechanism and the other using a pixel-wise sigmoid function for an adaptive dynamic range compression, a method termed enhanced luminance reflectance CC (ELRCC). We found that both algorithms improve the efficiency of target recognitions substantially better than that of the raw data without CC treatment, and in some cases the ELRCC improves target tracking by over 100% within the AUROC assessment metric. The performance of the ELRCC has been assessed over 10 selected targets from three different camera views of the i-LIDS footage, and the averaged target recognition efficiency over all these targets is found to be improved by about 54% in AUROC after the data are processed by

Local structure preserving sparse coding for infrared target recognition

PubMed Central

Han, Jing; Yue, Jiang; Zhang, Yi; Bai, Lianfa

2017-01-01

Sparse coding performs well in image classification. However, robust target recognition requires a lot of comprehensive template images and the sparse learning process is complex. We incorporate sparsity into a template matching concept to construct a local sparse structure matching (LSSM) model for general infrared target recognition. A local structure preserving sparse coding (LSPSc) formulation is proposed to simultaneously preserve the local sparse and structural information of objects. By adding a spatial local structure constraint into the classical sparse coding algorithm, LSPSc can improve the stability of sparse representation for targets and inhibit background interference in infrared images. Furthermore, a kernel LSPSc (K-LSPSc) formulation is proposed, which extends LSPSc to the kernel space to weaken the influence of the linear structure constraint in nonlinear natural data. Because of the anti-interference and fault-tolerant capabilities, both LSPSc- and K-LSPSc-based LSSM can implement target identification based on a simple template set, which just needs several images containing enough local sparse structures to learn a sufficient sparse structure dictionary of a target class. Specifically, this LSSM approach has stable performance in the target detection with scene, shape and occlusions variations. High performance is demonstrated on several datasets, indicating robust infrared target recognition in diverse environments and imaging conditions. PMID:28323824

An evolution based biosensor receptor DNA sequence generation algorithm.

PubMed

Kim, Eungyeong; Lee, Malrey; Gatton, Thomas M; Lee, Jaewan; Zang, Yupeng

2010-01-01

A biosensor is composed of a bioreceptor, an associated recognition molecule, and a signal transducer that can selectively detect target substances for analysis. DNA based biosensors utilize receptor molecules that allow hybridization with the target analyte. However, most DNA biosensor research uses oligonucleotides as the target analytes and does not address the potential problems of real samples. The identification of recognition molecules suitable for real target analyte samples is an important step towards further development of DNA biosensors. This study examines the characteristics of DNA used as bioreceptors and proposes a hybrid evolution-based DNA sequence generating algorithm, based on DNA computing, to identify suitable DNA bioreceptor recognition molecules for stable hybridization with real target substances. The Traveling Salesman Problem (TSP) approach is applied in the proposed algorithm to evaluate the safety and fitness of the generated DNA sequences. This approach improves efficiency and stability for enhanced and variable-length DNA sequence generation and allows extension to generation of variable-length DNA sequences with diverse receptor recognition requirements.

Feature-based RNN target recognition

NASA Astrophysics Data System (ADS)

Bakircioglu, Hakan; Gelenbe, Erol

1998-09-01

Detection and recognition of target signatures in sensory data obtained by synthetic aperture radar (SAR), forward- looking infrared, or laser radar, have received considerable attention in the literature. In this paper, we propose a feature based target classification methodology to detect and classify targets in cluttered SAR images, that makes use of selective signature data from sensory data, together with a neural network technique which uses a set of trained networks based on the Random Neural Network (RNN) model (Gelenbe 89, 90, 91, 93) which is trained to act as a matched filter. We propose and investigate radial features of target shapes that are invariant to rotation, translation, and scale, to characterize target and clutter signatures. These features are then used to train a set of learning RNNs which can be used to detect targets within clutter with high accuracy, and to classify the targets or man-made objects from natural clutter. Experimental data from SAR imagery is used to illustrate and validate the proposed method, and to calculate Receiver Operating Characteristics which illustrate the performance of the proposed algorithm.

Target recognition and phase acquisition by using incoherent digital holographic imaging

NASA Astrophysics Data System (ADS)

Lee, Munseob; Lee, Byung-Tak

2017-05-01

In this study, we proposed the Incoherent Digital Holographic Imaging (IDHI) for recognition and phase information of dedicated target. Although recent development of a number of target recognition techniques such as LIDAR, there have limited success in target discrimination, in part due to low-resolution, low scanning speed, and computation power. In the paper, the proposed system consists of the incoherent light source, such as LED, Michelson interferometer, and digital CCD for acquisition of four phase shifting image. First of all, to compare with relative coherence, we used a source as laser and LED, respectively. Through numerical reconstruction by using the four phase shifting method and Fresnel diffraction method, we recovered the intensity and phase image of USAF resolution target apart from about 1.0m distance. In this experiment, we show 1.2 times improvement in resolution compared to conventional imaging. Finally, to confirm the recognition result of camouflaged targets with the same color from background, we carry out to test holographic imaging in incoherent light. In this result, we showed the possibility of a target detection and recognition that used three dimensional shape and size signatures, numerical distance from phase information of obtained holographic image.

Emotionally conditioning the target-speech voice enhances recognition of the target speech under "cocktail-party" listening conditions.

PubMed

Lu, Lingxi; Bao, Xiaohan; Chen, Jing; Qu, Tianshu; Wu, Xihong; Li, Liang

2018-05-01

Under a noisy "cocktail-party" listening condition with multiple people talking, listeners can use various perceptual/cognitive unmasking cues to improve recognition of the target speech against informational speech-on-speech masking. One potential unmasking cue is the emotion expressed in a speech voice, by means of certain acoustical features. However, it was unclear whether emotionally conditioning a target-speech voice that has none of the typical acoustical features of emotions (i.e., an emotionally neutral voice) can be used by listeners for enhancing target-speech recognition under speech-on-speech masking conditions. In this study we examined the recognition of target speech against a two-talker speech masker both before and after the emotionally neutral target voice was paired with a loud female screaming sound that has a marked negative emotional valence. The results showed that recognition of the target speech (especially the first keyword in a target sentence) was significantly improved by emotionally conditioning the target speaker's voice. Moreover, the emotional unmasking effect was independent of the unmasking effect of the perceived spatial separation between the target speech and the masker. Also, (skin conductance) electrodermal responses became stronger after emotional learning when the target speech and masker were perceptually co-located, suggesting an increase of listening efforts when the target speech was informationally masked. These results indicate that emotionally conditioning the target speaker's voice does not change the acoustical parameters of the target-speech stimuli, but the emotionally conditioned vocal features can be used as cues for unmasking target speech.

Target Recognition Using Neural Networks for Model Deformation Measurements

NASA Technical Reports Server (NTRS)

Ross, Richard W.; Hibler, David L.

1999-01-01

Optical measurements provide a non-invasive method for measuring deformation of wind tunnel models. Model deformation systems use targets mounted or painted on the surface of the model to identify known positions, and photogrammetric methods are used to calculate 3-D positions of the targets on the model from digital 2-D images. Under ideal conditions, the reflective targets are placed against a dark background and provide high-contrast images, aiding in target recognition. However, glints of light reflecting from the model surface, or reduced contrast caused by light source or model smoothness constraints, can compromise accurate target determination using current algorithmic methods. This paper describes a technique using a neural network and image processing technologies which increases the reliability of target recognition systems. Unlike algorithmic methods, the neural network can be trained to identify the characteristic patterns that distinguish targets from other objects of similar size and appearance and can adapt to changes in lighting and environmental conditions.

Target recognition of ladar range images using even-order Zernike moments.

PubMed

Liu, Zheng-Jun; Li, Qi; Xia, Zhi-Wei; Wang, Qi

2012-11-01

Ladar range images have attracted considerable attention in automatic target recognition fields. In this paper, Zernike moments (ZMs) are applied to classify the target of the range image from an arbitrary azimuth angle. However, ZMs suffer from high computational costs. To improve the performance of target recognition based on small samples, even-order ZMs with serial-parallel backpropagation neural networks (BPNNs) are applied to recognize the target of the range image. It is found that the rotation invariance and classified performance of the even-order ZMs are both better than for odd-order moments and for moments compressed by principal component analysis. The experimental results demonstrate that combining the even-order ZMs with serial-parallel BPNNs can significantly improve the recognition rate for small samples.

Targeted therapy according to next generation sequencing-based panel sequencing.

PubMed

Saito, Motonobu; Momma, Tomoyuki; Kono, Koji

2018-04-17

Targeted therapy against actionable gene mutations shows a significantly higher response rate as well as longer survival compared to conventional chemotherapy, and has become a standard therapy for many cancers. Recent progress in next-generation sequencing (NGS) has enabled to identify huge number of genetic aberrations. Based on sequencing results, patients recommend to undergo targeted therapy or immunotherapy. In cases where there are no available approved drugs for the genetic mutations detected in the patients, it is recommended to be facilitate the registration for the clinical trials. For that purpose, a NGS-based sequencing panel that can simultaneously target multiple genes in a single investigation has been used in daily clinical practice. To date, various types of sequencing panels have been developed to investigate genetic aberrations with tumor somatic genome variants (gain-of-function or loss-of-function mutations, high-level copy number alterations, and gene fusions) through comprehensive bioinformatics. Because sequencing panels are efficient and cost-effective, they are quickly being adopted outside the lab, in hospitals and clinics, in order to identify personal targeted therapy for individual cancer patients.

Application of automatic threshold in dynamic target recognition with low contrast

NASA Astrophysics Data System (ADS)

Miao, Hua; Guo, Xiaoming; Chen, Yu

2014-11-01

Hybrid photoelectric joint transform correlator can realize automatic real-time recognition with high precision through the combination of optical devices and electronic devices. When recognizing targets with low contrast using photoelectric joint transform correlator, because of the difference of attitude, brightness and grayscale between target and template, only four to five frames of dynamic targets can be recognized without any processing. CCD camera is used to capture the dynamic target images and the capturing speed of CCD is 25 frames per second. Automatic threshold has many advantages like fast processing speed, effectively shielding noise interference, enhancing diffraction energy of useful information and better reserving outline of target and template, so this method plays a very important role in target recognition with optical correlation method. However, the automatic obtained threshold by program can not achieve the best recognition results for dynamic targets. The reason is that outline information is broken to some extent. Optimal threshold is obtained by manual intervention in most cases. Aiming at the characteristics of dynamic targets, the processing program of improved automatic threshold is finished by multiplying OTSU threshold of target and template by scale coefficient of the processed image, and combining with mathematical morphology. The optimal threshold can be achieved automatically by improved automatic threshold processing for dynamic low contrast target images. The recognition rate of dynamic targets is improved through decreased background noise effect and increased correlation information. A series of dynamic tank images with the speed about 70 km/h are adapted as target images. The 1st frame of this series of tanks can correlate only with the 3rd frame without any processing. Through OTSU threshold, the 80th frame can be recognized. By automatic threshold processing of the joint images, this number can be increased to 89 frames

Face recognition based on matching of local features on 3D dynamic range sequences

NASA Astrophysics Data System (ADS)

Echeagaray-Patrón, B. A.; Kober, Vitaly

2016-09-01

3D face recognition has attracted attention in the last decade due to improvement of technology of 3D image acquisition and its wide range of applications such as access control, surveillance, human-computer interaction and biometric identification systems. Most research on 3D face recognition has focused on analysis of 3D still data. In this work, a new method for face recognition using dynamic 3D range sequences is proposed. Experimental results are presented and discussed using 3D sequences in the presence of pose variation. The performance of the proposed method is compared with that of conventional face recognition algorithms based on descriptors.

Target recognition of log-polar ladar range images using moment invariants

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Cao, Jie; Yu, Haoyong

2017-01-01

The ladar range image has received considerable attentions in the automatic target recognition field. However, previous research does not cover target recognition using log-polar ladar range images. Therefore, we construct a target recognition system based on log-polar ladar range images in this paper. In this system combined moment invariants and backpropagation neural network are selected as shape descriptor and shape classifier, respectively. In order to fully analyze the effect of log-polar sampling pattern on recognition result, several comparative experiments based on simulated and real range images are carried out. Eventually, several important conclusions are drawn: (i) if combined moments are computed directly by log-polar range images, translation, rotation and scaling invariant properties of combined moments will be invalid (ii) when object is located in the center of field of view, recognition rate of log-polar range images is less sensitive to the changing of field of view (iii) as object position changes from center to edge of field of view, recognition performance of log-polar range images will decline dramatically (iv) log-polar range images has a better noise robustness than Cartesian range images. Finally, we give a suggestion that it is better to divide field of view into recognition area and searching area in the real application.

Crosslinking transcription factors to their recognition sequences with PtII complexes

NASA Technical Reports Server (NTRS)

Chu, B. C.; Orgel, L. E.

1992-01-01

We have prepared phosphorothioate-containing cyclic oligodeoxynucleotides that fold into 'dumbbells' containing CRE and TRE sequences, the binding sequences for the CREB and JUN proteins, respectively. Six phosphorothioate residues were introduced into each of the recognition sequences. K2PtCl4 crosslinks CRE to CREB and TRE to JUN. The extent of crosslinking is about eight times greater than that observed with standard oligodeoxynucleotides and amounts to 30-50% of the efficiency of non-covalent association as estimated by gel-shift assays. Crosslinking is reversed by incubation with NaCN. The crosslinking reaction is specific--a dumbbell oligonucleotide with six phosphorothioate groups introduced into the Sp1 recognition sequence could not be crosslinked efficiently to CREB or JUN proteins with K2PtCl4. The binding of TRE to CREB is not strong enough for effective detection by gel-shift assays, but the TRE-CREB complex is crosslinked efficiently by K2PtCl4 and can then readily be detected.

Combining high-speed SVM learning with CNN feature encoding for real-time target recognition in high-definition video for ISR missions

NASA Astrophysics Data System (ADS)

Kroll, Christine; von der Werth, Monika; Leuck, Holger; Stahl, Christoph; Schertler, Klaus

2017-05-01

For Intelligence, Surveillance, Reconnaissance (ISR) missions of manned and unmanned air systems typical electrooptical payloads provide high-definition video data which has to be exploited with respect to relevant ground targets in real-time by automatic/assisted target recognition software. Airbus Defence and Space is developing required technologies for real-time sensor exploitation since years and has combined the latest advances of Deep Convolutional Neural Networks (CNN) with a proprietary high-speed Support Vector Machine (SVM) learning method into a powerful object recognition system with impressive results on relevant high-definition video scenes compared to conventional target recognition approaches. This paper describes the principal requirements for real-time target recognition in high-definition video for ISR missions and the Airbus approach of combining an invariant feature extraction using pre-trained CNNs and the high-speed training and classification ability of a novel frequency-domain SVM training method. The frequency-domain approach allows for a highly optimized implementation for General Purpose Computation on a Graphics Processing Unit (GPGPU) and also an efficient training of large training samples. The selected CNN which is pre-trained only once on domain-extrinsic data reveals a highly invariant feature extraction. This allows for a significantly reduced adaptation and training of the target recognition method for new target classes and mission scenarios. A comprehensive training and test dataset was defined and prepared using relevant high-definition airborne video sequences. The assessment concept is explained and performance results are given using the established precision-recall diagrams, average precision and runtime figures on representative test data. A comparison to legacy target recognition approaches shows the impressive performance increase by the proposed CNN+SVM machine-learning approach and the capability of real-time high

Cat-eye effect target recognition with single-pixel detectors

NASA Astrophysics Data System (ADS)

Jian, Weijian; Li, Li; Zhang, Xiaoyue

2015-12-01

A prototype of cat-eye effect target recognition with single-pixel detectors is proposed. Based on the framework of compressive sensing, it is possible to recognize cat-eye effect targets by projecting a series of known random patterns and measuring the backscattered light with three single-pixel detectors in different locations. The prototype only requires simpler, less expensive detectors and extends well beyond the visible spectrum. The simulations are accomplished to evaluate the feasibility of the proposed prototype. We compared our results to that obtained from conventional cat-eye effect target recognition methods using area array sensor. The experimental results show that this method is feasible and superior to the conventional method in dynamic and complicated backgrounds.

Model-based recognition of 3D articulated target using ladar range data.

PubMed

Lv, Dan; Sun, Jian-Feng; Li, Qi; Wang, Qi

2015-06-10

Ladar is suitable for 3D target recognition because ladar range images can provide rich 3D geometric surface information of targets. In this paper, we propose a part-based 3D model matching technique to recognize articulated ground military vehicles in ladar range images. The key of this approach is to solve the decomposition and pose estimation of articulated parts of targets. The articulated components were decomposed into isolate parts based on 3D geometric properties of targets, such as surface point normals, data histogram distribution, and data distance relationships. The corresponding poses of these separate parts were estimated through the linear characteristics of barrels. According to these pose parameters, all parts of the target were roughly aligned to 3D point cloud models in a library and fine matching was finally performed to accomplish 3D articulated target recognition. The recognition performance was evaluated with 1728 ladar range images of eight different articulated military vehicles with various part types and orientations. Experimental results demonstrated that the proposed approach achieved a high recognition rate.

Influence of time and length size feature selections for human activity sequences recognition.

PubMed

Fang, Hongqing; Chen, Long; Srinivasan, Raghavendiran

2014-01-01

In this paper, Viterbi algorithm based on a hidden Markov model is applied to recognize activity sequences from observed sensors events. Alternative features selections of time feature values of sensors events and activity length size feature values are tested, respectively, and then the results of activity sequences recognition performances of Viterbi algorithm are evaluated. The results show that the selection of larger time feature values of sensor events and/or smaller activity length size feature values will generate relatively better results on the activity sequences recognition performances. © 2013 ISA Published by ISA All rights reserved.

Object recognition of real targets using modelled SAR images

NASA Astrophysics Data System (ADS)

Zherdev, D. A.

2017-12-01

In this work the problem of recognition is studied using SAR images. The algorithm of recognition is based on the computation of conjugation indices with vectors of class. The support subspaces for each class are constructed by exception of the most and the less correlated vectors in a class. In the study we examine the ability of a significant feature vector size reduce that leads to recognition time decrease. The images of targets form the feature vectors that are transformed using pre-trained convolutional neural network (CNN).

Specific and Modular Binding Code for Cytosine Recognition in Pumilio/FBF (PUF) RNA-binding Domains

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

Dong, Shuyun; Wang, Yang; Cassidy-Amstutz, Caleb

2011-10-28

Pumilio/fem-3 mRNA-binding factor (PUF) proteins possess a recognition code for bases A, U, and G, allowing designed RNA sequence specificity of their modular Pumilio (PUM) repeats. However, recognition side chains in a PUM repeat for cytosine are unknown. Here we report identification of a cytosine-recognition code by screening random amino acid combinations at conserved RNA recognition positions using a yeast three-hybrid system. This C-recognition code is specific and modular as specificity can be transferred to different positions in the RNA recognition sequence. A crystal structure of a modified PUF domain reveals specific contacts between an arginine side chain and themore » cytosine base. We applied the C-recognition code to design PUF domains that recognize targets with multiple cytosines and to generate engineered splicing factors that modulate alternative splicing. Finally, we identified a divergent yeast PUF protein, Nop9p, that may recognize natural target RNAs with cytosine. This work deepens our understanding of natural PUF protein target recognition and expands the ability to engineer PUF domains to recognize any RNA sequence.« less

DNA sequence similarity recognition by hybridization to short oligomers

DOEpatents

Milosavljevic, Aleksandar

1999-01-01

Methods are disclosed for the comparison of nucleic acid sequences. Data is generated by hybridizing sets of oligomers with target nucleic acids. The data thus generated is manipulated simultaneously with respect to both (i) matching between oligomers and (ii) matching between oligomers and putative reference sequences available in databases. Using data compression methods to manipulate this mutual information, sequences for the target can be constructed.

Software for Partly Automated Recognition of Targets

NASA Technical Reports Server (NTRS)

Opitz, David; Blundell, Stuart; Bain, William; Morris, Matthew; Carlson, Ian; Mangrich, Mark; Selinsky, T.

2002-01-01

The Feature Analyst is a computer program for assisted (partially automated) recognition of targets in images. This program was developed to accelerate the processing of high-resolution satellite image data for incorporation into geographic information systems (GIS). This program creates an advanced user interface that embeds proprietary machine-learning algorithms in commercial image-processing and GIS software. A human analyst provides samples of target features from multiple sets of data, then the software develops a data-fusion model that automatically extracts the remaining features from selected sets of data. The program thus leverages the natural ability of humans to recognize objects in complex scenes, without requiring the user to explain the human visual recognition process by means of lengthy software. Two major subprograms are the reactive agent and the thinking agent. The reactive agent strives to quickly learn the user's tendencies while the user is selecting targets and to increase the user's productivity by immediately suggesting the next set of pixels that the user may wish to select. The thinking agent utilizes all available resources, taking as much time as needed, to produce the most accurate autonomous feature-extraction model possible.

Software for Partly Automated Recognition of Targets

NASA Technical Reports Server (NTRS)

Opitz, David; Blundell, Stuart; Bain, William; Morris, Matthew; Carlson, Ian; Mangrich, Mark

2003-01-01

The Feature Analyst is a computer program for assisted (partially automated) recognition of targets in images. This program was developed to accelerate the processing of high-resolution satellite image data for incorporation into geographic information systems (GIS). This program creates an advanced user interface that embeds proprietary machine-learning algorithms in commercial image-processing and GIS software. A human analyst provides samples of target features from multiple sets of data, then the software develops a data-fusion model that automatically extracts the remaining features from selected sets of data. The program thus leverages the natural ability of humans to recognize objects in complex scenes, without requiring the user to explain the human visual recognition process by means of lengthy software. Two major subprograms are the reactive agent and the thinking agent. The reactive agent strives to quickly learn the user s tendencies while the user is selecting targets and to increase the user s productivity by immediately suggesting the next set of pixels that the user may wish to select. The thinking agent utilizes all available resources, taking as much time as needed, to produce the most accurate autonomous feature-extraction model possible.

A Spiking Neural Network System for Robust Sequence Recognition.

PubMed

Yu, Qiang; Yan, Rui; Tang, Huajin; Tan, Kay Chen; Li, Haizhou

2016-03-01

This paper proposes a biologically plausible network architecture with spiking neurons for sequence recognition. This architecture is a unified and consistent system with functional parts of sensory encoding, learning, and decoding. This is the first systematic model attempting to reveal the neural mechanisms considering both the upstream and the downstream neurons together. The whole system is a consistent temporal framework, where the precise timing of spikes is employed for information processing and cognitive computing. Experimental results show that the system is competent to perform the sequence recognition, being robust to noisy sensory inputs and invariant to changes in the intervals between input stimuli within a certain range. The classification ability of the temporal learning rule used in the system is investigated through two benchmark tasks that outperform the other two widely used learning rules for classification. The results also demonstrate the computational power of spiking neurons over perceptrons for processing spatiotemporal patterns. In summary, the system provides a general way with spiking neurons to encode external stimuli into spatiotemporal spikes, to learn the encoded spike patterns with temporal learning rules, and to decode the sequence order with downstream neurons. The system structure would be beneficial for developments in both hardware and software.

Clustered Multi-Task Learning for Automatic Radar Target Recognition

PubMed Central

Li, Cong; Bao, Weimin; Xu, Luping; Zhang, Hua

2017-01-01

Model training is a key technique for radar target recognition. Traditional model training algorithms in the framework of single task leaning ignore the relationships among multiple tasks, which degrades the recognition performance. In this paper, we propose a clustered multi-task learning, which can reveal and share the multi-task relationships for radar target recognition. To further make full use of these relationships, the latent multi-task relationships in the projection space are taken into consideration. Specifically, a constraint term in the projection space is proposed, the main idea of which is that multiple tasks within a close cluster should be close to each other in the projection space. In the proposed method, the cluster structures and multi-task relationships can be autonomously learned and utilized in both of the original and projected space. In view of the nonlinear characteristics of radar targets, the proposed method is extended to a non-linear kernel version and the corresponding non-linear multi-task solving method is proposed. Comprehensive experimental studies on simulated high-resolution range profile dataset and MSTAR SAR public database verify the superiority of the proposed method to some related algorithms. PMID:28953267

A fusion approach for coarse-to-fine target recognition

NASA Astrophysics Data System (ADS)

Folkesson, Martin; Grönwall, Christina; Jungert, Erland

2006-04-01

A fusion approach in a query based information system is presented. The system is designed for querying multimedia data bases, and here applied to target recognition using heterogeneous data sources. The recognition process is coarse-to-fine, with an initial attribute estimation step and a following matching step. Several sensor types and algorithms are involved in each of these two steps. An independence of the matching results, on the origin of the estimation results, is observed. It allows for distribution of data between algorithms in an intermediate fusion step, without risk of data incest. This increases the overall chance of recognising the target. An implementation of the system is described.

A programmable method for massively parallel targeted sequencing

PubMed Central

Hopmans, Erik S.; Natsoulis, Georges; Bell, John M.; Grimes, Susan M.; Sieh, Weiva; Ji, Hanlee P.

2014-01-01

We have developed a targeted resequencing approach referred to as Oligonucleotide-Selective Sequencing. In this study, we report a series of significant improvements and novel applications of this method whereby the surface of a sequencing flow cell is modified in situ to capture specific genomic regions of interest from a sample and then sequenced. These improvements include a fully automated targeted sequencing platform through the use of a standard Illumina cBot fluidics station. Targeting optimization increased the yield of total on-target sequencing data 2-fold compared to the previous iteration, while simultaneously increasing the percentage of reads that could be mapped to the human genome. The described assays cover up to 1421 genes with a total coverage of 5.5 Megabases (Mb). We demonstrate a 10-fold abundance uniformity of greater than 90% in 1 log distance from the median and a targeting rate of up to 95%. We also sequenced continuous genomic loci up to 1.5 Mb while simultaneously genotyping SNPs and genes. Variants with low minor allele fraction were sensitively detected at levels of 5%. Finally, we determined the exact breakpoint sequence of cancer rearrangements. Overall, this approach has high performance for selective sequencing of genome targets, configuration flexibility and variant calling accuracy. PMID:24782526

Analysis and Visualization Tool for Targeted Amplicon Bisulfite Sequencing on Ion Torrent Sequencers

PubMed Central

Pabinger, Stephan; Ernst, Karina; Pulverer, Walter; Kallmeyer, Rainer; Valdes, Ana M.; Metrustry, Sarah; Katic, Denis; Nuzzo, Angelo; Kriegner, Albert; Vierlinger, Klemens; Weinhaeusel, Andreas

2016-01-01

Targeted sequencing of PCR amplicons generated from bisulfite deaminated DNA is a flexible, cost-effective way to study methylation of a sample at single CpG resolution and perform subsequent multi-target, multi-sample comparisons. Currently, no platform specific protocol, support, or analysis solution is provided to perform targeted bisulfite sequencing on a Personal Genome Machine (PGM). Here, we present a novel tool, called TABSAT, for analyzing targeted bisulfite sequencing data generated on Ion Torrent sequencers. The workflow starts with raw sequencing data, performs quality assessment, and uses a tailored version of Bismark to map the reads to a reference genome. The pipeline visualizes results as lollipop plots and is able to deduce specific methylation-patterns present in a sample. The obtained profiles are then summarized and compared between samples. In order to assess the performance of the targeted bisulfite sequencing workflow, 48 samples were used to generate 53 different Bisulfite-Sequencing PCR amplicons from each sample, resulting in 2,544 amplicon targets. We obtained a mean coverage of 282X using 1,196,822 aligned reads. Next, we compared the sequencing results of these targets to the methylation level of the corresponding sites on an Illumina 450k methylation chip. The calculated average Pearson correlation coefficient of 0.91 confirms the sequencing results with one of the industry-leading CpG methylation platforms and shows that targeted amplicon bisulfite sequencing provides an accurate and cost-efficient method for DNA methylation studies, e.g., to provide platform-independent confirmation of Illumina Infinium 450k methylation data. TABSAT offers a novel way to analyze data generated by Ion Torrent instruments and can also be used with data from the Illumina MiSeq platform. It can be easily accessed via the Platomics platform, which offers a web-based graphical user interface along with sample and parameter storage. TABSAT is freely

Target Site Recognition by a Diversity-Generating Retroelement

PubMed Central

Guo, Huatao; Tse, Longping V.; Nieh, Angela W.; Czornyj, Elizabeth; Williams, Steven; Oukil, Sabrina; Liu, Vincent B.; Miller, Jeff F.

2011-01-01

Diversity-generating retroelements (DGRs) are in vivo sequence diversification machines that are widely distributed in bacterial, phage, and plasmid genomes. They function to introduce vast amounts of targeted diversity into protein-encoding DNA sequences via mutagenic homing. Adenine residues are converted to random nucleotides in a retrotransposition process from a donor template repeat (TR) to a recipient variable repeat (VR). Using the Bordetella bacteriophage BPP-1 element as a prototype, we have characterized requirements for DGR target site function. Although sequences upstream of VR are dispensable, a 24 bp sequence immediately downstream of VR, which contains short inverted repeats, is required for efficient retrohoming. The inverted repeats form a hairpin or cruciform structure and mutational analysis demonstrated that, while the structure of the stem is important, its sequence can vary. In contrast, the loop has a sequence-dependent function. Structure-specific nuclease digestion confirmed the existence of a DNA hairpin/cruciform, and marker coconversion assays demonstrated that it influences the efficiency, but not the site of cDNA integration. Comparisons with other phage DGRs suggested that similar structures are a conserved feature of target sequences. Using a kanamycin resistance determinant as a reporter, we found that transplantation of the IMH and hairpin/cruciform-forming region was sufficient to target the DGR diversification machinery to a heterologous gene. In addition to furthering our understanding of DGR retrohoming, our results suggest that DGRs may provide unique tools for directed protein evolution via in vivo DNA diversification. PMID:22194701

Testing Saliency Parameters for Automatic Target Recognition

NASA Technical Reports Server (NTRS)

Pandya, Sagar

2012-01-01

A bottom-up visual attention model (the saliency model) is tested to enhance the performance of Automated Target Recognition (ATR). JPL has developed an ATR system that identifies regions of interest (ROI) using a trained OT-MACH filter, and then classifies potential targets as true- or false-positives using machine-learning techniques. In this project, saliency is used as a pre-processing step to reduce the space for performing OT-MACH filtering. Saliency parameters, such as output level and orientation weight, are tuned to detect known target features. Preliminary results are promising and future work entails a rigrous and parameter-based search to gain maximum insight about this method.

A novel rotational invariants target recognition method for rotating motion blurred images

NASA Astrophysics Data System (ADS)

Lan, Jinhui; Gong, Meiling; Dong, Mingwei; Zeng, Yiliang; Zhang, Yuzhen

2017-11-01

The imaging of the image sensor is blurred due to the rotational motion of the carrier and reducing the target recognition rate greatly. Although the traditional mode that restores the image first and then identifies the target can improve the recognition rate, it takes a long time to recognize. In order to solve this problem, a rotating fuzzy invariants extracted model was constructed that recognizes target directly. The model includes three metric layers. The object description capability of metric algorithms that contain gray value statistical algorithm, improved round projection transformation algorithm and rotation-convolution moment invariants in the three metric layers ranges from low to high, and the metric layer with the lowest description ability among them is as the input which can eliminate non pixel points of target region from degenerate image gradually. Experimental results show that the proposed model can improve the correct target recognition rate of blurred image and optimum allocation between the computational complexity and function of region.

Radioligand Recognition of Insecticide Targets.

PubMed

Casida, John E

2018-04-04

Insecticide radioligands allow the direct recognition and analysis of the targets and mechanisms of toxic action critical to effective and safe pest control. These radioligands are either the insecticides themselves or analogs that bind at the same or coupled sites. Preferred radioligands and their targets, often in both insects and mammals, are trioxabicyclooctanes for the γ-aminobutyric acid (GABA) receptor, avermectin for the glutamate receptor, imidacloprid for the nicotinic receptor, ryanodine and chlorantraniliprole for the ryanodine receptor, and rotenone or pyridaben for NADH + ubiquinone oxidoreductase. Pyrethroids and other Na + channel modulator insecticides are generally poor radioligands due to lipophilicity and high nonspecific binding. For target site validation, the structure-activity relationships competing with the radioligand in the binding assays should be the same as that for insecticidal activity or toxicity except for rapidly detoxified or proinsecticide analogs. Once the radioligand assay is validated for relevance, it will often help define target site modifications on selection of resistant pest strains, selectivity between insects and mammals, and interaction with antidotes and other chemicals at modulator sites. Binding assays also serve for receptor isolation and photoaffinity labeling to characterize the interactions involved.

One recognition sequence, seven restriction enzymes, five reaction mechanisms

PubMed Central

Gowers, Darren M.; Bellamy, Stuart R.W.; Halford, Stephen E.

2004-01-01

The diversity of reaction mechanisms employed by Type II restriction enzymes was investigated by analysing the reactions of seven endonucleases at the same DNA sequence. NarI, KasI, Mly113I, SfoI, EgeI, EheI and BbeI cleave DNA at several different positions in the sequence 5′-GGCGCC-3′. Their reactions on plasmids with one or two copies of this sequence revealed five distinct mechanisms. These differ in terms of the number of sites the enzyme binds, and the number of phosphodiester bonds cleaved per turnover. NarI binds two sites, but cleaves only one bond per DNA-binding event. KasI also cuts only one bond per turnover but acts at individual sites, preferring intact to nicked sites. Mly113I cuts both strands of its recognition sites, but shows full activity only when bound to two sites, which are then cleaved concertedly. SfoI, EgeI and EheI cut both strands at individual sites, in the manner historically considered as normal for Type II enzymes. Finally, BbeI displays an absolute requirement for two sites in close physical proximity, which are cleaved concertedly. The range of reaction mechanisms for restriction enzymes is thus larger than commonly imagined, as is the number of enzymes needing two recognition sites. PMID:15226412

On-chip learning of hyper-spectral data for real time target recognition

NASA Technical Reports Server (NTRS)

Duong, T. A.; Daud, T.; Thakoor, A.

2000-01-01

As the focus of our present paper, we have used the cascade error projection (CEP) learning algorithm (shown to be hardware-implementable) with on-chip learning (OCL) scheme to obtain three orders of magnitude speed-up in target recognition compared to software-based learning schemes. Thus, it is shown, real time learning as well as data processing for target recognition can be achieved.

Gaussian mixture models-based ship target recognition algorithm in remote sensing infrared images

NASA Astrophysics Data System (ADS)

Yao, Shoukui; Qin, Xiaojuan

2018-02-01

Since the resolution of remote sensing infrared images is low, the features of ship targets become unstable. The issue of how to recognize ships with fuzzy features is an open problem. In this paper, we propose a novel ship target recognition algorithm based on Gaussian mixture models (GMMs). In the proposed algorithm, there are mainly two steps. At the first step, the Hu moments of these ship target images are calculated, and the GMMs are trained on the moment features of ships. At the second step, the moment feature of each ship image is assigned to the trained GMMs for recognition. Because of the scale, rotation, translation invariance property of Hu moments and the power feature-space description ability of GMMs, the GMMs-based ship target recognition algorithm can recognize ship reliably. Experimental results of a large simulating image set show that our approach is effective in distinguishing different ship types, and obtains a satisfactory ship recognition performance.

Single-Molecule View of Small RNA-Guided Target Search and Recognition.

PubMed

Globyte, Viktorija; Kim, Sung Hyun; Joo, Chirlmin

2018-05-20

Most everyday processes in life involve a necessity for an entity to locate its target. On a cellular level, many proteins have to find their target to perform their function. From gene-expression regulation to DNA repair to host defense, numerous nucleic acid-interacting proteins use distinct target search mechanisms. Several proteins achieve that with the help of short RNA strands known as guides. This review focuses on single-molecule advances studying the target search and recognition mechanism of Argonaute and CRISPR (clustered regularly interspaced short palindromic repeats) systems. We discuss different steps involved in search and recognition, from the initial complex prearrangement into the target-search competent state to the final proofreading steps. We focus on target search mechanisms that range from weak interactions, to one- and three-dimensional diffusion, to conformational proofreading. We compare the mechanisms of Argonaute and CRISPR with a well-studied target search system, RecA.

TRACX: A Recognition-Based Connectionist Framework for Sequence Segmentation and Chunk Extraction

ERIC Educational Resources Information Center

French, Robert M.; Addyman, Caspar; Mareschal, Denis

2011-01-01

Individuals of all ages extract structure from the sequences of patterns they encounter in their environment, an ability that is at the very heart of cognition. Exactly what underlies this ability has been the subject of much debate over the years. A novel mechanism, implicit chunk recognition (ICR), is proposed for sequence segmentation and chunk…

Classification of video sequences into chosen generalized use classes of target size and lighting level.

PubMed

Leszczuk, Mikołaj; Dudek, Łukasz; Witkowski, Marcin

The VQiPS (Video Quality in Public Safety) Working Group, supported by the U.S. Department of Homeland Security, has been developing a user guide for public safety video applications. According to VQiPS, five parameters have particular importance influencing the ability to achieve a recognition task. They are: usage time-frame, discrimination level, target size, lighting level, and level of motion. These parameters form what are referred to as Generalized Use Classes (GUCs). The aim of our research was to develop algorithms that would automatically assist classification of input sequences into one of the GUCs. Target size and lighting level parameters were approached. The experiment described reveals the experts' ambiguity and hesitation during the manual target size determination process. However, the automatic methods developed for target size classification make it possible to determine GUC parameters with 70 % compliance to the end-users' opinion. Lighting levels of the entire sequence can be classified with an efficiency reaching 93 %. To make the algorithms available for use, a test application has been developed. It is able to process video files and display classification results, the user interface being very simple and requiring only minimal user interaction.

Image-algebraic design of multispectral target recognition algorithms

NASA Astrophysics Data System (ADS)

Schmalz, Mark S.; Ritter, Gerhard X.

1994-06-01

In this paper, we discuss methods for multispectral ATR (Automated Target Recognition) of small targets that are sensed under suboptimal conditions, such as haze, smoke, and low light levels. In particular, we discuss our ongoing development of algorithms and software that effect intelligent object recognition by selecting ATR filter parameters according to ambient conditions. Our algorithms are expressed in terms of IA (image algebra), a concise, rigorous notation that unifies linear and nonlinear mathematics in the image processing domain. IA has been implemented on a variety of parallel computers, with preprocessors available for the Ada and FORTRAN languages. An image algebra C++ class library has recently been made available. Thus, our algorithms are both feasible implementationally and portable to numerous machines. Analyses emphasize the aspects of image algebra that aid the design of multispectral vision algorithms, such as parameterized templates that facilitate the flexible specification of ATR filters.

Skeleton-based human action recognition using multiple sequence alignment

NASA Astrophysics Data System (ADS)

Ding, Wenwen; Liu, Kai; Cheng, Fei; Zhang, Jin; Li, YunSong

2015-05-01

Human action recognition and analysis is an active research topic in computer vision for many years. This paper presents a method to represent human actions based on trajectories consisting of 3D joint positions. This method first decompose action into a sequence of meaningful atomic actions (actionlets), and then label actionlets with English alphabets according to the Davies-Bouldin index value. Therefore, an action can be represented using a sequence of actionlet symbols, which will preserve the temporal order of occurrence of each of the actionlets. Finally, we employ sequence comparison to classify multiple actions through using string matching algorithms (Needleman-Wunsch). The effectiveness of the proposed method is evaluated on datasets captured by commodity depth cameras. Experiments of the proposed method on three challenging 3D action datasets show promising results.

Hemispheric asymmetries of a motor memory in a recognition test after learning a movement sequence.

PubMed

Leinen, Peter; Panzer, Stefan; Shea, Charles H

2016-11-01

Two experiments utilizing a spatial-temporal movement sequence were designed to determine if the memory of the sequence is lateralized in the left or right hemisphere. In Experiment 1, dominant right-handers were randomly assigned to one of two acquisition groups: a left-hand starter and a right-hand starter group. After an acquisition phase, reaction time (RT) was measured in a recognition test by providing the learned sequential pattern in the left or right visual half-field for 150ms. In a retention test and two transfer tests the dominant coordinate system for sequence production was evaluated. In Experiment 2 dominant left-handers and dominant right-handers had to acquire the sequence with their dominant limb. The results of Experiment 1 indicated that RT was significantly shorter when the acquired sequence was provided in the right visual field during the recognition test. The same results occurred in Experiment 2 for dominant right-handers and left-handers. These results indicated a right visual field left hemisphere advantage in the recognition test for the practiced stimulus for dominant left and right-handers, when the task was practiced with the dominant limb. Copyright © 2016 Elsevier B.V. All rights reserved.

Single molecule targeted sequencing for cancer gene mutation detection.

PubMed

Gao, Yan; Deng, Liwei; Yan, Qin; Gao, Yongqian; Wu, Zengding; Cai, Jinsen; Ji, Daorui; Li, Gailing; Wu, Ping; Jin, Huan; Zhao, Luyang; Liu, Song; Ge, Liangjin; Deem, Michael W; He, Jiankui

2016-05-19

With the rapid decline in cost of sequencing, it is now affordable to examine multiple genes in a single disease-targeted clinical test using next generation sequencing. Current targeted sequencing methods require a separate step of targeted capture enrichment during sample preparation before sequencing. Although there are fast sample preparation methods available in market, the library preparation process is still relatively complicated for physicians to use routinely. Here, we introduced an amplification-free Single Molecule Targeted Sequencing (SMTS) technology, which combined targeted capture and sequencing in one step. We demonstrated that this technology can detect low-frequency mutations using artificially synthesized DNA sample. SMTS has several potential advantages, including simple sample preparation thus no biases and errors are introduced by PCR reaction. SMTS has the potential to be an easy and quick sequencing technology for clinical diagnosis such as cancer gene mutation detection, infectious disease detection, inherited condition screening and noninvasive prenatal diagnosis.

Anodal tDCS targeting the right orbitofrontal cortex enhances facial expression recognition

PubMed Central

Murphy, Jillian M.; Ridley, Nicole J.; Vercammen, Ans

2015-01-01

The orbitofrontal cortex (OFC) has been implicated in the capacity to accurately recognise facial expressions. The aim of the current study was to determine if anodal transcranial direct current stimulation (tDCS) targeting the right OFC in healthy adults would enhance facial expression recognition, compared with a sham condition. Across two counterbalanced sessions of tDCS (i.e. anodal and sham), 20 undergraduate participants (18 female) completed a facial expression labelling task comprising angry, disgusted, fearful, happy, sad and neutral expressions, and a control (social judgement) task comprising the same expressions. Responses on the labelling task were scored for accuracy, median reaction time and overall efficiency (i.e. combined accuracy and reaction time). Anodal tDCS targeting the right OFC enhanced facial expression recognition, reflected in greater efficiency and speed of recognition across emotions, relative to the sham condition. In contrast, there was no effect of tDCS to responses on the control task. This is the first study to demonstrate that anodal tDCS targeting the right OFC boosts facial expression recognition. This finding provides a solid foundation for future research to examine the efficacy of this technique as a means to treat facial expression recognition deficits, particularly in individuals with OFC damage or dysfunction. PMID:25971602

Autonomous target recognition using remotely sensed surface vibration measurements

NASA Astrophysics Data System (ADS)

Geurts, James; Ruck, Dennis W.; Rogers, Steven K.; Oxley, Mark E.; Barr, Dallas N.

1993-09-01

The remotely measured surface vibration signatures of tactical military ground vehicles are investigated for use in target classification and identification friend or foe (IFF) systems. The use of remote surface vibration sensing by a laser radar reduces the effects of partial occlusion, concealment, and camouflage experienced by automatic target recognition systems using traditional imagery in a tactical battlefield environment. Linear Predictive Coding (LPC) efficiently represents the vibration signatures and nearest neighbor classifiers exploit the LPC feature set using a variety of distortion metrics. Nearest neighbor classifiers achieve an 88 percent classification rate in an eight class problem, representing a classification performance increase of thirty percent from previous efforts. A novel confidence figure of merit is implemented to attain a 100 percent classification rate with less than 60 percent rejection. The high classification rates are achieved on a target set which would pose significant problems to traditional image-based recognition systems. The targets are presented to the sensor in a variety of aspects and engine speeds at a range of 1 kilometer. The classification rates achieved demonstrate the benefits of using remote vibration measurement in a ground IFF system. The signature modeling and classification system can also be used to identify rotary and fixed-wing targets.

Aided target recognition processing of MUDSS sonar data

NASA Astrophysics Data System (ADS)

Lau, Brian; Chao, Tien-Hsin

1998-09-01

The Mobile Underwater Debris Survey System (MUDSS) is a collaborative effort by the Navy and the Jet Propulsion Lab to demonstrate multi-sensor, real-time, survey of underwater sites for ordnance and explosive waste (OEW). We describe the sonar processing algorithm, a novel target recognition algorithm incorporating wavelets, morphological image processing, expansion by Hermite polynomials, and neural networks. This algorithm has found all planted targets in MUDSS tests and has achieved spectacular success upon another Coastal Systems Station (CSS) sonar image database.

Protein-targeted corona phase molecular recognition

PubMed Central

Bisker, Gili; Dong, Juyao; Park, Hoyoung D.; Iverson, Nicole M.; Ahn, Jiyoung; Nelson, Justin T.; Landry, Markita P.; Kruss, Sebastian; Strano, Michael S.

2016-01-01

Corona phase molecular recognition (CoPhMoRe) uses a heteropolymer adsorbed onto and templated by a nanoparticle surface to recognize a specific target analyte. This method has not yet been extended to macromolecular analytes, including proteins. Herein we develop a variant of a CoPhMoRe screening procedure of single-walled carbon nanotubes (SWCNT) and use it against a panel of human blood proteins, revealing a specific corona phase that recognizes fibrinogen with high selectivity. In response to fibrinogen binding, SWCNT fluorescence decreases by >80% at saturation. Sequential binding of the three fibrinogen nodules is suggested by selective fluorescence quenching by isolated sub-domains and validated by the quenching kinetics. The fibrinogen recognition also occurs in serum environment, at the clinically relevant fibrinogen concentrations in the human blood. These results open new avenues for synthetic, non-biological antibody analogues that recognize biological macromolecules, and hold great promise for medical and clinical applications. PMID:26742890

An automatic target recognition system based on SAR image

NASA Astrophysics Data System (ADS)

Li, Qinfu; Wang, Jinquan; Zhao, Bo; Luo, Furen; Xu, Xiaojian

2009-10-01

In this paper, an automatic target recognition (ATR) system based on synthetic aperture radar (SAR) is proposed. This ATR system can play an important role in the simulation of up-to-data battlefield environment and be used in ATR research. To establish an integral and available system, the processing of SAR image was divided into four main stages which are de-noise, detection, cluster-discrimination and segment-recognition, respectively. The first three stages are used for searching region of interest (ROI). Once the ROIs are extracted, the recognition stage will be taken to compute the similarity between the ROIs and the templates in the electromagnetic simulation software National Electromagnetic Scattering Code (NESC). Due to the lack of the SAR raw data, the electromagnetic simulated images are added to the measured SAR background to simulate the battlefield environment8. The purpose of the system is to find the ROIs which can be the artificial military targets such as tanks, armored cars and so on and to categorize the ROIs into the right classes according to the existing templates. From the results we can see that the proposed system achieves a satisfactory result.

The research of multi-frame target recognition based on laser active imaging

NASA Astrophysics Data System (ADS)

Wang, Can-jin; Sun, Tao; Wang, Tin-feng; Chen, Juan

2013-09-01

Laser active imaging is fit to conditions such as no difference in temperature between target and background, pitch-black night, bad visibility. Also it can be used to detect a faint target in long range or small target in deep space, which has advantage of high definition and good contrast. In one word, it is immune to environment. However, due to the affect of long distance, limited laser energy and atmospheric backscatter, it is impossible to illuminate the whole scene at the same time. It means that the target in every single frame is unevenly or partly illuminated, which make the recognition more difficult. At the same time the speckle noise which is common in laser active imaging blurs the images . In this paper we do some research on laser active imaging and propose a new target recognition method based on multi-frame images . Firstly, multi pulses of laser is used to obtain sub-images for different parts of scene. A denoising method combined homomorphic filter with wavelet domain SURE is used to suppress speckle noise. And blind deconvolution is introduced to obtain low-noise and clear sub-images. Then these sub-images are registered and stitched to combine a completely and uniformly illuminated scene image. After that, a new target recognition method based on contour moments is proposed. Firstly, canny operator is used to obtain contours. For each contour, seven invariant Hu moments are calculated to generate the feature vectors. At last the feature vectors are input into double hidden layers BP neural network for classification . Experiments results indicate that the proposed algorithm could achieve a high recognition rate and satisfactory real-time performance for laser active imaging.

Sequence-Specific Targeting of Dosage Compensation in Drosophila Favors an Active Chromatin Context

PubMed Central

Gelbart, Marnie; Tolstorukov, Michael Y.; Plachetka, Annette; Kharchenko, Peter V.; Jung, Youngsook L.; Gorchakov, Andrey A.; Larschan, Erica; Gu, Tingting; Minoda, Aki; Riddle, Nicole C.; Schwartz, Yuri B.; Elgin, Sarah C. R.; Karpen, Gary H.; Pirrotta, Vincenzo; Kuroda, Mitzi I.; Park, Peter J.

2012-01-01

The Drosophila MSL complex mediates dosage compensation by increasing transcription of the single X chromosome in males approximately two-fold. This is accomplished through recognition of the X chromosome and subsequent acetylation of histone H4K16 on X-linked genes. Initial binding to the X is thought to occur at “entry sites” that contain a consensus sequence motif (“MSL recognition element” or MRE). However, this motif is only ∼2 fold enriched on X, and only a fraction of the motifs on X are initially targeted. Here we ask whether chromatin context could distinguish between utilized and non-utilized copies of the motif, by comparing their relative enrichment for histone modifications and chromosomal proteins mapped in the modENCODE project. Through a comparative analysis of the chromatin features in male S2 cells (which contain MSL complex) and female Kc cells (which lack the complex), we find that the presence of active chromatin modifications, together with an elevated local GC content in the surrounding sequences, has strong predictive value for functional MSL entry sites, independent of MSL binding. We tested these sites for function in Kc cells by RNAi knockdown of Sxl, resulting in induction of MSL complex. We show that ectopic MSL expression in Kc cells leads to H4K16 acetylation around these sites and a relative increase in X chromosome transcription. Collectively, our results support a model in which a pre-existing active chromatin environment, coincident with H3K36me3, contributes to MSL entry site selection. The consequences of MSL targeting of the male X chromosome include increase in nucleosome lability, enrichment for H4K16 acetylation and JIL-1 kinase, and depletion of linker histone H1 on active X-linked genes. Our analysis can serve as a model for identifying chromatin and local sequence features that may contribute to selection of functional protein binding sites in the genome. PMID:22570616

Testing of a Composite Wavelet Filter to Enhance Automated Target Recognition in SONAR

NASA Technical Reports Server (NTRS)

Chiang, Jeffrey N.

2011-01-01

Automated Target Recognition (ATR) systems aim to automate target detection, recognition, and tracking. The current project applies a JPL ATR system to low resolution SONAR and camera videos taken from Unmanned Underwater Vehicles (UUVs). These SONAR images are inherently noisy and difficult to interpret, and pictures taken underwater are unreliable due to murkiness and inconsistent lighting. The ATR system breaks target recognition into three stages: 1) Videos of both SONAR and camera footage are broken into frames and preprocessed to enhance images and detect Regions of Interest (ROIs). 2) Features are extracted from these ROIs in preparation for classification. 3) ROIs are classified as true or false positives using a standard Neural Network based on the extracted features. Several preprocessing, feature extraction, and training methods are tested and discussed in this report.

Loop nucleotides control primary and mature miRNA function in target recognition and repression

PubMed Central

Yue, Si-Biao; Deis Trujillo, Robin; Tang, Yujie; O'Gorman, William E

2011-01-01

MicroRNA (miRNA) genes produce three major RNA products; primary (pri-), precursor (pre-), and mature miRNAs. Each product includes sequences complementary to cognate targets, thus they all can in principle interact with the targets. In a recent study we showed that pri-miRNAs play a direct role in target recognition and repression in the absence of functional mature miRNAs. Here we examined the functional contribution of pri-miRNAs in target regulation when full-length functional miRNAs are present. We found that pri-let-7 loop nucleotides control the production of the 5′ end of mature miRNAs and modulate the activity of the miRNA gene. This insight enabled us to modulate biogenesis of functional mature miRNAs and dissect the causal relationships between mature miRNA biogenesis and target repression. We demonstrate that both pri- and mature miRNAs can contribute to target repression and that their contributions can be distinguished by the differences between the pri- and mature miRNAs' sensitivity to bind to the first seed nucleotide. Our results demonstrate that the regulatory information encoded in the pri-/pre-miRNA loop nucleotides controls the activities of pri-miRNAs and mature let-7 by influencing pri-miRNA and target complex formation and the fidelity of mature miRNA seed generation. PMID:22142974

Bioinspired Pollen-Like Hierarchical Surface for Efficient Recognition of Target Cancer Cells.

PubMed

Wang, Wenshuo; Yang, Gao; Cui, Haijun; Meng, Jingxin; Wang, Shutao; Jiang, Lei

2017-08-01

The efficient recognition and isolation of rare cancer cells holds great promise for cancer diagnosis and prognosis. In nature, pollens exploit spiky structures to realize recognition and adhesion to stigma. Herein, a bioinspired pollen-like hierarchical surface is developed by replicating the assembly of pollen grains, and efficient and specific recognition to target cancer cells is achieved. The pollen-like surface is fabricated by combining filtering-assisted assembly and soft lithography-based replication of pollen grains of wild chrysanthemum. After modification with a capture agent specific to cancer cells, the pollen-like surface enables the capture of target cancer cells with high efficiency and specificity. In addition, the pollen-like surface not only assures high viability of captured cells but also performs well in cell mixture system and at low cell density. This study represents a good example of constructing cell recognition biointerfaces inspired by pollen-stigma adhesion. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

SAR target recognition and posture estimation using spatial pyramid pooling within CNN

NASA Astrophysics Data System (ADS)

Peng, Lijiang; Liu, Xiaohua; Liu, Ming; Dong, Liquan; Hui, Mei; Zhao, Yuejin

2018-01-01

Many convolution neural networks(CNN) architectures have been proposed to strengthen the performance on synthetic aperture radar automatic target recognition (SAR-ATR) and obtained state-of-art results on targets classification on MSTAR database, but few methods concern about the estimation of depression angle and azimuth angle of targets. To get better effect on learning representation of hierarchies of features on both 10-class target classification task and target posture estimation tasks, we propose a new CNN architecture with spatial pyramid pooling(SPP) which can build high hierarchy of features map by dividing the convolved feature maps from finer to coarser levels to aggregate local features of SAR images. Experimental results on MSTAR database show that the proposed architecture can get high recognition accuracy as 99.57% on 10-class target classification task as the most current state-of-art methods, and also get excellent performance on target posture estimation tasks which pays attention to depression angle variety and azimuth angle variety. What's more, the results inspire us the application of deep learning on SAR target posture description.

Enantiospecific recognition of DNA sequences by a proflavine Tröger base.

PubMed

Bailly, C; Laine, W; Demeunynck, M; Lhomme, J

2000-07-05

The DNA interaction of a chiral Tröger base derived from proflavine was investigated by DNA melting temperature measurements and complementary biochemical assays. DNase I footprinting experiments demonstrate that the binding of the proflavine-based Tröger base is both enantio- and sequence-specific. The (+)-isomer poorly interacts with DNA in a non-sequence-selective fashion. In sharp contrast, the corresponding (-)-isomer recognizes preferentially certain DNA sequences containing both A. T and G. C base pairs, such as the motifs 5'-GTT. AAC and 5'-ATGA. TCAT. This is the first experimental demonstration that acridine-type Tröger bases can be used for enantiospecific recognition of DNA sequences. Copyright 2000 Academic Press.

Kilo-sequencing: an ordered strategy for rapid DNA sequence data acquisition.

PubMed Central

Barnes, W M; Bevan, M

1983-01-01

A strategy for rapid DNA sequence acquisition in an ordered, nonrandom manner, while retaining all of the conveniences of the dideoxy method with M13 transducing phage DNA template, is described. Target DNA 3 to 14 kb in size can be stably carried by our M13 vectors. Suitable targets are stretches of DNA which lack an enzyme recognition site which is unique on our cloning vectors and adjacent to the sequencing primer; current sites that are so useful when lacking are Pst, Xba, HindIII, BglII, EcoRI. By an in vitro procedure, we cut RF DNA once randomly and once specifically, to create thousands of deletions which start at the unique restriction site adjacent to the dideoxy sequencing primer and extend various distances across the target DNA. Phage carrying a desired size of deletions, whose DNA as template will give rise to DNA sequence data in a desired location along the target DNA, may be purified by electrophoresis alive on agarose gels. Phage running in the same location on the agarose gel thus conveniently give rise to nucleotide sequence data from the same kilobase of target DNA. Images PMID:6298723

Bi-Spectral Method for Radar Target Recognition

DTIC Science & Technology

2006-12-01

θazimuth=60° and ϕelevation=30° with HV Polarization....................................53 Figure 50 Comparison of Radar Range Profile with Actual...radar systems. A comparison of the NCTR techniques and their relative advantages and disadvantages in target recognition performance is presented. 8...32 f fR i R R c c f fi R R i R R c c A e A e A e ψ ψ π ψ ψ π ψ ψ π ψ ψ

A Pathogenic Nematode Targets Recognition Proteins to Avoid Insect Defenses

PubMed Central

Toubarro, Duarte; Avila, Mónica Martinez; Montiel, Rafael; Simões, Nelson

2013-01-01

Steinernema carpocapsae is a nematode pathogenic in a wide variety of insect species. The great pathogenicity of this nematode has been ascribed to its ability to overcome the host immune response; however, little is known about the mechanisms involved in this process. The analysis of an expressed sequence tags (EST) library in the nematode during the infective phase was performed and a highly abundant contig homologous to serine protease inhibitors was identified. In this work, we show that this contig is part of a 641-bp cDNA that encodes a BPTI-Kunitz family inhibitor (Sc-KU-4), which is up-regulated in the parasite during invasion and installation. Recombinant Sc-KU-4 protein was produced in Escherichia coli and shown to inhibit chymotrypsin and elastase activities in a dose-dependent manner by a competitive mechanism with Ki values of 1.8 nM and 2.6 nM, respectively. Sc-KU-4 also inhibited trypsin and thrombin activities to a lesser extent. Studies of the mode of action of Sc-KU-4 and its effects on insect defenses suggest that although Sc-KU-4 did not inhibit the activation of hemocytes or the formation of clotting fibers, it did inhibit hemocyte aggregation and the entrapment of foreign particles by fibers. Moreover, Sc-KU-4 avoided encapsulation and the deposition of clotting materials, which usually occurs in response to foreign particles. We show by protein-protein interaction that Sc-KU-4 targets recognition proteins of insect immune system such as masquerade-like and serine protease-like homologs. The interaction of Sc-KU-4 with these proteins explains the ability of the nematode to overcome host reactions and its large pathogenic spectrum, once these immune proteins are well conserved in insects. The discovery of this inhibitor targeting insect recognition proteins opens new avenues for the development of S . carpocapsae as a biological control agent and provides a new tool to study host-pathogen interactions. PMID:24098715

Targeted RNA-Sequencing with Competitive Multiplex-PCR Amplicon Libraries

PubMed Central

Blomquist, Thomas M.; Crawford, Erin L.; Lovett, Jennie L.; Yeo, Jiyoun; Stanoszek, Lauren M.; Levin, Albert; Li, Jia; Lu, Mei; Shi, Leming; Muldrew, Kenneth; Willey, James C.

2013-01-01

Whole transcriptome RNA-sequencing is a powerful tool, but is costly and yields complex data sets that limit its utility in molecular diagnostic testing. A targeted quantitative RNA-sequencing method that is reproducible and reduces the number of sequencing reads required to measure transcripts over the full range of expression would be better suited to diagnostic testing. Toward this goal, we developed a competitive multiplex PCR-based amplicon sequencing library preparation method that a) targets only the sequences of interest and b) controls for inter-target variation in PCR amplification during library preparation by measuring each transcript native template relative to a known number of synthetic competitive template internal standard copies. To determine the utility of this method, we intentionally selected PCR conditions that would cause transcript amplification products (amplicons) to converge toward equimolar concentrations (normalization) during library preparation. We then tested whether this approach would enable accurate and reproducible quantification of each transcript across multiple library preparations, and at the same time reduce (through normalization) total sequencing reads required for quantification of transcript targets across a large range of expression. We demonstrate excellent reproducibility (R2 = 0.997) with 97% accuracy to detect 2-fold change using External RNA Controls Consortium (ERCC) reference materials; high inter-day, inter-site and inter-library concordance (R2 = 0.97–0.99) using FDA Sequencing Quality Control (SEQC) reference materials; and cross-platform concordance with both TaqMan qPCR (R2 = 0.96) and whole transcriptome RNA-sequencing following “traditional” library preparation using Illumina NGS kits (R2 = 0.94). Using this method, sequencing reads required to accurately quantify more than 100 targeted transcripts expressed over a 107-fold range was reduced more than 10,000-fold, from 2.3×109 to 1

"Multiple partial recognitions in dynamic equilibrium" in the binding sites of proteins form the molecular basis of promiscuous recognition of structurally diverse ligands.

PubMed

Kohda, Daisuke

2018-04-01

Promiscuous recognition of ligands by proteins is as important as strict recognition in numerous biological processes. In living cells, many short, linear amino acid motifs function as targeting signals in proteins to specify the final destination of the protein transport. In general, the target signal is defined by a consensus sequence containing wild-characters, and hence represented by diverse amino acid sequences. The classical lock-and-key or induced-fit/conformational selection mechanism may not cover all aspects of the promiscuous recognition. On the basis of our crystallographic and NMR studies on the mitochondrial Tom20 protein-presequence interaction, we proposed a new hypothetical mechanism based on "a rapid equilibrium of multiple states with partial recognitions". This dynamic, multiple recognition mode enables the Tom20 receptor to recognize diverse mitochondrial presequences with nearly equal affinities. The plant Tom20 is evolutionally unrelated to the animal Tom20 in our study, but is a functional homolog of the animal/fungal Tom20. NMR studies by another research group revealed that the presequence binding by the plant Tom20 was not fully explained by simple interaction modes, suggesting the presence of a similar dynamic, multiple recognition mode. Circumstantial evidence also suggested that similar dynamic mechanisms may be applicable to other promiscuous recognitions of signal peptides by the SRP54/Ffh and SecA proteins.

Learning and recognition of tactile temporal sequences by mice and humans

PubMed Central

Bale, Michael R; Bitzidou, Malamati; Pitas, Anna; Brebner, Leonie S; Khazim, Lina; Anagnou, Stavros T; Stevenson, Caitlin D; Maravall, Miguel

2017-01-01

The world around us is replete with stimuli that unfold over time. When we hear an auditory stream like music or speech or scan a texture with our fingertip, physical features in the stimulus are concatenated in a particular order. This temporal patterning is critical to interpreting the stimulus. To explore the capacity of mice and humans to learn tactile sequences, we developed a task in which subjects had to recognise a continuous modulated noise sequence delivered to whiskers or fingertips, defined by its temporal patterning over hundreds of milliseconds. GO and NO-GO sequences differed only in that the order of their constituent noise modulation segments was temporally scrambled. Both mice and humans efficiently learned tactile sequences. Mouse sequence recognition depended on detecting transitions in noise amplitude; animals could base their decision on the earliest information available. Humans appeared to use additional cues, including the duration of noise modulation segments. DOI: http://dx.doi.org/10.7554/eLife.27333.001 PMID:28812976

Metal cofactor modulated folding and target recognition of HIV-1 NCp7.

PubMed

Ren, Weitong; Ji, Dongqing; Xu, Xiulian

2018-01-01

The HIV-1 nucleocapsid 7 (NCp7) plays crucial roles in multiple stages of HIV-1 life cycle, and its biological functions rely on the binding of zinc ions. Understanding the molecular mechanism of how the zinc ions modulate the conformational dynamics and functions of the NCp7 is essential for the drug development and HIV-1 treatment. In this work, using a structure-based coarse-grained model, we studied the effects of zinc cofactors on the folding and target RNA(SL3) recognition of the NCp7 by molecular dynamics simulations. After reproducing some key properties of the zinc binding and folding of the NCp7 observed in previous experiments, our simulations revealed several interesting features in the metal ion modulated folding and target recognition. Firstly, we showed that the zinc binding makes the folding transition states of the two zinc fingers less structured, which is in line with the Hammond effect observed typically in mutation, temperature or denaturant induced perturbations to protein structure and stability. Secondly, We showed that there exists mutual interplay between the zinc ion binding and NCp7-target recognition. Binding of zinc ions enhances the affinity between the NCp7 and the target RNA, whereas the formation of the NCp7-RNA complex reshapes the intrinsic energy landscape of the NCp7 and increases the stability and zinc affinity of the two zinc fingers. Thirdly, by characterizing the effects of salt concentrations on the target RNA recognition, we showed that the NCp7 achieves optimal balance between the affinity and binding kinetics near the physiologically relevant salt concentrations. In addition, the effects of zinc binding on the inter-domain conformational flexibility and folding cooperativity of the NCp7 were also discussed.

Pharmacologic suppression of target cell recognition by engineered T cells expressing chimeric T-cell receptors.

PubMed

Alvarez-Vallina, L; Yañez, R; Blanco, B; Gil, M; Russell, S J

2000-04-01

Adoptive therapy with autologous T cells expressing chimeric T-cell receptors (chTCRs) is of potential interest for the treatment of malignancy. To limit possible T-cell-mediated damage to normal tissues that weakly express the targeted tumor antigen (Ag), we have tested a strategy for the suppression of target cell recognition by engineered T cells. Jurkat T cells were transduced with an anti-hapten chTCR tinder the control of a tetracycline-suppressible promoter and were shown to respond to Ag-positive (hapten-coated) but not to Ag-negative target cells. The engineered T cells were then reacted with hapten-coated target cells at different effector to target cell ratios before and after exposure to tetracycline. When the engineered T cells were treated with tetracycline, expression of the chTCR was greatly decreased and recognition of the hapten-coated target cells was completely suppressed. Tetracycline-mediated suppression of target cell recognition by engineered T cells may be a useful strategy to limit the toxicity of the approach to cancer gene therapy.

Programmable RNA recognition and cleavage by CRISPR/Cas9.

PubMed

O'Connell, Mitchell R; Oakes, Benjamin L; Sternberg, Samuel H; East-Seletsky, Alexandra; Kaplan, Matias; Doudna, Jennifer A

2014-12-11

The CRISPR-associated protein Cas9 is an RNA-guided DNA endonuclease that uses RNA-DNA complementarity to identify target sites for sequence-specific double-stranded DNA (dsDNA) cleavage. In its native context, Cas9 acts on DNA substrates exclusively because both binding and catalysis require recognition of a short DNA sequence, known as the protospacer adjacent motif (PAM), next to and on the strand opposite the twenty-nucleotide target site in dsDNA. Cas9 has proven to be a versatile tool for genome engineering and gene regulation in a large range of prokaryotic and eukaryotic cell types, and in whole organisms, but it has been thought to be incapable of targeting RNA. Here we show that Cas9 binds with high affinity to single-stranded RNA (ssRNA) targets matching the Cas9-associated guide RNA sequence when the PAM is presented in trans as a separate DNA oligonucleotide. Furthermore, PAM-presenting oligonucleotides (PAMmers) stimulate site-specific endonucleolytic cleavage of ssRNA targets, similar to PAM-mediated stimulation of Cas9-catalysed DNA cleavage. Using specially designed PAMmers, Cas9 can be specifically directed to bind or cut RNA targets while avoiding corresponding DNA sequences, and we demonstrate that this strategy enables the isolation of a specific endogenous messenger RNA from cells. These results reveal a fundamental connection between PAM binding and substrate selection by Cas9, and highlight the utility of Cas9 for programmable transcript recognition without the need for tags.

Programmable RNA recognition and cleavage by CRISPR/Cas9

PubMed Central

O’Connell, Mitchell R.; Oakes, Benjamin L.; Sternberg, Samuel H.; East-Seletsky, Alexandra; Kaplan, Matias; Doudna, Jennifer A.

2014-01-01

The CRISPR-associated protein Cas9 is an RNA-guided DNA endonuclease that uses RNA:DNA complementarity to identify target sites for sequence-specific doublestranded DNA (dsDNA) cleavage1-5. In its native context, Cas9 acts on DNA substrates exclusively because both binding and catalysis require recognition of a short DNA sequence, the protospacer adjacent motif (PAM), next to and on the strand opposite the 20-nucleotide target site in dsDNA4-7. Cas9 has proven to be a versatile tool for genome engineering and gene regulation in many cell types and organisms8, but it has been thought to be incapable of targeting RNA5. Here we show that Cas9 binds with high affinity to single-stranded RNA (ssRNA) targets matching the Cas9-associated guide RNA sequence when the PAM is presented in trans as a separate DNA oligonucleotide. Furthermore, PAM-presenting oligonucleotides (PAMmers) stimulate site-specific endonucleolytic cleavage of ssRNA targets, similar to PAM-mediated stimulation of Cas9-catalyzed DNA cleavage7. Using specially designed PAMmers, Cas9 can be specifically directed to bind or cut RNA targets while avoiding corresponding DNA sequences, and we demonstrate that this strategy enables the isolation of a specific endogenous mRNA from cells. These results reveal a fundamental connection between PAM binding and substrate selection by Cas9, and highlight the utility of Cas9 for programmable and tagless transcript recognition. PMID:25274302

Dactyl Alphabet Gesture Recognition in a Video Sequence Using Microsoft Kinect

NASA Astrophysics Data System (ADS)

Artyukhin, S. G.; Mestetskiy, L. M.

2015-05-01

This paper presents an efficient framework for solving the problem of static gesture recognition based on data obtained from the web cameras and depth sensor Kinect (RGB-D - data). Each gesture given by a pair of images: color image and depth map. The database store gestures by it features description, genereated by frame for each gesture of the alphabet. Recognition algorithm takes as input a video sequence (a sequence of frames) for marking, put in correspondence with each frame sequence gesture from the database, or decide that there is no suitable gesture in the database. First, classification of the frame of the video sequence is done separately without interframe information. Then, a sequence of successful marked frames in equal gesture is grouped into a single static gesture. We propose a method combined segmentation of frame by depth map and RGB-image. The primary segmentation is based on the depth map. It gives information about the position and allows to get hands rough border. Then, based on the color image border is specified and performed analysis of the shape of the hand. Method of continuous skeleton is used to generate features. We propose a method of skeleton terminal branches, which gives the opportunity to determine the position of the fingers and wrist. Classification features for gesture is description of the position of the fingers relative to the wrist. The experiments were carried out with the developed algorithm on the example of the American Sign Language. American Sign Language gesture has several components, including the shape of the hand, its orientation in space and the type of movement. The accuracy of the proposed method is evaluated on the base of collected gestures consisting of 2700 frames.

Photonics: From target recognition to lesion detection

NASA Technical Reports Server (NTRS)

Henry, E. Michael

1994-01-01

Since 1989, Martin Marietta has invested in the development of an innovative concept for robust real-time pattern recognition for any two-dimensioanal sensor. This concept has been tested in simulation, and in laboratory and field hardware, for a number of DOD and commercial uses from automatic target recognition to manufacturing inspection. We have now joined Rose Health Care Systems in developing its use for medical diagnostics. The concept is based on determining regions of interest by using optical Fourier bandpassing as a scene segmentation technique, enhancing those regions using wavelet filters, passing the enhanced regions to a neural network for analysis and initial pattern identification, and following this initial identification with confirmation by optical correlation. The optical scene segmentation and pattern confirmation are performed by the same optical module. The neural network is a recursive error minimization network with a small number of connections and nodes that rapidly converges to a global minimum.

Targeted Capture and High-Throughput Sequencing Using Molecular Inversion Probes (MIPs).

PubMed

Cantsilieris, Stuart; Stessman, Holly A; Shendure, Jay; Eichler, Evan E

2017-01-01

Molecular inversion probes (MIPs) in combination with massively parallel DNA sequencing represent a versatile, yet economical tool for targeted sequencing of genomic DNA. Several thousand genomic targets can be selectively captured using long oligonucleotides containing unique targeting arms and universal linkers. The ability to append sequencing adaptors and sample-specific barcodes allows large-scale pooling and subsequent high-throughput sequencing at relatively low cost per sample. Here, we describe a "wet bench" protocol detailing the capture and subsequent sequencing of >2000 genomic targets from 192 samples, representative of a single lane on the Illumina HiSeq 2000 platform.

Compressive sensing method for recognizing cat-eye effect targets.

PubMed

Li, Li; Li, Hui; Dang, Ersheng; Liu, Bo

2013-10-01

This paper proposes a cat-eye effect target recognition method with compressive sensing (CS) and presents a recognition method (sample processing before reconstruction based on compressed sensing, or SPCS) for image processing. In this method, the linear projections of original image sequences are applied to remove dynamic background distractions and extract cat-eye effect targets. Furthermore, the corresponding imaging mechanism for acquiring active and passive image sequences is put forward. This method uses fewer images to recognize cat-eye effect targets, reduces data storage, and translates the traditional target identification, based on original image processing, into measurement vectors processing. The experimental results show that the SPCS method is feasible and superior to the shape-frequency dual criteria method.

Accurate and exact CNV identification from targeted high-throughput sequence data.

PubMed

Nord, Alex S; Lee, Ming; King, Mary-Claire; Walsh, Tom

2011-04-12

Massively parallel sequencing of barcoded DNA samples significantly increases screening efficiency for clinically important genes. Short read aligners are well suited to single nucleotide and indel detection. However, methods for CNV detection from targeted enrichment are lacking. We present a method combining coverage with map information for the identification of deletions and duplications in targeted sequence data. Sequencing data is first scanned for gains and losses using a comparison of normalized coverage data between samples. CNV calls are confirmed by testing for a signature of sequences that span the CNV breakpoint. With our method, CNVs can be identified regardless of whether breakpoints are within regions targeted for sequencing. For CNVs where at least one breakpoint is within targeted sequence, exact CNV breakpoints can be identified. In a test data set of 96 subjects sequenced across ~1 Mb genomic sequence using multiplexing technology, our method detected mutations as small as 31 bp, predicted quantitative copy count, and had a low false-positive rate. Application of this method allows for identification of gains and losses in targeted sequence data, providing comprehensive mutation screening when combined with a short read aligner.

Toxins of Prokaryotic Toxin-Antitoxin Systems with Sequence-Specific Endoribonuclease Activity

PubMed Central

Masuda, Hisako; Inouye, Masayori

2017-01-01

Protein translation is the most common target of toxin-antitoxin system (TA) toxins. Sequence-specific endoribonucleases digest RNA in a sequence-specific manner, thereby blocking translation. While past studies mainly focused on the digestion of mRNA, recent analysis revealed that toxins can also digest tRNA, rRNA and tmRNA. Purified toxins can digest single-stranded portions of RNA containing recognition sequences in the absence of ribosome in vitro. However, increasing evidence suggests that in vivo digestion may occur in association with ribosomes. Despite the prevalence of recognition sequences in many mRNA, preferential digestion seems to occur at specific positions within mRNA and also in certain reading frames. In this review, a variety of tools utilized to study the nuclease activities of toxins over the past 15 years will be reviewed. A recent adaptation of an RNA-seq-based technique to analyze entire sets of cellular RNA will be introduced with an emphasis on its strength in identifying novel targets and redefining recognition sequences. The differences in biochemical properties and postulated physiological roles will also be discussed. PMID:28420090

The siRNA Non-seed Region and Its Target Sequences Are Auxiliary Determinants of Off-Target Effects.

PubMed

Kamola, Piotr J; Nakano, Yuko; Takahashi, Tomoko; Wilson, Paul A; Ui-Tei, Kumiko

2015-12-01

RNA interference (RNAi) is a powerful tool for post-transcriptional gene silencing. However, the siRNA guide strand may bind unintended off-target transcripts via partial sequence complementarity by a mechanism closely mirroring micro RNA (miRNA) silencing. To better understand these off-target effects, we investigated the correlation between sequence features within various subsections of siRNA guide strands, and its corresponding target sequences, with off-target activities. Our results confirm previous reports that strength of base-pairing in the siRNA seed region is the primary factor determining the efficiency of off-target silencing. However, the degree of downregulation of off-target transcripts with shared seed sequence is not necessarily similar, suggesting that there are additional auxiliary factors that influence the silencing potential. Here, we demonstrate that both the melting temperature (Tm) in a subsection of siRNA non-seed region, and the GC contents of its corresponding target sequences, are negatively correlated with the efficiency of off-target effect. Analysis of experimentally validated miRNA targets demonstrated a similar trend, indicating a putative conserved mechanistic feature of seed region-dependent targeting mechanism. These observations may prove useful as parameters for off-target prediction algorithms and improve siRNA 'specificity' design rules.

Highly multiplexed targeted DNA sequencing from single nuclei.

PubMed

Leung, Marco L; Wang, Yong; Kim, Charissa; Gao, Ruli; Jiang, Jerry; Sei, Emi; Navin, Nicholas E

2016-02-01

Single-cell DNA sequencing methods are challenged by poor physical coverage, high technical error rates and low throughput. To address these issues, we developed a single-cell DNA sequencing protocol that combines flow-sorting of single nuclei, time-limited multiple-displacement amplification (MDA), low-input library preparation, DNA barcoding, targeted capture and next-generation sequencing (NGS). This approach represents a major improvement over our previous single nucleus sequencing (SNS) Nature Protocols paper in terms of generating higher-coverage data (>90%), thereby enabling the detection of genome-wide variants in single mammalian cells at base-pair resolution. Furthermore, by pooling 48-96 single-cell libraries together for targeted capture, this approach can be used to sequence many single-cell libraries in parallel in a single reaction. This protocol greatly reduces the cost of single-cell DNA sequencing, and it can be completed in 5-6 d by advanced users. This single-cell DNA sequencing protocol has broad applications for studying rare cells and complex populations in diverse fields of biological research and medicine.

Pattern recognition of electronic bit-sequences using a semiconductor mode-locked laser and spatial light modulators

NASA Astrophysics Data System (ADS)

Bhooplapur, Sharad; Akbulut, Mehmetkan; Quinlan, Franklyn; Delfyett, Peter J.

2010-04-01

A novel scheme for recognition of electronic bit-sequences is demonstrated. Two electronic bit-sequences that are to be compared are each mapped to a unique code from a set of Walsh-Hadamard codes. The codes are then encoded in parallel on the spectral phase of the frequency comb lines from a frequency-stabilized mode-locked semiconductor laser. Phase encoding is achieved by using two independent spatial light modulators based on liquid crystal arrays. Encoded pulses are compared using interferometric pulse detection and differential balanced photodetection. Orthogonal codes eight bits long are compared, and matched codes are successfully distinguished from mismatched codes with very low error rates, of around 10-18. This technique has potential for high-speed, high accuracy recognition of bit-sequences, with applications in keyword searches and internet protocol packet routing.

Unravelling Glucan Recognition Systems by Glycome Microarrays Using the Designer Approach and Mass Spectrometry*

PubMed Central

Palma, Angelina S.; Liu, Yan; Zhang, Hongtao; Zhang, Yibing; McCleary, Barry V.; Yu, Guangli; Huang, Qilin; Guidolin, Leticia S.; Ciocchini, Andres E.; Torosantucci, Antonella; Wang, Denong; Carvalho, Ana Luísa; Fontes, Carlos M. G. A.; Mulloy, Barbara; Childs, Robert A.; Feizi, Ten; Chai, Wengang

2015-01-01

Glucans are polymers of d-glucose with differing linkages in linear or branched sequences. They are constituents of microbial and plant cell-walls and involved in important bio-recognition processes, including immunomodulation, anticancer activities, pathogen virulence, and plant cell-wall biodegradation. Translational possibilities for these activities in medicine and biotechnology are considerable. High-throughput micro-methods are needed to screen proteins for recognition of specific glucan sequences as a lead to structure–function studies and their exploitation. We describe construction of a “glucome” microarray, the first sequence-defined glycome-scale microarray, using a “designer” approach from targeted ligand-bearing glucans in conjunction with a novel high-sensitivity mass spectrometric sequencing method, as a screening tool to assign glucan recognition motifs. The glucome microarray comprises 153 oligosaccharide probes with high purity, representing major sequences in glucans. Negative-ion electrospray tandem mass spectrometry with collision-induced dissociation was used for complete linkage analysis of gluco-oligosaccharides in linear “homo” and “hetero” and branched sequences. The system is validated using antibodies and carbohydrate-binding modules known to target α- or β-glucans in different biological contexts, extending knowledge on their specificities, and applied to reveal new information on glucan recognition by two signaling molecules of the immune system against pathogens: Dectin-1 and DC-SIGN. The sequencing of the glucan oligosaccharides by the MS method and their interrogation on the microarrays provides detailed information on linkage, sequence and chain length requirements of glucan-recognizing proteins, and are a sensitive means of revealing unsuspected sequences in the polysaccharides. PMID:25670804

Unsupervised learning in persistent sensing for target recognition by wireless ad hoc networks of ground-based sensors

NASA Astrophysics Data System (ADS)

Hortos, William S.

2008-04-01

In previous work by the author, effective persistent and pervasive sensing for recognition and tracking of battlefield targets were seen to be achieved, using intelligent algorithms implemented by distributed mobile agents over a composite system of unmanned aerial vehicles (UAVs) for persistence and a wireless network of unattended ground sensors for pervasive coverage of the mission environment. While simulated performance results for the supervised algorithms of the composite system are shown to provide satisfactory target recognition over relatively brief periods of system operation, this performance can degrade by as much as 50% as target dynamics in the environment evolve beyond the period of system operation in which the training data are representative. To overcome this limitation, this paper applies the distributed approach using mobile agents to the network of ground-based wireless sensors alone, without the UAV subsystem, to provide persistent as well as pervasive sensing for target recognition and tracking. The supervised algorithms used in the earlier work are supplanted by unsupervised routines, including competitive-learning neural networks (CLNNs) and new versions of support vector machines (SVMs) for characterization of an unknown target environment. To capture the same physical phenomena from battlefield targets as the composite system, the suite of ground-based sensors can be expanded to include imaging and video capabilities. The spatial density of deployed sensor nodes is increased to allow more precise ground-based location and tracking of detected targets by active nodes. The "swarm" mobile agents enabling WSN intelligence are organized in a three processing stages: detection, recognition and sustained tracking of ground targets. Features formed from the compressed sensor data are down-selected according to an information-theoretic algorithm that reduces redundancy within the feature set, reducing the dimension of samples used in the target

Targeted Re-Sequencing Emulsion PCR Panel for Myopathies: Results in 94 Cases.

PubMed

Punetha, Jaya; Kesari, Akanchha; Uapinyoying, Prech; Giri, Mamta; Clarke, Nigel F; Waddell, Leigh B; North, Kathryn N; Ghaoui, Roula; O'Grady, Gina L; Oates, Emily C; Sandaradura, Sarah A; Bönnemann, Carsten G; Donkervoort, Sandra; Plotz, Paul H; Smith, Edward C; Tesi-Rocha, Carolina; Bertorini, Tulio E; Tarnopolsky, Mark A; Reitter, Bernd; Hausmanowa-Petrusewicz, Irena; Hoffman, Eric P

2016-05-27

Molecular diagnostics in the genetic myopathies often requires testing of the largest and most complex transcript units in the human genome (DMD, TTN, NEB). Iteratively targeting single genes for sequencing has traditionally entailed high costs and long turnaround times. Exome sequencing has begun to supplant single targeted genes, but there are concerns regarding coverage and needed depth of the very large and complex genes that frequently cause myopathies. To evaluate efficiency of next-generation sequencing technologies to provide molecular diagnostics for patients with previously undiagnosed myopathies. We tested a targeted re-sequencing approach, using a 45 gene emulsion PCR myopathy panel, with subsequent sequencing on the Illumina platform in 94 undiagnosed patients. We compared the targeted re-sequencing approach to exome sequencing for 10 of these patients studied. We detected likely pathogenic mutations in 33 out of 94 patients with a molecular diagnostic rate of approximately 35%. The remaining patients showed variants of unknown significance (35/94 patients) or no mutations detected in the 45 genes tested (26/94 patients). Mutation detection rates for targeted re-sequencing vs. whole exome were similar in both methods; however exome sequencing showed better distribution of reads and fewer exon dropouts. Given that costs of highly parallel re-sequencing and whole exome sequencing are similar, and that exome sequencing now takes considerably less laboratory processing time than targeted re-sequencing, we recommend exome sequencing as the standard approach for molecular diagnostics of myopathies.

The eukaryotic signal sequence, YGRL, targets the chlamydial inclusion

PubMed Central

Kabeiseman, Emily J.; Cichos, Kyle H.; Moore, Elizabeth R.

2014-01-01

Understanding how host proteins are targeted to pathogen-specified organelles, like the chlamydial inclusion, is fundamentally important to understanding the biogenesis of these unique subcellular compartments and how they maintain autonomy within the cell. Syntaxin 6, which localizes to the chlamydial inclusion, contains an YGRL signal sequence. The YGRL functions to return syntaxin 6 to the trans-Golgi from the plasma membrane, and deletion of the YGRL signal sequence from syntaxin 6 also prevents the protein from localizing to the chlamydial inclusion. YGRL is one of three YXXL (YGRL, YQRL, and YKGL) signal sequences which target proteins to the trans-Golgi. We designed various constructs of eukaryotic proteins to test the specificity and propensity of YXXL sequences to target the inclusion. The YGRL signal sequence redirects proteins (e.g., Tgn38, furin, syntaxin 4) that normally do not localize to the chlamydial inclusion. Further, the requirement of the YGRL signal sequence for syntaxin 6 localization to inclusions formed by different species of Chlamydia is conserved. These data indicate that there is an inherent property of the chlamydial inclusion, which allows it to recognize the YGRL signal sequence. To examine whether this “inherent property” was protein or lipid in nature, we asked if deletion of the YGRL signal sequence from syntaxin 6 altered the ability of the protein to interact with proteins or lipids. Deletion or alteration of the YGRL from syntaxin 6 does not appreciably impact syntaxin 6-protein interactions, but does decrease syntaxin 6-lipid interactions. Intriguingly, data also demonstrate that YKGL or YQRL can successfully substitute for YGRL in localization of syntaxin 6 to the chlamydial inclusion. Importantly and for the first time, we are establishing that a eukaryotic signal sequence targets the chlamydial inclusion. PMID:25309881

Structural basis for the recognition of guide RNA and target DNA heteroduplex by Argonaute.

PubMed

Miyoshi, Tomohiro; Ito, Kosuke; Murakami, Ryo; Uchiumi, Toshio

2016-06-21

Argonaute proteins are key players in the gene silencing mechanisms mediated by small nucleic acids in all domains of life from bacteria to eukaryotes. However, little is known about the Argonaute protein that recognizes guide RNA/target DNA. Here, we determine the 2 Å crystal structure of Rhodobacter sphaeroides Argonaute (RsAgo) in a complex with 18-nucleotide guide RNA and its complementary target DNA. The heteroduplex maintains Watson-Crick base-pairing even in the 3'-region of the guide RNA between the N-terminal and PIWI domains, suggesting a recognition mode by RsAgo for stable interaction with the target strand. In addition, the MID/PIWI interface of RsAgo has a system that specifically recognizes the 5' base-U of the guide RNA, and the duplex-recognition loop of the PAZ domain is important for the DNA silencing activity. Furthermore, we show that Argonaute discriminates the nucleic acid type (RNA/DNA) by recognition of the duplex structure of the seed region.

Vander Lugt correlation of DNA sequence data

NASA Astrophysics Data System (ADS)

Christens-Barry, William A.; Hawk, James F.; Martin, James C.

1990-12-01

DNA, the molecule containing the genetic code of an organism, is a linear chain of subunits. It is the sequence of subunits, of which there are four kinds, that constitutes the unique blueprint of an individual. This sequence is the focus of a large number of analyses performed by an army of geneticists, biologists, and computer scientists. Most of these analyses entail searches for specific subsequences within the larger set of sequence data. Thus, most analyses are essentially pattern recognition or correlation tasks. Yet, there are special features to such analysis that influence the strategy and methods of an optical pattern recognition approach. While the serial processing employed in digital electronic computers remains the main engine of sequence analyses, there is no fundamental reason that more efficient parallel methods cannot be used. We describe an approach using optical pattern recognition (OPR) techniques based on matched spatial filtering. This allows parallel comparison of large blocks of sequence data. In this study we have simulated a Vander Lugt1 architecture implementing our approach. Searches for specific target sequence strings within a block of DNA sequence from the Co/El plasmid2 are performed.

Foundations for a syntatic pattern recognition system for genomic DNA sequences

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

Searles, D.B.

1993-03-01

The goal of the proposed work is the creation of a software system that will perform sophisticated pattern recognition and related functions at a level of abstraction and with expressive power beyond current general-purpose pattern-matching systems for biological sequences; and with a more uniform language, environment, and graphical user interface, and with greater flexibility, extensibility, embeddability, and ability to incorporate other algorithms, than current special-purpose analytic software.

The striking similarities between standard, distractor-free, and target-free recognition

PubMed Central

Dobbins, Ian G.

2012-01-01

It is often assumed that observers seek to maximize correct responding during recognition testing by actively adjusting a decision criterion. However, early research by Wallace (Journal of Experimental Psychology: Human Learning and Memory 4:441–452, 1978) suggested that recognition rates for studied items remained similar, regardless of whether or not the tests contained distractor items. We extended these findings across three experiments, addressing whether detection rates or observer confidence changed when participants were presented standard tests (targets and distractors) versus “pure-list” tests (lists composed entirely of targets or distractors). Even when observers were made aware of the composition of the pure-list test, the endorsement rates and confidence patterns remained largely similar to those observed during standard testing, suggesting that observers are typically not striving to maximize the likelihood of success across the test. We discuss the implications for decision models that assume a likelihood ratio versus a strength decision axis, as well as the implications for prior findings demonstrating large criterion shifts using target probability manipulations. PMID:21476108

Fluorescence self-quenching assay for the detection of target collagen sequences using a short probe peptide.

PubMed

Nian, Linge; Hu, Yue; Fu, Caihong; Song, Chen; Wang, Jie; Xiao, Jianxi

2018-01-01

The development of novel assays to detect collagen fragments is of utmost importance for diagnostic, prognostic and therapeutic decisions in various collagen-related diseases, and one essential question is to discover probe peptides that can specifically recognize target collagen sequences. Herein we have developed the fluorescence self-quenching assay as a convenient tool to screen the capability of a series of fluorescent probe peptides of variable lengths to bind with target collagen peptides. We have revealed that the targeting ability of probe peptides is length-dependent, and have discovered a relatively short probe peptide FAM-G(POG) 8 capable to identify the target peptide. We have further demonstrated that fluorescence self-quenching assay together with this short probe peptide can be applied to specifically detect the desired collagen fragment in complex biological media. Fluorescence self-quenching assay provides a powerful new tool to discover effective peptides for the recognition of collagen biomarkers, and it may have great potential to identify probe peptides for various protein biomarkers involved in pathological conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Automated Target Acquisition, Recognition and Tracking (ATTRACT). Phase 1

NASA Technical Reports Server (NTRS)

Abdallah, Mahmoud A.

1995-01-01

The primary objective of phase 1 of this research project is to conduct multidisciplinary research that will contribute to fundamental scientific knowledge in several of the USAF critical technology areas. Specifically, neural networks, signal processing techniques, and electro-optic capabilities are utilized to solve problems associated with automated target acquisition, recognition, and tracking. To accomplish the stated objective, several tasks have been identified and were executed.

Learning and Recognition of a Non-conscious Sequence of Events in Human Primary Visual Cortex.

PubMed

Rosenthal, Clive R; Andrews, Samantha K; Antoniades, Chrystalina A; Kennard, Christopher; Soto, David

2016-03-21

Human primary visual cortex (V1) has long been associated with learning simple low-level visual discriminations [1] and is classically considered outside of neural systems that support high-level cognitive behavior in contexts that differ from the original conditions of learning, such as recognition memory [2, 3]. Here, we used a novel fMRI-based dichoptic masking protocol-designed to induce activity in V1, without modulation from visual awareness-to test whether human V1 is implicated in human observers rapidly learning and then later (15-20 min) recognizing a non-conscious and complex (second-order) visuospatial sequence. Learning was associated with a change in V1 activity, as part of a temporo-occipital and basal ganglia network, which is at variance with the cortico-cerebellar network identified in prior studies of "implicit" sequence learning that involved motor responses and visible stimuli (e.g., [4]). Recognition memory was associated with V1 activity, as part of a temporo-occipital network involving the hippocampus, under conditions that were not imputable to mechanisms associated with conscious retrieval. Notably, the V1 responses during learning and recognition separately predicted non-conscious recognition memory, and functional coupling between V1 and the hippocampus was enhanced for old retrieval cues. The results provide a basis for novel hypotheses about the signals that can drive recognition memory, because these data (1) identify human V1 with a memory network that can code complex associative serial visuospatial information and support later non-conscious recognition memory-guided behavior (cf. [5]) and (2) align with mouse models of experience-dependent V1 plasticity in learning and memory [6]. Copyright © 2016 Elsevier Ltd. All rights reserved.

Structural basis for microRNA targeting

DOE PAGES

Schirle, Nicole T.; Sheu-Gruttadauria, Jessica; MacRae, Ian J.

2014-10-31

MicroRNAs (miRNAs) control expression of thousands of genes in plants and animals. miRNAs function by guiding Argonaute proteins to complementary sites in messenger RNAs (mRNAs) targeted for repression. In this paper, we determined crystal structures of human Argonaute-2 (Ago2) bound to a defined guide RNA with and without target RNAs representing miRNA recognition sites. These structures suggest a stepwise mechanism, in which Ago2 primarily exposes guide nucleotides (nt) 2 to 5 for initial target pairing. Pairing to nt 2 to 5 promotes conformational changes that expose nt 2 to 8 and 13 to 16 for further target recognition. Interactions withmore » the guide-target minor groove allow Ago2 to interrogate target RNAs in a sequence-independent manner, whereas an adenosine binding-pocket opposite guide nt 1 further facilitates target recognition. Spurious slicing of miRNA targets is avoided through an inhibitory coordination of one catalytic magnesium ion. Finally, these results explain the conserved nucleotide-pairing patterns in animal miRNA target sites first observed over two decades ago.« less

A tale of two sequences: microRNA-target chimeric reads.

PubMed

Broughton, James P; Pasquinelli, Amy E

2016-04-04

In animals, a functional interaction between a microRNA (miRNA) and its target RNA requires only partial base pairing. The limited number of base pair interactions required for miRNA targeting provides miRNAs with broad regulatory potential and also makes target prediction challenging. Computational approaches to target prediction have focused on identifying miRNA target sites based on known sequence features that are important for canonical targeting and may miss non-canonical targets. Current state-of-the-art experimental approaches, such as CLIP-seq (cross-linking immunoprecipitation with sequencing), PAR-CLIP (photoactivatable-ribonucleoside-enhanced CLIP), and iCLIP (individual-nucleotide resolution CLIP), require inference of which miRNA is bound at each site. Recently, the development of methods to ligate miRNAs to their target RNAs during the preparation of sequencing libraries has provided a new tool for the identification of miRNA target sites. The chimeric, or hybrid, miRNA-target reads that are produced by these methods unambiguously identify the miRNA bound at a specific target site. The information provided by these chimeric reads has revealed extensive non-canonical interactions between miRNAs and their target mRNAs, and identified many novel interactions between miRNAs and noncoding RNAs.

Recognition of the DNA sequence by an inorganic crystal surface

PubMed Central

Sampaolese, Beatrice; Bergia, Anna; Scipioni, Anita; Zuccheri, Giampaolo; Savino, Maria; Samorì, Bruno; De Santis, Pasquale

2002-01-01

The sequence-dependent curvature is generally recognized as an important and biologically relevant property of DNA because it is involved in the formation and stability of association complexes with proteins. When a DNA tract, intrinsically curved for the periodical recurrence on the same strand of A-tracts phased with the B-DNA periodicity, is deposited on a flat surface, it exposes to that surface either a T- or an A-rich face. The surface of a freshly cleaved mica crystal recognizes those two faces and preferentially interacts with the former one. Statistical analysis of scanning force microscopy (SFM) images provides evidence of this recognition between an inorganic crystal surface and nanoscale structures of double-stranded DNA. This finding could open the way toward the use of the sequence-dependent adhesion to specific crystal faces for nanotechnological purposes. PMID:12361979

The chaperonin-60 universal target is a barcode for bacteria that enables de novo assembly of metagenomic sequence data.

PubMed

Links, Matthew G; Dumonceaux, Tim J; Hemmingsen, Sean M; Hill, Janet E

2012-01-01

Barcoding with molecular sequences is widely used to catalogue eukaryotic biodiversity. Studies investigating the community dynamics of microbes have relied heavily on gene-centric metagenomic profiling using two genes (16S rRNA and cpn60) to identify and track Bacteria. While there have been criteria formalized for barcoding of eukaryotes, these criteria have not been used to evaluate gene targets for other domains of life. Using the framework of the International Barcode of Life we evaluated DNA barcodes for Bacteria. Candidates from the 16S rRNA gene and the protein coding cpn60 gene were evaluated. Within complete bacterial genomes in the public domain representing 983 species from 21 phyla, the largest difference between median pairwise inter- and intra-specific distances ("barcode gap") was found from cpn60. Distribution of sequence diversity along the ∼555 bp cpn60 target region was remarkably uniform. The barcode gap of the cpn60 universal target facilitated the faithful de novo assembly of full-length operational taxonomic units from pyrosequencing data from a synthetic microbial community. Analysis supported the recognition of both 16S rRNA and cpn60 as DNA barcodes for Bacteria. The cpn60 universal target was found to have a much larger barcode gap than 16S rRNA suggesting cpn60 as a preferred barcode for Bacteria. A large barcode gap for cpn60 provided a robust target for species-level characterization of data. The assembly of consensus sequences for barcodes was shown to be a reliable method for the identification and tracking of novel microbes in metagenomic studies.

A hierarchical, automated target recognition algorithm for a parallel analog processor

NASA Technical Reports Server (NTRS)

Woodward, Gail; Padgett, Curtis

1997-01-01

A hierarchical approach is described for an automated target recognition (ATR) system, VIGILANTE, that uses a massively parallel, analog processor (3DANN). The 3DANN processor is capable of performing 64 concurrent inner products of size 1x4096 every 250 nanoseconds.

PHYSICAL MODEL FOR RECOGNITION TUNNELING

PubMed Central

Krstić, Predrag; Ashcroft, Brian; Lindsay, Stuart

2015-01-01

Recognition tunneling (RT) identifies target molecules trapped between tunneling electrodes functionalized with recognition molecules that serve as specific chemical linkages between the metal electrodes and the trapped target molecule. Possible applications include single molecule DNA and protein sequencing. This paper addresses several fundamental aspects of RT by multiscale theory, applying both all-atom and coarse-grained DNA models: (1) We show that the magnitude of the observed currents are consistent with the results of non-equilibrium Green's function calculations carried out on a solvated all-atom model. (2) Brownian fluctuations in hydrogen bond-lengths lead to current spikes that are similar to what is observed experimentally. (3) The frequency characteristics of these fluctuations can be used to identify the trapped molecules with a machine-learning algorithm, giving a theoretical underpinning to this new method of identifying single molecule signals. PMID:25650375

Structural basis for the recognition of guide RNA and target DNA heteroduplex by Argonaute

PubMed Central

Miyoshi, Tomohiro; Ito, Kosuke; Murakami, Ryo; Uchiumi, Toshio

2016-01-01

Argonaute proteins are key players in the gene silencing mechanisms mediated by small nucleic acids in all domains of life from bacteria to eukaryotes. However, little is known about the Argonaute protein that recognizes guide RNA/target DNA. Here, we determine the 2 Å crystal structure of Rhodobacter sphaeroides Argonaute (RsAgo) in a complex with 18-nucleotide guide RNA and its complementary target DNA. The heteroduplex maintains Watson–Crick base-pairing even in the 3′-region of the guide RNA between the N-terminal and PIWI domains, suggesting a recognition mode by RsAgo for stable interaction with the target strand. In addition, the MID/PIWI interface of RsAgo has a system that specifically recognizes the 5′ base-U of the guide RNA, and the duplex-recognition loop of the PAZ domain is important for the DNA silencing activity. Furthermore, we show that Argonaute discriminates the nucleic acid type (RNA/DNA) by recognition of the duplex structure of the seed region. PMID:27325485

Convolutional neural networks based on augmented training samples for synthetic aperture radar target recognition

NASA Astrophysics Data System (ADS)

Yan, Yue

2018-03-01

A synthetic aperture radar (SAR) automatic target recognition (ATR) method based on the convolutional neural networks (CNN) trained by augmented training samples is proposed. To enhance the robustness of CNN to various extended operating conditions (EOCs), the original training images are used to generate the noisy samples at different signal-to-noise ratios (SNRs), multiresolution representations, and partially occluded images. Then, the generated images together with the original ones are used to train a designed CNN for target recognition. The augmented training samples can contrapuntally improve the robustness of the trained CNN to the covered EOCs, i.e., the noise corruption, resolution variance, and partial occlusion. Moreover, the significantly larger training set effectively enhances the representation capability for other conditions, e.g., the standard operating condition (SOC), as well as the stability of the network. Therefore, better performance can be achieved by the proposed method for SAR ATR. For experimental evaluation, extensive experiments are conducted on the Moving and Stationary Target Acquisition and Recognition dataset under SOC and several typical EOCs.

Target-context unitization effect on the familiarity-related FN400: a face recognition exclusion task.

PubMed

Guillaume, Fabrice; Etienne, Yann

2015-03-01

Using two exclusion tasks, the present study examined how the ERP correlates of face recognition are affected by the nature of the information to be retrieved. Intrinsic (facial expression) and extrinsic (background scene) visual information were paired with face identity and constituted the exclusion criterion at test time. Although perceptual information had to be taken into account in both situations, the FN400 old-new effect was observed only for old target faces on the expression-exclusion task, whereas it was found for both old target and old non-target faces in the background-exclusion situation. These results reveal that the FN400, which is generally interpreted as a correlate of familiarity, was modulated by the retrieval of intra-item and intrinsic face information, but not by the retrieval of extrinsic information. The observed effects on the FN400 depended on the nature of the information to be retrieved and its relationship (unitization) to the recognition target. On the other hand, the parietal old-new effect (generally described as an ERP correlate of recollection) reflected the retrieval of both types of contextual features equivalently. The current findings are discussed in relation to recent controversies about the nature of the recognition processes reflected by the ERP correlates of face recognition. Copyright © 2015 Elsevier B.V. All rights reserved.

[Target gene sequence capture and next generation sequencing technology to diagnose four children with Alagille syndrome].

PubMed

Gao, M L; Zhong, X M; Ma, X; Ning, H J; Zhu, D; Zou, J Z

2016-06-02

To make genetic diagnosis of Alagille syndrome (ALGS) patients using target gene sequence capture and next generation sequencing technology. Target gene sequence capture and next generation sequencing were used to detect ALGS gene of 4 patients. They were hospitalized at the Affiliated Hospital, Capital Institute of Pediatrics between January 2014 and December 2015, referred to clinical diagnosis of ALGS typical and atypical respectively in 2 cases. Blood samples were collected from patients and their parents and genomic DNA was extracted from lymphocytes. Target gene sequence capture and next generation sequencing was detected. Sanger sequencing was used to confirm the results of the patients and their parents. Cholestasis, heart defects, inverted triangular face and butterfly vertebrae were presented as main clinical features in 4 male patients. The first hospital visiting ages ranged from 3 months and 14 days to 3 years and 1 month. The age of onset ranged from 3 days to 42 days (median 23 days). According to the clinical diagnostic criteria of ALGS, patient 1 and patient 2 were considered as typical ALGS. The other 2 patients were considered as atypical ALGS. Four Jagged 1(JAG1) pathogenic mutations were detected. Three different missense mutations were detected in patient 1 to patient 3 with ALGS(c.839C>T(p.W280X), c. 703G>A(p.R235X), c. 1720C>T(p.V574M)). The JAG1 mutation of patient 3 was first reported. Patient 4 had one novel insertion mutation (c.1779_1780insA(p.Ile594AsnfsTer23)). Parental analysis verified that the JAG1 missense mutation of 3 patients were de novo. The results of sanger sequencing was consistent with the results of the next generation sequencing. Target gene sequence capture combined with next generation sequencing can detect two pathogenic genes in ALGS and test genes of other related diseases in infantile cholestatic diseases simultaneously and presents a high throughput, high efficiency and low cost. It may provide molecular

HybPiper: Extracting coding sequence and introns for phylogenetics from high-throughput sequencing reads using target enrichment1

PubMed Central

Johnson, Matthew G.; Gardner, Elliot M.; Liu, Yang; Medina, Rafael; Goffinet, Bernard; Shaw, A. Jonathan; Zerega, Nyree J. C.; Wickett, Norman J.

2016-01-01

Premise of the study: Using sequence data generated via target enrichment for phylogenetics requires reassembly of high-throughput sequence reads into loci, presenting a number of bioinformatics challenges. We developed HybPiper as a user-friendly platform for assembly of gene regions, extraction of exon and intron sequences, and identification of paralogous gene copies. We test HybPiper using baits designed to target 333 phylogenetic markers and 125 genes of functional significance in Artocarpus (Moraceae). Methods and Results: HybPiper implements parallel execution of sequence assembly in three phases: read mapping, contig assembly, and target sequence extraction. The pipeline was able to recover nearly complete gene sequences for all genes in 22 species of Artocarpus. HybPiper also recovered more than 500 bp of nontargeted intron sequence in over half of the phylogenetic markers and identified paralogous gene copies in Artocarpus. Conclusions: HybPiper was designed for Linux and Mac OS X and is freely available at https://github.com/mossmatters/HybPiper. PMID:27437175

Deep Learning Methods for Underwater Target Feature Extraction and Recognition

PubMed Central

Peng, Yuan; Qiu, Mengran; Shi, Jianfei; Liu, Liangliang

2018-01-01

The classification and recognition technology of underwater acoustic signal were always an important research content in the field of underwater acoustic signal processing. Currently, wavelet transform, Hilbert-Huang transform, and Mel frequency cepstral coefficients are used as a method of underwater acoustic signal feature extraction. In this paper, a method for feature extraction and identification of underwater noise data based on CNN and ELM is proposed. An automatic feature extraction method of underwater acoustic signals is proposed using depth convolution network. An underwater target recognition classifier is based on extreme learning machine. Although convolution neural networks can execute both feature extraction and classification, their function mainly relies on a full connection layer, which is trained by gradient descent-based; the generalization ability is limited and suboptimal, so an extreme learning machine (ELM) was used in classification stage. Firstly, CNN learns deep and robust features, followed by the removing of the fully connected layers. Then ELM fed with the CNN features is used as the classifier to conduct an excellent classification. Experiments on the actual data set of civil ships obtained 93.04% recognition rate; compared to the traditional Mel frequency cepstral coefficients and Hilbert-Huang feature, recognition rate greatly improved. PMID:29780407

Enrichment of target sequences for next-generation sequencing applications in research and diagnostics.

PubMed

Altmüller, Janine; Budde, Birgit S; Nürnberg, Peter

2014-02-01

Abstract Targeted re-sequencing such as gene panel sequencing (GPS) has become very popular in medical genetics, both for research projects and in diagnostic settings. The technical principles of the different enrichment methods have been reviewed several times before; however, new enrichment products are constantly entering the market, and researchers are often puzzled about the requirement to take decisions about long-term commitments, both for the enrichment product and the sequencing technology. This review summarizes important considerations for the experimental design and provides helpful recommendations in choosing the best sequencing strategy for various research projects and diagnostic applications.

Intravenous phage display identifies peptide sequences that target the burn-injured intestine.

PubMed

Costantini, Todd W; Eliceiri, Brian P; Putnam, James G; Bansal, Vishal; Baird, Andrew; Coimbra, Raul

2012-11-01

The injured intestine is responsible for significant morbidity and mortality after severe trauma and burn; however, targeting the intestine with therapeutics aimed at decreasing injury has proven difficult. We hypothesized that we could use intravenous phage display technology to identify peptide sequences that target the injured intestinal mucosa in a murine model, and then confirm the cross-reactivity of this peptide sequence with ex vivo human gut. Four hours following 30% TBSA burn we performed an in vivo, intravenous systemic administration of phage library containing 10(12) phage in balb/c mice to biopan for gut-targeting peptides. In vivo assessment of the candidate peptide sequences identified after 4 rounds of internalization was performed by injecting 1×10(12) copies of each selected phage clone into sham or burned animals. Internalization into the gut was assessed using quantitative polymerase chain reaction. We then incubated this gut-targeting peptide sequence with human intestine and visualized fluorescence using confocal microscopy. We identified 3 gut-targeting peptide sequences which caused collapse of the phage library (4-1: SGHQLLLNKMP, 4-5: ILANDLTAPGPR, 4-11: SFKPSGLPAQSL). Sequence 4-5 was internalized into the intestinal mucosa of burned animals 9.3-fold higher than sham animals injected with the same sequence (2.9×10(5)vs. 3.1×10(4) particles per mg tissue). Sequences 4-1 and 4-11 were both internalized into the gut, but did not demonstrate specificity for the injured mucosa. Phage sequence 4-11 demonstrated cross-reactivity with human intestine. In the future, this gut-targeting peptide sequence could serve as a platform for the delivery of biotherapeutics. Copyright © 2012 Elsevier Inc. All rights reserved.

Targeted exome sequencing of suspected mitochondrial disorders

PubMed Central

Lieber, Daniel S.; Calvo, Sarah E.; Shanahan, Kristy; Slate, Nancy G.; Liu, Shangtao; Hershman, Steven G.; Gold, Nina B.; Chapman, Brad A.; Thorburn, David R.; Berry, Gerard T.; Schmahmann, Jeremy D.; Borowsky, Mark L.; Mueller, David M.; Sims, Katherine B.

2013-01-01

Objective: To evaluate the utility of targeted exome sequencing for the molecular diagnosis of mitochondrial disorders, which exhibit marked phenotypic and genetic heterogeneity. Methods: We considered a diverse set of 102 patients with suspected mitochondrial disorders based on clinical, biochemical, and/or molecular findings, and whose disease ranged from mild to severe, with varying age at onset. We sequenced the mitochondrial genome (mtDNA) and the exons of 1,598 nuclear-encoded genes implicated in mitochondrial biology, mitochondrial disease, or monogenic disorders with phenotypic overlap. We prioritized variants likely to underlie disease and established molecular diagnoses in accordance with current clinical genetic guidelines. Results: Targeted exome sequencing yielded molecular diagnoses in established disease loci in 22% of cases, including 17 of 18 (94%) with prior molecular diagnoses and 5 of 84 (6%) without. The 5 new diagnoses implicated 2 genes associated with canonical mitochondrial disorders (NDUFV1, POLG2), and 3 genes known to underlie other neurologic disorders (DPYD, KARS, WFS1), underscoring the phenotypic and biochemical overlap with other inborn errors. We prioritized variants in an additional 26 patients, including recessive, X-linked, and mtDNA variants that were enriched 2-fold over background and await further support of pathogenicity. In one case, we modeled patient mutations in yeast to provide evidence that recessive mutations in ATP5A1 can underlie combined respiratory chain deficiency. Conclusion: The results demonstrate that targeted exome sequencing is an effective alternative to the sequential testing of mtDNA and individual nuclear genes as part of the investigation of mitochondrial disease. Our study underscores the ongoing challenge of variant interpretation in the clinical setting. PMID:23596069

Integrated approach for automatic target recognition using a network of collaborative sensors.

PubMed

Mahalanobis, Abhijit; Van Nevel, Alan

2006-10-01

We introduce what is believed to be a novel concept by which several sensors with automatic target recognition (ATR) capability collaborate to recognize objects. Such an approach would be suitable for netted systems in which the sensors and platforms can coordinate to optimize end-to-end performance. We use correlation filtering techniques to facilitate the development of the concept, although other ATR algorithms may be easily substituted. Essentially, a self-configuring geometry of netted platforms is proposed that positions the sensors optimally with respect to each other, and takes into account the interactions among the sensor, the recognition algorithms, and the classes of the objects to be recognized. We show how such a paradigm optimizes overall performance, and illustrate the collaborative ATR scheme for recognizing targets in synthetic aperture radar imagery by using viewing position as a sensor parameter.

Design of the hairpin ribozyme for targeting specific RNA sequences.

PubMed

Hampel, A; DeYoung, M B; Galasinski, S; Siwkowski, A

1997-01-01

The following steps should be taken when designing the hairpin ribozyme to cleave a specific target sequence: 1. Select a target sequence containing BN*GUC where B is C, G, or U. 2. Select the target sequence in areas least likely to have extensive interfering structure. 3. Design the conventional hairpin ribozyme as shown in Fig. 1, such that it can form a 4 bp helix 2 and helix 1 lengths up to 10 bp. 4. Synthesize this ribozyme from single-stranded DNA templates with a double-stranded T7 promoter. 5. Prepare a series of short substrates capable of forming a range of helix 1 lengths of 5-10 bp. 6. Identify these by direct RNA sequencing. 7. Assay the extent of cleavage of each substrate to identify the optimal length of helix 1. 8. Prepare the hairpin tetraloop ribozyme to determine if catalytic efficiency can be improved.

A long-term target detection approach in infrared image sequence

NASA Astrophysics Data System (ADS)

Li, Hang; Zhang, Qi; Wang, Xin; Hu, Chao

2016-10-01

An automatic target detection method used in long term infrared (IR) image sequence from a moving platform is proposed. Firstly, based on POME(the principle of maximum entropy), target candidates are iteratively segmented. Then the real target is captured via two different selection approaches. At the beginning of image sequence, the genuine target with litter texture is discriminated from other candidates by using contrast-based confidence measure. On the other hand, when the target becomes larger, we apply online EM method to estimate and update the distributions of target's size and position based on the prior detection results, and then recognize the genuine one which satisfies both the constraints of size and position. Experimental results demonstrate that the presented method is accurate, robust and efficient.

Research and Development of Target Recognition and Location Crawling Platform based on Binocular Vision

NASA Astrophysics Data System (ADS)

Xu, Weidong; Lei, Zhu; Yuan, Zhang; Gao, Zhenqing

2018-03-01

The application of visual recognition technology in industrial robot crawling and placing operation is one of the key tasks in the field of robot research. In order to improve the efficiency and intelligence of the material sorting in the production line, especially to realize the sorting of the scattered items, the robot target recognition and positioning crawling platform based on binocular vision is researched and developed. The images were collected by binocular camera, and the images were pretreated. Harris operator was used to identify the corners of the images. The Canny operator was used to identify the images. Hough-chain code recognition was used to identify the images. The target image in the image, obtain the coordinates of each vertex of the image, calculate the spatial position and posture of the target item, and determine the information needed to capture the movement and transmit it to the robot control crawling operation. Finally, In this paper, we use this method to experiment the wrapping problem in the express sorting process The experimental results show that the platform can effectively solve the problem of sorting of loose parts, so as to achieve the purpose of efficient and intelligent sorting.

Simultaneous fluorescence light-up and selective multicolor nucleobase recognition based on sequence-dependent strong binding of berberine to DNA abasic site.

PubMed

Wu, Fei; Shao, Yong; Ma, Kun; Cui, Qinghua; Liu, Guiying; Xu, Shujuan

2012-04-28

Label-free DNA nucleobase recognition by fluorescent small molecules has received much attention due to its simplicity in mutation identification and drug screening. However, sequence-dependent fluorescence light-up nucleobase recognition and multicolor emission with individual emission energy for individual nucleobases have been seldom realized. Herein, an abasic site (AP site) in a DNA duplex was employed as a binding field for berberine, one of isoquinoline alkaloids. Unlike weak binding of berberine to the fully matched DNAs without the AP site, strong binding of berberine to the AP site occurs and the berberine's fluorescence light-up behaviors are highly dependent on the target nucleobases opposite the AP site in which the targets thymine and cytosine produce dual emission bands, while the targets guanine and adenine only give a single emission band. Furthermore, more intense emissions are observed for the target pyrimidines than purines. The flanking bases of the AP site also produce some modifications of the berberine's emission behavior. The binding selectivity of berberine at the AP site is also confirmed by measurements of fluorescence resonance energy transfer, excited-state lifetime, DNA melting and fluorescence quenching by ferrocyanide and sodium chloride. It is expected that the target pyrimidines cause berberine to be stacked well within DNA base pairs near the AP site, which results in a strong resonance coupling of the electronic transitions to the particular vibration mode to produce the dual emissions. The fluorescent signal-on and emission energy-modulated sensing for nucleobases based on this fluorophore is substantially advantageous over the previously used fluorophores. We expect that this approach will be developed as a practical device for differentiating pyrimidines from purines by positioning an AP site toward a target that is available for readout by this alkaloid probe. This journal is © The Royal Society of Chemistry 2012

Structural Insights Into the Recognition of Peroxisomal Targeting Signal 1 By Trypanosoma Brucei Peroxin 5

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

Sampathkumar, P.; Roach, C.; Michels, P.A.M.

2009-05-27

Glycosomes are peroxisome-like organelles essential for trypanosomatid parasites. Glycosome biogenesis is mediated by proteins called 'peroxins,' which are considered to be promising drug targets in pathogenic Trypanosomatidae. The first step during protein translocation across the glycosomal membrane of peroxisomal targeting signal 1 (PTS1)-harboring proteins is signal recognition by the cytosolic receptor peroxin 5 (PEX5). The C-terminal PTS1 motifs interact with the PTS1 binding domain (P1BD) of PEX5, which is made up of seven tetratricopeptide repeats. Obtaining diffraction-quality crystals of the P1BD of Trypanosoma brucei PEX5 (TbPEX5) required surface entropy reduction mutagenesis. Each of the seven tetratricopeptide repeats appears to havemore » a residue in the alpha(L) conformation in the loop connecting helices A and B. Five crystal structures of the P1BD of TbPEX5 were determined, each in complex with a hepta- or decapeptide corresponding to a natural or nonnatural PTS1 sequence. The PTS1 peptides are bound between the two subdomains of the P1BD. These structures indicate precise recognition of the C-terminal Leu of the PTS1 motif and important interactions between the PTS1 peptide main chain and up to five invariant Asn side chains of PEX5. The TbPEX5 structures reported here reveal a unique hydrophobic pocket in the subdomain interface that might be explored to obtain compounds that prevent relative motions of the subdomains and interfere selectively with PTS1 motif binding or release in trypanosomatids, and would therefore disrupt glycosome biogenesis and prevent parasite growth.« less

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

NASA Technical Reports Server (NTRS)

Tescher, Andrew G. (Editor)

1989-01-01

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

Extracting features from protein sequences to improve deep extreme learning machine for protein fold recognition.

PubMed

Ibrahim, Wisam; Abadeh, Mohammad Saniee

2017-05-21

Protein fold recognition is an important problem in bioinformatics to predict three-dimensional structure of a protein. One of the most challenging tasks in protein fold recognition problem is the extraction of efficient features from the amino-acid sequences to obtain better classifiers. In this paper, we have proposed six descriptors to extract features from protein sequences. These descriptors are applied in the first stage of a three-stage framework PCA-DELM-LDA to extract feature vectors from the amino-acid sequences. Principal Component Analysis PCA has been implemented to reduce the number of extracted features. The extracted feature vectors have been used with original features to improve the performance of the Deep Extreme Learning Machine DELM in the second stage. Four new features have been extracted from the second stage and used in the third stage by Linear Discriminant Analysis LDA to classify the instances into 27 folds. The proposed framework is implemented on the independent and combined feature sets in SCOP datasets. The experimental results show that extracted feature vectors in the first stage could improve the performance of DELM in extracting new useful features in second stage. Copyright © 2017 Elsevier Ltd. All rights reserved.

Sequence-Specific Recognition of DNA by Proteins: Binding Motifs Discovered Using a Novel Statistical/Computational Analysis

PubMed Central

Jakubec, David; Laskowski, Roman A.; Vondrasek, Jiri

2016-01-01

Decades of intensive experimental studies of the recognition of DNA sequences by proteins have provided us with a view of a diverse and complicated world in which few to no features are shared between individual DNA-binding protein families. The originally conceived direct readout of DNA residue sequences by amino acid side chains offers very limited capacity for sequence recognition, while the effects of the dynamic properties of the interacting partners remain difficult to quantify and almost impossible to generalise. In this work we investigated the energetic characteristics of all DNA residue—amino acid side chain combinations in the conformations found at the interaction interface in a very large set of protein—DNA complexes by the means of empirical potential-based calculations. General specificity-defining criteria were derived and utilised to look beyond the binding motifs considered in previous studies. Linking energetic favourability to the observed geometrical preferences, our approach reveals several additional amino acid motifs which can distinguish between individual DNA bases. Our results remained valid in environments with various dielectric properties. PMID:27384774

Low, slow, small target recognition based on spatial vision network

NASA Astrophysics Data System (ADS)

Cheng, Zhao; Guo, Pei; Qi, Xin

2018-03-01

Traditional photoelectric monitoring is monitored using a large number of identical cameras. In order to ensure the full coverage of the monitoring area, this monitoring method uses more cameras, which leads to more monitoring and repetition areas, and higher costs, resulting in more waste. In order to reduce the monitoring cost and solve the difficult problem of finding, identifying and tracking a low altitude, slow speed and small target, this paper presents spatial vision network for low-slow-small targets recognition. Based on camera imaging principle and monitoring model, spatial vision network is modeled and optimized. Simulation experiment results demonstrate that the proposed method has good performance.

Genetic mutations in human rectal cancers detected by targeted sequencing.

PubMed

Bai, Jun; Gao, Jinglong; Mao, Zhijun; Wang, Jianhua; Li, Jianhui; Li, Wensheng; Lei, Yu; Li, Shuaishuai; Wu, Zhuo; Tang, Chuanning; Jones, Lindsey; Ye, Hua; Lou, Feng; Liu, Zhiyuan; Dong, Zhishou; Guo, Baishuai; Huang, Xue F; Chen, Si-Yi; Zhang, Enke

2015-10-01

Colorectal cancer (CRC) is widespread with significant mortality. Both inherited and sporadic mutations in various signaling pathways influence the development and progression of the cancer. Identifying genetic mutations in CRC is important for optimal patient treatment and many approaches currently exist to uncover these mutations, including next-generation sequencing (NGS) and commercially available kits. In the present study, we used a semiconductor-based targeted DNA-sequencing approach to sequence and identify genetic mutations in 91 human rectal cancer samples. Analysis revealed frequent mutations in KRAS (58.2%), TP53 (28.6%), APC (16.5%), FBXW7 (9.9%) and PIK3CA (9.9%), and additional mutations in BRAF, CTNNB1, ERBB2 and SMAD4 were also detected at lesser frequencies. Thirty-eight samples (41.8%) also contained two or more mutations, with common combination mutations occurring between KRAS and TP53 (42.1%), and KRAS and APC (31.6%). DNA sequencing for individual cancers is of clinical importance for targeted drug therapy and the advantages of such targeted gene sequencing over other NGS platforms or commercially available kits in sensitivity, cost and time effectiveness may aid clinicians in treating CRC patients in the near future.

Measurement Marker Recognition In A Time Sequence Of Infrared Images For Biomedical Applications

NASA Astrophysics Data System (ADS)

Fiorini, A. R.; Fumero, R.; Marchesi, R.

1986-03-01

In thermographic measurements, quantitative surface temperature evaluation is often uncertain. The main reason is in the lack of available reference points in transient conditions. Reflective markers were used for automatic marker recognition and pixel coordinate computations. An algorithm selects marker icons to match marker references where particular luminance conditions are satisfied. Automatic marker recognition allows luminance compensation and temperature calibration of recorded infrared images. A biomedical application is presented: the dynamic behaviour of the surface temperature distributions is investigated in order to study the performance of two different pumping systems for extracorporeal circulation. Sequences of images are compared and results are discussed. Finally, the algorithm allows to monitor the experimental environment and to alert for the presence of unusual experimental conditions.

HIV-1 gp140 epitope recognition is influenced by immunoglobulin DH gene segment sequence

PubMed Central

Wang, Yuge; Kapoor, Pratibha; Parks, Robert; Silva-Sanchez, Aaron; Alam, S. Munir; Verkoczy, Laurent; Liao, Hua-Xin; Zhuang, Yingxin; Burrows, Peter; Levinson, Michael; Elgavish, Ada; Cui, Xiangqin; Haynes, Barton F.; Schroeder, Harry

2015-01-01

Complementarity determining region 3 of the immunoglobulin (Ig) H chain (CDR-H3) lies at the center of the antigen binding site where it often plays a decisive role in antigen recognition and binding. Amino acids encoded by the diversity (DH) gene segment are the main component of CDR-H3. Each DH has the potential to rearrange into one of six DH reading frames (RFs), each of which exhibits a characteristic amino acid hydrophobicity signature that has been conserved among jawed vertebrates by natural selection. A preference for use of RF1 promotes the incorporation of tyrosine into CDR-H3 while suppressing the inclusion of hydrophobic or charged amino acids. To test the hypothesis that these evolutionary constraints on DH sequence influence epitope recognition, we used mice with a single DH that has been altered to preferentially use RF2 or inverted RF1. B cells in these mice produce a CDR-H3 repertoire that is enriched for valine or arginine in place of tyrosine. We serially immunized this panel of mice with gp140 from HIV-1 JR-FL isolate and then used ELISA or peptide microarray to assess antibody binding to key or overlapping HIV-1 envelope epitopes. By ELISA, serum reactivity to key epitopes varied by DH sequence. By microarray, sera with Ig CDR-H3s enriched for arginine bound to linear peptides with a greater range of hydrophobicity, but had a lower intensity of binding than sera containing Ig CDR-H3s enriched for tyrosine or valine. We conclude that patterns of epitope recognition and binding can be heavily influenced by DH germline sequence. This may help explain why antibodies in HIV infected patients must undergo extensive somatic mutation in order to bind to specific viral epitopes and achieve neutralization. PMID:26687685

Competitive Deep-Belief Networks for Underwater Acoustic Target Recognition

PubMed Central

Shen, Sheng; Yao, Xiaohui; Sheng, Meiping; Wang, Chen

2018-01-01

Underwater acoustic target recognition based on ship-radiated noise belongs to the small-sample-size recognition problems. A competitive deep-belief network is proposed to learn features with more discriminative information from labeled and unlabeled samples. The proposed model consists of four stages: (1) A standard restricted Boltzmann machine is pretrained using a large number of unlabeled data to initialize its parameters; (2) the hidden units are grouped according to categories, which provides an initial clustering model for competitive learning; (3) competitive training and back-propagation algorithms are used to update the parameters to accomplish the task of clustering; (4) by applying layer-wise training and supervised fine-tuning, a deep neural network is built to obtain features. Experimental results show that the proposed method can achieve classification accuracy of 90.89%, which is 8.95% higher than the accuracy obtained by the compared methods. In addition, the highest accuracy of our method is obtained with fewer features than other methods. PMID:29570642

A long-term target detection approach in infrared image sequence

NASA Astrophysics Data System (ADS)

Li, Hang; Zhang, Qi; Li, Yuanyuan; Wang, Liqiang

2015-12-01

An automatic target detection method used in long term infrared (IR) image sequence from a moving platform is proposed. Firstly, based on non-linear histogram equalization, target candidates are coarse-to-fine segmented by using two self-adapt thresholds generated in the intensity space. Then the real target is captured via two different selection approaches. At the beginning of image sequence, the genuine target with litter texture is discriminated from other candidates by using contrast-based confidence measure. On the other hand, when the target becomes larger, we apply online EM method to iteratively estimate and update the distributions of target's size and position based on the prior detection results, and then recognize the genuine one which satisfies both the constraints of size and position. Experimental results demonstrate that the presented method is accurate, robust and efficient.

Evaluation of target acquisition difficulty using recognition distance to measure required retinal area

NASA Astrophysics Data System (ADS)

Nilsson, Thomy H.

2001-09-01

The psychophysical method of limits was used to measure the distance at which observers could distinguish military vehicles photographed in natural landscapes. Obtained from the TNO-TM Search_2 dataset, these pictures either were rear-projected 35-mm slides or were presented on a computer monitor. Based on the rationale that more difficult vehicle targets would require more visual pathways for recognition, difficult of acquisition was defined in terms of the relative retinal area required for recognition. Relative retinal area was derived from the inverse square of the recognition distance of a particular vehicle relative to the distance of the vehicle that could be seen furthest away. Results are compared with data on the time required to find the vehicles in these pictures. These comparison indicate recognition distance thresholds can be a suitable means of defining standards for the effectiveness of vital graphic information; and the two methods are complementary with respect to distinguishing different degrees of acquisition difficulty, and together may provide a means to measure the total information processing required for recognition.

Infrared target simulation environment for pattern recognition applications

NASA Astrophysics Data System (ADS)

Savakis, Andreas E.; George, Nicholas

1994-07-01

The generation of complete databases of IR data is extremely useful for training human observers and testing automatic pattern recognition algorithms. Field data may be used for realism, but require expensive and time-consuming procedures. IR scene simulation methods have emerged as a more economical and efficient alternative for the generation of IR databases. A novel approach to IR target simulation is presented in this paper. Model vehicles at 1:24 scale are used for the simulation of real targets. The temperature profile of the model vehicles is controlled using resistive circuits which are embedded inside the models. The IR target is recorded using an Inframetrics dual channel IR camera system. Using computer processing we place the recorded IR target in a prerecorded background. The advantages of this approach are: (1) the range and 3D target aspect can be controlled by the relative position between the camera and model vehicle; (2) the temperature profile can be controlled by adjusting the power delivered to the resistive circuit; (3) the IR sensor effects are directly incorporated in the recording process, because the real sensor is used; (4) the recorded target can embedded in various types of backgrounds recorded under different weather conditions, times of day etc. The effectiveness of this approach is demonstrated by generating an IR database of three vehicles which is used to train a back propagation neural network. The neural network is capable of classifying vehicle type, vehicle aspect, and relative temperature with a high degree of accuracy.

MicroRNAs: Processing, Maturation, Target Recognition and Regulatory Functions

PubMed Central

Shukla, Girish C.; Singh, Jagjit; Barik, Sailen

2012-01-01

The remarkable discovery of small noncoding microRNAs (miRNAs) and their role in posttranscriptional gene regulation have revealed another fine-tuning step in the expression of genetic information. A large number of cellular pathways, which act in organismal development and are important in health and disease, appear to be modulated by miRNAs. At the molecular level, miRNAs restrain the production of proteins by affecting the stability of their target mRNA and/or by down-regulating their translation. This review attempts to offer a snapshot of aspects of miRNA coding, processing, target recognition and function in animals. Our goal here is to provide the readers with a thought-provoking and mechanistic introduction to the miRNA world rather than with a detailed encyclopedia. PMID:22468167

Exploring the sequence-structure protein landscape in the glycosyltransferase family

PubMed Central

Zhang, Ziding; Kochhar, Sunil; Grigorov, Martin

2003-01-01

To understand the molecular basis of glycosyltransferases’ (GTFs) catalytic mechanism, extensive structural information is required. Here, fold recognition methods were employed to assign 3D protein shapes (folds) to the currently known GTF sequences, available in public databases such as GenBank and Swissprot. First, GTF sequences were retrieved and classified into clusters, based on sequence similarity only. Intracluster sequence similarity was chosen sufficiently high to ensure that the same fold is found within a given cluster. Then, a representative sequence from each cluster was selected to compose a subset of GTF sequences. The members of this reduced set were processed by three different fold recognition methods: 3D-PSSM, FUGUE, and GeneFold. Finally, the results from different fold recognition methods were analyzed and compared to sequence-similarity search methods (i.e., BLAST and PSI-BLAST). It was established that the folds of about 70% of all currently known GTF sequences can be confidently assigned by fold recognition methods, a value which is higher than the fold identification rate based on sequence comparison alone (48% for BLAST and 64% for PSI-BLAST). The identified folds were submitted to 3D clustering, and we found that most of the GTF sequences adopt the typical GTF A or GTF B folds. Our results indicate a lack of evidence that new GTF folds (i.e., folds other than GTF A and B) exist. Based on cases where fold identification was not possible, we suggest several sequences as the most promising targets for a structural genomics initiative focused on the GTF protein family. PMID:14500887

Dubinett - Targeted Sequencing 2012 — EDRN Public Portal

Cancer.gov

we propose to use targeted massively parallel DNA sequencing to identify somatic alterations within mutational hotspots in matched sets of primary lung tumors, premalignant lesions, and adjacent,histologically normal lung tissue.

RISC RNA sequencing for context-specific identification of in vivo miR targets

PubMed Central

Matkovich, Scot J; Van Booven, Derek J; Eschenbacher, William H; Dorn, Gerald W

2010-01-01

Rationale MicroRNAs (miRs) are expanding our understanding of cardiac disease and have the potential to transform cardiovascular therapeutics. One miR can target hundreds of individual mRNAs, but existing methodologies are not sufficient to accurately and comprehensively identify these mRNA targets in vivo. Objective To develop methods permitting identification of in vivo miR targets in an unbiased manner, using massively parallel sequencing of mouse cardiac transcriptomes in combination with sequencing of mRNA associated with mouse cardiac RNA-induced silencing complexes (RISCs). Methods and Results We optimized techniques for expression profiling small amounts of RNA without introducing amplification bias, and applied this to anti-Argonaute 2 immunoprecipitated RISCs (RISC-Seq) from mouse hearts. By comparing RNA-sequencing results of cardiac RISC and transcriptome from the same individual hearts, we defined 1,645 mRNAs consistently targeted to mouse cardiac RISCs. We employed this approach in hearts overexpressing miRs from Myh6 promoter-driven precursors (programmed RISC-Seq) to identify 209 in vivo targets of miR-133a and 81 in vivo targets of miR-499. Consistent with the fact that miR-133a and miR-499 have widely differing ‘seed’ sequences and belong to different miR families, only 6 targets were common to miR-133a- and miR-499-programmed hearts. Conclusions RISC-sequencing is a highly sensitive method for general RISC profiling and individual miR target identification in biological context, and is applicable to any tissue and any disease state. Summary MicroRNAs (miRs) are key regulators of mRNA translation in health and disease. While bioinformatic predictions suggest that a single miR may target hundreds of mRNAs, the number of experimentally verified targets of miRs is low. To enable comprehensive, unbiased examination of miR targets, we have performed deep RNA sequencing of cardiac transcriptomes in parallel with cardiac RNA-induced silencing complex

Comparative study of methods for recognition of an unknown person's action from a video sequence

NASA Astrophysics Data System (ADS)

Hori, Takayuki; Ohya, Jun; Kurumisawa, Jun

2009-02-01

This paper proposes a Tensor Decomposition Based method that can recognize an unknown person's action from a video sequence, where the unknown person is not included in the database (tensor) used for the recognition. The tensor consists of persons, actions and time-series image features. For the observed unknown person's action, one of the actions stored in the tensor is assumed. Using the motion signature obtained from the assumption, the unknown person's actions are synthesized. The actions of one of the persons in the tensor are replaced by the synthesized actions. Then, the core tensor for the replaced tensor is computed. This process is repeated for the actions and persons. For each iteration, the difference between the replaced and original core tensors is computed. The assumption that gives the minimal difference is the action recognition result. For the time-series image features to be stored in the tensor and to be extracted from the observed video sequence, the human body silhouette's contour shape based feature is used. To show the validity of our proposed method, our proposed method is experimentally compared with Nearest Neighbor rule and Principal Component analysis based method. Experiments using 33 persons' seven kinds of action show that our proposed method achieves better recognition accuracies for the seven actions than the other methods.

Non-Cooperative Target Recognition by Means of Singular Value Decomposition Applied to Radar High Resolution Range Profiles †

PubMed Central

López-Rodríguez, Patricia; Escot-Bocanegra, David; Fernández-Recio, Raúl; Bravo, Ignacio

2015-01-01

Radar high resolution range profiles are widely used among the target recognition community for the detection and identification of flying targets. In this paper, singular value decomposition is applied to extract the relevant information and to model each aircraft as a subspace. The identification algorithm is based on angle between subspaces and takes place in a transformed domain. In order to have a wide database of radar signatures and evaluate the performance, simulated range profiles are used as the recognition database while the test samples comprise data of actual range profiles collected in a measurement campaign. Thanks to the modeling of aircraft as subspaces only the valuable information of each target is used in the recognition process. Thus, one of the main advantages of using singular value decomposition, is that it helps to overcome the notable dissimilarities found in the shape and signal-to-noise ratio between actual and simulated profiles due to their difference in nature. Despite these differences, the recognition rates obtained with the algorithm are quite promising. PMID:25551484

Feature extraction and selection strategies for automated target recognition

NASA Astrophysics Data System (ADS)

Greene, W. Nicholas; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2010-04-01

Several feature extraction and selection methods for an existing automatic target recognition (ATR) system using JPLs Grayscale Optical Correlator (GOC) and Optimal Trade-Off Maximum Average Correlation Height (OT-MACH) filter were tested using MATLAB. The ATR system is composed of three stages: a cursory regionof- interest (ROI) search using the GOC and OT-MACH filter, a feature extraction and selection stage, and a final classification stage. Feature extraction and selection concerns transforming potential target data into more useful forms as well as selecting important subsets of that data which may aide in detection and classification. The strategies tested were built around two popular extraction methods: Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Performance was measured based on the classification accuracy and free-response receiver operating characteristic (FROC) output of a support vector machine(SVM) and a neural net (NN) classifier.

GWASeq: targeted re-sequencing follow up to GWAS.

PubMed

Salomon, Matthew P; Li, Wai Lok Sibon; Edlund, Christopher K; Morrison, John; Fortini, Barbara K; Win, Aung Ko; Conti, David V; Thomas, Duncan C; Duggan, David; Buchanan, Daniel D; Jenkins, Mark A; Hopper, John L; Gallinger, Steven; Le Marchand, Loïc; Newcomb, Polly A; Casey, Graham; Marjoram, Paul

2016-03-03

For the last decade the conceptual framework of the Genome-Wide Association Study (GWAS) has dominated the investigation of human disease and other complex traits. While GWAS have been successful in identifying a large number of variants associated with various phenotypes, the overall amount of heritability explained by these variants remains small. This raises the question of how best to follow up on a GWAS, localize causal variants accounting for GWAS hits, and as a consequence explain more of the so-called "missing" heritability. Advances in high throughput sequencing technologies now allow for the efficient and cost-effective collection of vast amounts of fine-scale genomic data to complement GWAS. We investigate these issues using a colon cancer dataset. After QC, our data consisted of 1993 cases, 899 controls. Using marginal tests of associations, we identify 10 variants distributed among six targeted regions that are significantly associated with colorectal cancer, with eight of the variants being novel to this study. Additionally, we perform so-called 'SNP-set' tests of association and identify two sets of variants that implicate both common and rare variants in the etiology of colorectal cancer. Here we present a large-scale targeted re-sequencing resource focusing on genomic regions implicated in colorectal cancer susceptibility previously identified in several GWAS, which aims to 1) provide fine-scale targeted sequencing data for fine-mapping and 2) provide data resources to address methodological questions regarding the design of sequencing-based follow-up studies to GWAS. Additionally, we show that this strategy successfully identifies novel variants associated with colorectal cancer susceptibility and can implicate both common and rare variants.

A fast recognition method of warhead target in boost phase using kinematic features

NASA Astrophysics Data System (ADS)

Chen, Jian; Xu, Shiyou; Tian, Biao; Wu, Jianhua; Chen, Zengping

2015-12-01

The radar targets number increases from one to more when the ballistic missile is in the process of separating the lower stage rocket or casting covers or other components. It is vital to identify the warhead target quickly among these multiple targets for radar tracking. A fast recognition method of the warhead target is proposed to solve this problem by using kinematic features, utilizing fuzzy comprehensive method and information fusion method. In order to weaken the influence of radar measurement noise, an extended Kalman filter with constant jerk model (CJEKF) is applied to obtain more accurate target's motion information. The simulation shows the validity of the algorithm and the effects of the radar measurement precision upon the algorithm's performance.

The research of edge extraction and target recognition based on inherent feature of objects

NASA Astrophysics Data System (ADS)

Xie, Yu-chan; Lin, Yu-chi; Huang, Yin-guo

2008-03-01

Current research on computer vision often needs specific techniques for particular problems. Little use has been made of high-level aspects of computer vision, such as three-dimensional (3D) object recognition, that are appropriate for large classes of problems and situations. In particular, high-level vision often focuses mainly on the extraction of symbolic descriptions, and pays little attention to the speed of processing. In order to extract and recognize target intelligently and rapidly, in this paper we developed a new 3D target recognition method based on inherent feature of objects in which cuboid was taken as model. On the basis of analysis cuboid nature contour and greyhound distributing characteristics, overall fuzzy evaluating technique was utilized to recognize and segment the target. Then Hough transform was used to extract and match model's main edges, we reconstruct aim edges by stereo technology in the end. There are three major contributions in this paper. Firstly, the corresponding relations between the parameters of cuboid model's straight edges lines in an image field and in the transform field were summed up. By those, the aimless computations and searches in Hough transform processing can be reduced greatly and the efficiency is improved. Secondly, as the priori knowledge about cuboids contour's geometry character known already, the intersections of the component extracted edges are taken, and assess the geometry of candidate edges matches based on the intersections, rather than the extracted edges. Therefore the outlines are enhanced and the noise is depressed. Finally, a 3-D target recognition method is proposed. Compared with other recognition methods, this new method has a quick response time and can be achieved with high-level computer vision. The method present here can be used widely in vision-guide techniques to strengthen its intelligence and generalization, which can also play an important role in object tracking, port AGV, robots

Programmable RNA Cleavage and Recognition by a Natural CRISPR-Cas9 System from Neisseria meningitidis.

PubMed

Rousseau, Beth A; Hou, Zhonggang; Gramelspacher, Max J; Zhang, Yan

2018-03-01

The microbial CRISPR systems enable adaptive defense against mobile elements and also provide formidable tools for genome engineering. The Cas9 proteins are type II CRISPR-associated, RNA-guided DNA endonucleases that identify double-stranded DNA targets by sequence complementarity and protospacer adjacent motif (PAM) recognition. Here we report that the type II-C CRISPR-Cas9 from Neisseria meningitidis (Nme) is capable of programmable, RNA-guided, site-specific cleavage and recognition of single-stranded RNA targets and that this ribonuclease activity is independent of the PAM sequence. We define the mechanistic feature and specificity constraint for RNA cleavage by NmeCas9 and also show that nuclease null dNmeCas9 binds to RNA target complementary to CRISPR RNA. Finally, we demonstrate that NmeCas9-catalyzed RNA cleavage can be blocked by three families of type II-C anti-CRISPR proteins. These results fundamentally expand the targeting capacities of CRISPR-Cas9 and highlight the potential utility of NmeCas9 as a single platform to target both RNA and DNA. Copyright © 2018 Elsevier Inc. All rights reserved.

Targeted Analysis of Whole Genome Sequence Data to Diagnose Genetic Cardiomyopathy

DOE PAGES

Golbus, Jessica R.; Puckelwartz, Megan J.; Dellefave-Castillo, Lisa; ...

2014-09-01

Background—Cardiomyopathy is highly heritable but genetically diverse. At present, genetic testing for cardiomyopathy uses targeted sequencing to simultaneously assess the coding regions of more than 50 genes. New genes are routinely added to panels to improve the diagnostic yield. With the anticipated $1000 genome, it is expected that genetic testing will shift towards comprehensive genome sequencing accompanied by targeted gene analysis. Therefore, we assessed the reliability of whole genome sequencing and targeted analysis to identify cardiomyopathy variants in 11 subjects with cardiomyopathy. Methods and Results—Whole genome sequencing with an average of 37× coverage was combined with targeted analysis focused onmore » 204 genes linked to cardiomyopathy. Genetic variants were scored using multiple prediction algorithms combined with frequency data from public databases. This pipeline yielded 1-14 potentially pathogenic variants per individual. Variants were further analyzed using clinical criteria and/or segregation analysis. Three of three previously identified primary mutations were detected by this analysis. In six subjects for whom the primary mutation was previously unknown, we identified mutations that segregated with disease, had clinical correlates, and/or had additional pathological correlation to provide evidence for causality. For two subjects with previously known primary mutations, we identified additional variants that may act as modifiers of disease severity. In total, we identified the likely pathological mutation in 9 of 11 (82%) subjects. We conclude that these pilot data demonstrate that ~30-40× coverage whole genome sequencing combined with targeted analysis is feasible and sensitive to identify rare variants in cardiomyopathy-associated genes.« less

Using Metadynamics to Understand the Mechanism of Calmodulin/Target Recognition at Atomic Detail

PubMed Central

Fiorin, G.; Pastore, A.; Carloni, P.; Parrinello, M.

2006-01-01

The ability of calcium-bound calmodulin (CaM) to recognize most of its target peptides is caused by its binding to two hydrophobic residues (‘anchors’). In most of the CaM complexes, the anchors pack against the hydrophobic pockets of the CaM domains and are surrounded by fully conserved Met side chains. Here, by using metadynamics simulations, we investigate quantitatively the energetics of the final step of this process using the M13 peptide, which has a high affinity and spans the sequence of the skeletal myosin light chain kinase, an important natural CaM target. We established the accuracy of our calculations by a comparison between calculated and NMR-derived structural and dynamical properties. Our calculations provide novel insights into the mechanism of protein/peptide recognition: we show that the process is associated with a free energy gain similar to that experimentally measured for the CaM complex with the homologous smooth muscle MLCK peptide (Ehrhardt et al., 1995, Biochemistry 34, 2731). We suggest that binding is dominated by the entropic effect, in agreement with previous proposals. Furthermore, we explain the role of conserved methionines by showing that the large flexibility of these side chains is a key feature of the binding mechanism. Finally, we provide a rationale for the experimental observation that in all CaM complexes the C-terminal domain seems to be hierarchically more important in establishing the interaction. PMID:16877506

Automated target recognition using passive radar and coordinated flight models

NASA Astrophysics Data System (ADS)

Ehrman, Lisa M.; Lanterman, Aaron D.

2003-09-01

Rather than emitting pulses, passive radar systems rely on illuminators of opportunity, such as TV and FM radio, to illuminate potential targets. These systems are particularly attractive since they allow receivers to operate without emitting energy, rendering them covert. Many existing passive radar systems estimate the locations and velocities of targets. This paper focuses on adding an automatic target recognition (ATR) component to such systems. Our approach to ATR compares the Radar Cross Section (RCS) of targets detected by a passive radar system to the simulated RCS of known targets. To make the comparison as accurate as possible, the received signal model accounts for aircraft position and orientation, propagation losses, and antenna gain patterns. The estimated positions become inputs for an algorithm that uses a coordinated flight model to compute probable aircraft orientation angles. The Fast Illinois Solver Code (FISC) simulates the RCS of several potential target classes as they execute the estimated maneuvers. The RCS is then scaled by the Advanced Refractive Effects Prediction System (AREPS) code to account for propagation losses that occur as functions of altitude and range. The Numerical Electromagnetic Code (NEC2) computes the antenna gain pattern, so that the RCS can be further scaled. The Rician model compares the RCS of the illuminated aircraft with those of the potential targets. This comparison results in target identification.

Recognition of Double Stranded RNA by Guanidine-Modified Peptide Nucleic Acids (GPNA)

PubMed Central

Gupta, Pankaj; Muse, Oluwatoyosi; Rozners, Eriks

2011-01-01

Double helical RNA has become an attractive target for molecular recognition because many non-coding RNAs play important roles in control of gene expression. Recently, we discovered that short peptide nucleic acids (PNA) bind strongly and sequence selectively to a homopurine tract of double helical RNA via triple helix formation. Herein we tested if the molecular recognition of RNA can be enhanced by α-guanidine modification of PNA. Our study was motivated by the discovery of Ly and co-workers that the guanidine modification greatly enhances the cellular delivery of PNA. Isothermal titration calorimetry showed that the guanidine-modified PNA (GPNA) had reduced affinity and sequence selectivity for triple helical recognition of RNA. The data suggested that in contrast to unmodified PNA, which formed a 1:1 PNA-RNA triple helix, GPNA preferred a 2:1 GPNA-RNA triplex-invasion complex. Nevertheless, promising results were obtained for recognition of biologically relevant double helical RNA. Consistent with enhanced strand invasion ability, GPNA derived from D-arginine recognized the transactivation response element (TAR) of HIV-1 with high affinity and sequence selectivity, presumably via Watson-Crick duplex formation. On the other hand, strong and sequence selective triple helices were formed by unmodified and nucelobase-modified PNAs and the purine rich strand of bacterial A-site. These results suggest that appropriate chemical modifications of PNA may enhance molecular recognition of complex non-coding RNAs. PMID:22146072

Multi-Stage System for Automatic Target Recognition

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Lu, Thomas T.; Ye, David; Edens, Weston; Johnson, Oliver

2010-01-01

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an

Target recognition of ladar range images using slice image: comparison of four improved algorithms

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Cao, Jingya; Wang, Liang; Zhai, Yu; Cheng, Yang

2017-07-01

Compared with traditional 3-D shape data, ladar range images possess properties of strong noise, shape degeneracy, and sparsity, which make feature extraction and representation difficult. The slice image is an effective feature descriptor to resolve this problem. We propose four improved algorithms on target recognition of ladar range images using slice image. In order to improve resolution invariance of the slice image, mean value detection instead of maximum value detection is applied in these four improved algorithms. In order to improve rotation invariance of the slice image, three new improved feature descriptors-which are feature slice image, slice-Zernike moments, and slice-Fourier moments-are applied to the last three improved algorithms, respectively. Backpropagation neural networks are used as feature classifiers in the last two improved algorithms. The performance of these four improved recognition systems is analyzed comprehensively in the aspects of the three invariances, recognition rate, and execution time. The final experiment results show that the improvements for these four algorithms reach the desired effect, the three invariances of feature descriptors are not directly related to the final recognition performance of recognition systems, and these four improved recognition systems have different performances under different conditions.

Bio-recognitive photonics of a DNA-guided organic semiconductor.

PubMed

Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

2016-01-04

Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA-DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an 'inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA-DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition.

Bio-recognitive photonics of a DNA-guided organic semiconductor

NASA Astrophysics Data System (ADS)

Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

2016-01-01

Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA-DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an `inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA-DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition.

An algorithm for automatic target recognition using passive radar and an EKF for estimating aircraft orientation

NASA Astrophysics Data System (ADS)

Ehrman, Lisa M.

2005-07-01

Rather than emitting pulses, passive radar systems rely on "illuminators of opportunity," such as TV and FM radio, to illuminate potential targets. These systems are attractive since they allow receivers to operate without emitting energy, rendering them covert. Until recently, most of the research regarding passive radar has focused on detecting and tracking targets. This dissertation focuses on extending the capabilities of passive radar systems to include automatic target recognition. The target recognition algorithm described in this dissertation uses the radar cross section (RCS) of potential targets, collected over a short period of time, as the key information for target recognition. To make the simulated RCS as accurate as possible, the received signal model accounts for aircraft position and orientation, propagation losses, and antenna gain patterns. An extended Kalman filter (EKF) estimates the target's orientation (and uncertainty in the estimate) from velocity measurements obtained from the passive radar tracker. Coupling the aircraft orientation and state with the known antenna locations permits computation of the incident and observed azimuth and elevation angles. The Fast Illinois Solver Code (FISC) simulates the RCS of potential target classes as a function of these angles. Thus, the approximated incident and observed angles allow the appropriate RCS to be extracted from a database of FISC results. Using this process, the RCS of each aircraft in the target class is simulated as though each is executing the same maneuver as the target detected by the system. Two additional scaling processes are required to transform the RCS into a power profile (magnitude only) simulating the signal in the receiver. First, the RCS is scaled by the Advanced Refractive Effects Prediction System (AREPS) code to account for propagation losses that occur as functions of altitude and range. Then, the Numerical Electromagnetic Code (NEC2) computes the antenna gain pattern

[Neuronal activity of monkey dorso-lateral premotor cortex during tasks of figure recognition guided motor sequence vs memorized spatial motor sequence].

PubMed

Chen, Y C; Huang, F D; Chen, N H; Shou, J Y; Wu, L

1998-04-01

In the last 2-3 decades the role of the premotor cortex (PM) of monkey in memorized spatial sequential (MSS) movements has been amply investigated. However, it is as yet not known whether PM participates in the movement sequence behaviour guided by recognition of visual figures (i.e. the figure-recognition sequence, FRS). In the present work three monkeys were trained to perform both FRS and MSS tasks. Postmortem examination showed that 202 cells were in the dorso-lateral premotor cortex. Among 111 cells recorded during the two tasks, more than 50% changed their activity during the cue periods in either task. During the response period, the ratios of cells with changes of firing rate in both FRS and MSS were high and roughly equal to each other, while during the image period, the proportion in the FRS (83.7%) was significantly higher than that in the MSS (66.7%). Comparison of neuronal activities during same motor sequence of two different tasks showed that during the image periods PM neuronal activities were more closely related to the FRS task, while during the cue periods no difference could be found. Analysis of cell responses showed that the neurons with longer latency were much more in MSS than in FRS in either cue or image period. The present results indicate that the premotor cortex participates in FRS motor sequence as well as in MSS and suggest that the dorso-lateral PM represents another subarea in function shared by both FRS and MSS tasks. However, in view of the differences of PM neuronal responses in cue or image periods of FRS and MSS tasks, it seems likely that neural networks involved in FRS and MSS tasks are different.

Feature Extraction and Selection Strategies for Automated Target Recognition

NASA Technical Reports Server (NTRS)

Greene, W. Nicholas; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2010-01-01

Several feature extraction and selection methods for an existing automatic target recognition (ATR) system using JPLs Grayscale Optical Correlator (GOC) and Optimal Trade-Off Maximum Average Correlation Height (OT-MACH) filter were tested using MATLAB. The ATR system is composed of three stages: a cursory region of-interest (ROI) search using the GOC and OT-MACH filter, a feature extraction and selection stage, and a final classification stage. Feature extraction and selection concerns transforming potential target data into more useful forms as well as selecting important subsets of that data which may aide in detection and classification. The strategies tested were built around two popular extraction methods: Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Performance was measured based on the classification accuracy and free-response receiver operating characteristic (FROC) output of a support vector machine(SVM) and a neural net (NN) classifier.

Influence of motion on face recognition.

PubMed

Bonfiglio, Natale S; Manfredi, Valentina; Pessa, Eliano

2012-02-01

The influence of motion information and temporal associations on recognition of non-familiar faces was investigated using two groups which performed a face recognition task. One group was presented with regular temporal sequences of face views designed to produce the impression of motion of the face rotating in depth, the other group with random sequences of the same views. In one condition, participants viewed the sequences of the views in rapid succession with a negligible interstimulus interval (ISI). This condition was characterized by three different presentation times. In another condition, participants were presented a sequence with a 1-sec. ISI among the views. That regular sequences of views with a negligible ISI and a shorter presentation time were hypothesized to give rise to better recognition, related to a stronger impression of face rotation. Analysis of data from 45 participants showed a shorter presentation time was associated with significantly better accuracy on the recognition task; however, differences between performances associated with regular and random sequences were not significant.

A novel paired domain DNA recognition motif can mediate Pax2 repression of gene transcription.

PubMed

Håvik, B; Ragnhildstveit, E; Lorens, J B; Saelemyr, K; Fauske, O; Knudsen, L K; Fjose, A

1999-12-20

The paired domain (PD) is an evolutionarily conserved DNA-binding domain encoded by the Pax gene family of developmental regulators. The Pax proteins are transcription factors and are involved in a variety of processes such as brain development, patterning of the central nervous system (CNS), and B-cell development. In this report we demonstrate that the zebrafish Pax2 PD can interact with a novel type of DNA sequences in vitro, the triple-A motif, consisting of a heptameric nucleotide sequence G/CAAACA/TC with an invariant core of three adjacent adenosines. This recognition sequence was found to be conserved in known natural Pax5 repressor elements involved in controlling the expression of the p53 and J-chain genes. By identifying similar high affinity binding sites in potential target genes of the Pax2 protein, including the pax2 gene itself, we obtained further evidence that the triple-A sites are biologically significant. The putative natural target sites also provide a basis for defining an extended consensus recognition sequence. In addition, we observed in transformation assays a direct correlation between Pax2 repressor activity and the presence of triple-A sites. The results suggest that a transcriptional regulatory function of Pax proteins can be modulated by PD binding to different categories of target sequences. Copyright 1999 Academic Press.

MPN estimation of qPCR target sequence recoveries from whole cell calibrator samples.

PubMed

Sivaganesan, Mano; Siefring, Shawn; Varma, Manju; Haugland, Richard A

2011-12-01

DNA extracts from enumerated target organism cells (calibrator samples) have been used for estimating Enterococcus cell equivalent densities in surface waters by a comparative cycle threshold (Ct) qPCR analysis method. To compare surface water Enterococcus density estimates from different studies by this approach, either a consistent source of calibrator cells must be used or the estimates must account for any differences in target sequence recoveries from different sources of calibrator cells. In this report we describe two methods for estimating target sequence recoveries from whole cell calibrator samples based on qPCR analyses of their serially diluted DNA extracts and most probable number (MPN) calculation. The first method employed a traditional MPN calculation approach. The second method employed a Bayesian hierarchical statistical modeling approach and a Monte Carlo Markov Chain (MCMC) simulation method to account for the uncertainty in these estimates associated with different individual samples of the cell preparations, different dilutions of the DNA extracts and different qPCR analytical runs. The two methods were applied to estimate mean target sequence recoveries per cell from two different lots of a commercially available source of enumerated Enterococcus cell preparations. The mean target sequence recovery estimates (and standard errors) per cell from Lot A and B cell preparations by the Bayesian method were 22.73 (3.4) and 11.76 (2.4), respectively, when the data were adjusted for potential false positive results. Means were similar for the traditional MPN approach which cannot comparably assess uncertainty in the estimates. Cell numbers and estimates of recoverable target sequences in calibrator samples prepared from the two cell sources were also used to estimate cell equivalent and target sequence quantities recovered from surface water samples in a comparative Ct method. Our results illustrate the utility of the Bayesian method in accounting for

RISC RNA sequencing for context-specific identification of in vivo microRNA targets.

PubMed

Matkovich, Scot J; Van Booven, Derek J; Eschenbacher, William H; Dorn, Gerald W

2011-01-07

MicroRNAs (miRs) are expanding our understanding of cardiac disease and have the potential to transform cardiovascular therapeutics. One miR can target hundreds of individual mRNAs, but existing methodologies are not sufficient to accurately and comprehensively identify these mRNA targets in vivo. To develop methods permitting identification of in vivo miR targets in an unbiased manner, using massively parallel sequencing of mouse cardiac transcriptomes in combination with sequencing of mRNA associated with mouse cardiac RNA-induced silencing complexes (RISCs). We optimized techniques for expression profiling small amounts of RNA without introducing amplification bias and applied this to anti-Argonaute 2 immunoprecipitated RISCs (RISC-Seq) from mouse hearts. By comparing RNA-sequencing results of cardiac RISC and transcriptome from the same individual hearts, we defined 1645 mRNAs consistently targeted to mouse cardiac RISCs. We used this approach in hearts overexpressing miRs from Myh6 promoter-driven precursors (programmed RISC-Seq) to identify 209 in vivo targets of miR-133a and 81 in vivo targets of miR-499. Consistent with the fact that miR-133a and miR-499 have widely differing "seed" sequences and belong to different miR families, only 6 targets were common to miR-133a- and miR-499-programmed hearts. RISC-sequencing is a highly sensitive method for general RISC profiling and individual miR target identification in biological context and is applicable to any tissue and any disease state.

Bio-recognitive photonics of a DNA-guided organic semiconductor

PubMed Central

Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

2016-01-01

Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA–DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an ‘inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA–DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition. PMID:26725969

The study of infrared target recognition at sea background based on visual attention computational model

NASA Astrophysics Data System (ADS)

Wang, Deng-wei; Zhang, Tian-xu; Shi, Wen-jun; Wei, Long-sheng; Wang, Xiao-ping; Ao, Guo-qing

2009-07-01

Infrared images at sea background are notorious for the low signal-to-noise ratio, therefore, the target recognition of infrared image through traditional methods is very difficult. In this paper, we present a novel target recognition method based on the integration of visual attention computational model and conventional approach (selective filtering and segmentation). The two distinct techniques for image processing are combined in a manner to utilize the strengths of both. The visual attention algorithm searches the salient regions automatically, and represented them by a set of winner points, at the same time, demonstrated the salient regions in terms of circles centered at these winner points. This provides a priori knowledge for the filtering and segmentation process. Based on the winner point, we construct a rectangular region to facilitate the filtering and segmentation, then the labeling operation will be added selectively by requirement. Making use of the labeled information, from the final segmentation result we obtain the positional information of the interested region, label the centroid on the corresponding original image, and finish the localization for the target. The cost time does not depend on the size of the image but the salient regions, therefore the consumed time is greatly reduced. The method is used in the recognition of several kinds of real infrared images, and the experimental results reveal the effectiveness of the algorithm presented in this paper.

RNase H-assisted RNA-primed rolling circle amplification for targeted RNA sequence detection.

PubMed

Takahashi, Hirokazu; Ohkawachi, Masahiko; Horio, Kyohei; Kobori, Toshiro; Aki, Tsunehiro; Matsumura, Yukihiko; Nakashimada, Yutaka; Okamura, Yoshiko

2018-05-17

RNA-primed rolling circle amplification (RPRCA) is a useful laboratory method for RNA detection; however, the detection of RNA is limited by the lack of information on 3'-terminal sequences. We uncovered that conventional RPRCA using pre-circularized probes could potentially detect the internal sequence of target RNA molecules in combination with RNase H. However, the specificity for mRNA detection was low, presumably due to non-specific hybridization of non-target RNA with the circular probe. To overcome this technical problem, we developed a method for detecting a sequence of interest in target RNA molecules via RNase H-assisted RPRCA using padlocked probes. When padlock probes are hybridized to the target RNA molecule, they are converted to the circular form by SplintR ligase. Subsequently, RNase H creates nick sites only in the hybridized RNA sequence, and single-stranded DNA is finally synthesized from the nick site by phi29 DNA polymerase. This method could specifically detect at least 10 fmol of the target RNA molecule without reverse transcription. Moreover, this method detected GFP mRNA present in 10 ng of total RNA isolated from Escherichia coli without background DNA amplification. Therefore, this method can potentially detect almost all types of RNA molecules without reverse transcription and reveal full-length sequence information.

Autonomous space target recognition and tracking approach using star sensors based on a Kalman filter.

PubMed

Ye, Tao; Zhou, Fuqiang

2015-04-10

When imaged by detectors, space targets (including satellites and debris) and background stars have similar point-spread functions, and both objects appear to change as detectors track targets. Therefore, traditional tracking methods cannot separate targets from stars and cannot directly recognize targets in 2D images. Consequently, we propose an autonomous space target recognition and tracking approach using a star sensor technique and a Kalman filter (KF). A two-step method for subpixel-scale detection of star objects (including stars and targets) is developed, and the combination of the star sensor technique and a KF is used to track targets. The experimental results show that the proposed method is adequate for autonomously recognizing and tracking space targets.

Wavelet-Based Signal and Image Processing for Target Recognition

NASA Astrophysics Data System (ADS)

Sherlock, Barry G.

2002-11-01

The PI visited NSWC Dahlgren, VA, for six weeks in May-June 2002 and collaborated with scientists in the G33 TEAMS facility, and with Marilyn Rudzinsky of T44 Technology and Photonic Systems Branch. During this visit the PI also presented six educational seminars to NSWC scientists on various aspects of signal processing. Several items from the grant proposal were completed, including (1) wavelet-based algorithms for interpolation of 1-d signals and 2-d images; (2) Discrete Wavelet Transform domain based algorithms for filtering of image data; (3) wavelet-based smoothing of image sequence data originally obtained for the CRITTIR (Clutter Rejection Involving Temporal Techniques in the Infra-Red) project. The PI visited the University of Stellenbosch, South Africa to collaborate with colleagues Prof. B.M. Herbst and Prof. J. du Preez on the use of wavelet image processing in conjunction with pattern recognition techniques. The University of Stellenbosch has offered the PI partial funding to support a sabbatical visit in Fall 2003, the primary purpose of which is to enable the PI to develop and enhance his expertise in Pattern Recognition. During the first year, the grant supported publication of 3 referred papers, presentation of 9 seminars and an intensive two-day course on wavelet theory. The grant supported the work of two students who functioned as research assistants.

Bioinformatics by Example: From Sequence to Target

NASA Astrophysics Data System (ADS)

Kossida, Sophia; Tahri, Nadia; Daizadeh, Iraj

2002-12-01

With the completion of the human genome, and the imminent completion of other large-scale sequencing and structure-determination projects, computer-assisted bioscience is aimed to become the new paradigm for conducting basic and applied research. The presence of these additional bioinformatics tools stirs great anxiety for experimental researchers (as well as for pedagogues), since they are now faced with a wider and deeper knowledge of differing disciplines (biology, chemistry, physics, mathematics, and computer science). This review targets those individuals who are interested in using computational methods in their teaching or research. By analyzing a real-life, pharmaceutical, multicomponent, target-based example the reader will experience this fascinating new discipline.

Structural basis of DNA sequence recognition by the response regulator PhoP in Mycobacterium tuberculosis.

PubMed

He, Xiaoyuan; Wang, Liqin; Wang, Shuishu

2016-04-15

The transcriptional regulator PhoP is an essential virulence factor in Mycobacterium tuberculosis, and it presents a target for the development of new anti-tuberculosis drugs and attenuated tuberculosis vaccine strains. PhoP binds to DNA as a highly cooperative dimer by recognizing direct repeats of 7-bp motifs with a 4-bp spacer. To elucidate the PhoP-DNA binding mechanism, we determined the crystal structure of the PhoP-DNA complex. The structure revealed a tandem PhoP dimer that bound to the direct repeat. The surprising tandem arrangement of the receiver domains allowed the four domains of the PhoP dimer to form a compact structure, accounting for the strict requirement of a 4-bp spacer and the highly cooperative binding of the dimer. The PhoP-DNA interactions exclusively involved the effector domain. The sequence-recognition helix made contact with the bases of the 7-bp motif in the major groove, and the wing interacted with the adjacent minor groove. The structure provides a starting point for the elucidation of the mechanism by which PhoP regulates the virulence of M. tuberculosis and guides the design of screening platforms for PhoP inhibitors.

Targeted next-generation sequencing in monogenic dyslipidemias.

PubMed

Hegele, Robert A; Ban, Matthew R; Cao, Henian; McIntyre, Adam D; Robinson, John F; Wang, Jian

2015-04-01

To evaluate the potential clinical translation of high-throughput next-generation sequencing (NGS) methods in diagnosis and management of dyslipidemia. Recent NGS experiments indicate that most causative genes for monogenic dyslipidemias are already known. Thus, monogenic dyslipidemias can now be diagnosed using targeted NGS. Targeting of dyslipidemia genes can be achieved by either: designing custom reagents for a dyslipidemia-specific NGS panel; or performing genome-wide NGS and focusing on genes of interest. Advantages of the former approach are lower cost and limited potential to detect incidental pathogenic variants unrelated to dyslipidemia. However, the latter approach is more flexible because masking criteria can be altered as knowledge advances, with no need for re-design of reagents or follow-up sequencing runs. Also, the cost of genome-wide analysis is decreasing and ethical concerns can likely be mitigated. DNA-based diagnosis is already part of the clinical diagnostic algorithms for familial hypercholesterolemia. Furthermore, DNA-based diagnosis is supplanting traditional biochemical methods to diagnose chylomicronemia caused by deficiency of lipoprotein lipase or its co-factors. The increasing availability and decreasing cost of clinical NGS for dyslipidemia means that its potential benefits can now be evaluated on a larger scale.

Bipartite recognition of target RNAs activates DNA cleavage by the Type III-B CRISPR–Cas system

PubMed Central

Elmore, Joshua R.; Sheppard, Nolan F.; Ramia, Nancy; Deighan, Trace; Li, Hong; Terns, Rebecca M.; Terns, Michael P.

2016-01-01

CRISPR–Cas systems eliminate nucleic acid invaders in bacteria and archaea. The effector complex of the Type III-B Cmr system cleaves invader RNAs recognized by the CRISPR RNA (crRNA ) of the complex. Here we show that invader RNAs also activate the Cmr complex to cleave DNA. As has been observed for other Type III systems, Cmr eliminates plasmid invaders in Pyrococcus furiosus by a mechanism that depends on transcription of the crRNA target sequence within the plasmid. Notably, we found that the target RNA per se induces DNA cleavage by the Cmr complex in vitro. DNA cleavage activity does not depend on cleavage of the target RNA but notably does require the presence of a short sequence adjacent to the target sequence within the activating target RNA (rPAM [RNA protospacer-adjacent motif]). The activated complex does not require a target sequence (or a PAM) in the DNA substrate. Plasmid elimination by the P. furiosus Cmr system also does not require the Csx1 (CRISPR-associated Rossman fold [CARF] superfamily) protein. Plasmid silencing depends on the HD nuclease and Palm domains of the Cmr2 (Cas10 superfamily) protein. The results establish the Cmr complex as a novel DNA nuclease activated by invader RNAs containing a crRNA target sequence and a rPAM. PMID:26848045

[Detection of pathogenic mutations in Marfan syndrome by targeted next-generation semiconductor sequencing].

PubMed

Lu, Chaoxia; Wu, Wei; Xiao, Jifang; Meng, Yan; Zhang, Shuyang; Zhang, Xue

2013-06-01

To detect pathogenic mutations in Marfan syndrome (MFS) using an Ion Torrent Personal Genome Machine (PGM) and to validate the result of targeted next-generation semiconductor sequencing for the diagnosis of genetic disorders. Peripheral blood samples were collected from three MFS patients and a normal control with informed consent. Genomic DNA was isolated by standard method and then subjected to targeted sequencing using an Ion Ampliseq(TM) Inherited Disease Panel. Three multiplex PCR reactions were carried out to amplify the coding exons of 328 genes including FBN1, TGFBR1 and TGFBR2. DNA fragments from different samples were ligated with barcoded sequencing adaptors. Template preparation and emulsion PCR, and Ion Sphere Particles enrichment were carried out using an Ion One Touch system. The ion sphere particles were sequenced on a 318 chip using the PGM platform. Data from the PGM runs were processed using an Ion Torrent Suite 3.2 software to generate sequence reads. After sequence alignment and extraction of SNPs and indels, all the variants were filtered against dbSNP137. DNA sequences were visualized with an Integrated Genomics Viewer. The most likely disease-causing variants were analyzed by Sanger sequencing. The PGM sequencing has yielded an output of 855.80 Mb, with a > 100 × median sequencing depth and a coverage of > 98% for the targeted regions in all the four samples. After data analysis and database filtering, one known missense mutation (p.E1811K) and two novel premature termination mutations (p.E2264X and p.L871FfsX23) in the FBN1 gene were identified in the three MFS patients. All mutations were verified by conventional Sanger sequencing. Pathogenic FBN1 mutations have been identified in all patients with MFS, indicating that the targeted next-generation sequencing on the PGM sequencers can be applied for accurate and high-throughput testing of genetic disorders.

Next-generation sequencing for targeted discovery of rare mutations in rice

USDA-ARS?s Scientific Manuscript database

Advances in DNA sequencing (i.e., next-generation sequencing, NGS) have greatly increased the power and efficiency of detecting rare mutations in large mutant populations. Targeting Induced Local Lesions in Genomes (TILLING) is a reverse genetics approach for identifying gene mutations resulting fro...

Deciphering the genomic targets of alkylating polyamide conjugates using high-throughput sequencing

PubMed Central

Chandran, Anandhakumar; Syed, Junetha; Taylor, Rhys D.; Kashiwazaki, Gengo; Sato, Shinsuke; Hashiya, Kaori; Bando, Toshikazu; Sugiyama, Hiroshi

2016-01-01

Chemically engineered small molecules targeting specific genomic sequences play an important role in drug development research. Pyrrole-imidazole polyamides (PIPs) are a group of molecules that can bind to the DNA minor-groove and can be engineered to target specific sequences. Their biological effects rely primarily on their selective DNA binding. However, the binding mechanism of PIPs at the chromatinized genome level is poorly understood. Herein, we report a method using high-throughput sequencing to identify the DNA-alkylating sites of PIP-indole-seco-CBI conjugates. High-throughput sequencing analysis of conjugate 2 showed highly similar DNA-alkylating sites on synthetic oligos (histone-free DNA) and on human genomes (chromatinized DNA context). To our knowledge, this is the first report identifying alkylation sites across genomic DNA by alkylating PIP conjugates using high-throughput sequencing. PMID:27098039

Automatic target recognition apparatus and method

DOEpatents

Baumgart, Chris W.; Ciarcia, Christopher A.

2000-01-01

An automatic target recognition apparatus (10) is provided, having a video camera/digitizer (12) for producing a digitized image signal (20) representing an image containing therein objects which objects are to be recognized if they meet predefined criteria. The digitized image signal (20) is processed within a video analysis subroutine (22) residing in a computer (14) in a plurality of parallel analysis chains such that the objects are presumed to be lighter in shading than the background in the image in three of the chains and further such that the objects are presumed to be darker than the background in the other three chains. In two of the chains the objects are defined by surface texture analysis using texture filter operations. In another two of the chains the objects are defined by background subtraction operations. In yet another two of the chains the objects are defined by edge enhancement processes. In each of the analysis chains a calculation operation independently determines an error factor relating to the probability that the objects are of the type which should be recognized, and a probability calculation operation combines the results of the analysis chains.

Targeted amplicon sequencing (TAS): a scalable next-gen approach to multilocus, multitaxa phylogenetics.

PubMed

Bybee, Seth M; Bracken-Grissom, Heather; Haynes, Benjamin D; Hermansen, Russell A; Byers, Robert L; Clement, Mark J; Udall, Joshua A; Wilcox, Edward R; Crandall, Keith A

2011-01-01

Next-gen sequencing technologies have revolutionized data collection in genetic studies and advanced genome biology to novel frontiers. However, to date, next-gen technologies have been used principally for whole genome sequencing and transcriptome sequencing. Yet many questions in population genetics and systematics rely on sequencing specific genes of known function or diversity levels. Here, we describe a targeted amplicon sequencing (TAS) approach capitalizing on next-gen capacity to sequence large numbers of targeted gene regions from a large number of samples. Our TAS approach is easily scalable, simple in execution, neither time-nor labor-intensive, relatively inexpensive, and can be applied to a broad diversity of organisms and/or genes. Our TAS approach includes a bioinformatic application, BarcodeCrucher, to take raw next-gen sequence reads and perform quality control checks and convert the data into FASTA format organized by gene and sample, ready for phylogenetic analyses. We demonstrate our approach by sequencing targeted genes of known phylogenetic utility to estimate a phylogeny for the Pancrustacea. We generated data from 44 taxa using 68 different 10-bp multiplexing identifiers. The overall quality of data produced was robust and was informative for phylogeny estimation. The potential for this method to produce copious amounts of data from a single 454 plate (e.g., 325 taxa for 24 loci) significantly reduces sequencing expenses incurred from traditional Sanger sequencing. We further discuss the advantages and disadvantages of this method, while offering suggestions to enhance the approach.

Targeted Amplicon Sequencing (TAS): A Scalable Next-Gen Approach to Multilocus, Multitaxa Phylogenetics

PubMed Central

Bybee, Seth M.; Bracken-Grissom, Heather; Haynes, Benjamin D.; Hermansen, Russell A.; Byers, Robert L.; Clement, Mark J.; Udall, Joshua A.; Wilcox, Edward R.; Crandall, Keith A.

2011-01-01

Next-gen sequencing technologies have revolutionized data collection in genetic studies and advanced genome biology to novel frontiers. However, to date, next-gen technologies have been used principally for whole genome sequencing and transcriptome sequencing. Yet many questions in population genetics and systematics rely on sequencing specific genes of known function or diversity levels. Here, we describe a targeted amplicon sequencing (TAS) approach capitalizing on next-gen capacity to sequence large numbers of targeted gene regions from a large number of samples. Our TAS approach is easily scalable, simple in execution, neither time-nor labor-intensive, relatively inexpensive, and can be applied to a broad diversity of organisms and/or genes. Our TAS approach includes a bioinformatic application, BarcodeCrucher, to take raw next-gen sequence reads and perform quality control checks and convert the data into FASTA format organized by gene and sample, ready for phylogenetic analyses. We demonstrate our approach by sequencing targeted genes of known phylogenetic utility to estimate a phylogeny for the Pancrustacea. We generated data from 44 taxa using 68 different 10-bp multiplexing identifiers. The overall quality of data produced was robust and was informative for phylogeny estimation. The potential for this method to produce copious amounts of data from a single 454 plate (e.g., 325 taxa for 24 loci) significantly reduces sequencing expenses incurred from traditional Sanger sequencing. We further discuss the advantages and disadvantages of this method, while offering suggestions to enhance the approach. PMID:22002916

Background characterization techniques for target detection using scene metrics and pattern recognition

NASA Astrophysics Data System (ADS)

Noah, Paul V.; Noah, Meg A.; Schroeder, John W.; Chernick, Julian A.

1990-09-01

The U.S. Army has a requirement to develop systems for the detection and identification of ground targets in a clutter environment. Autonomous Homing Munitions (AHM) using infrared, visible, millimeter wave and other sensors are being investigated for this application. Advanced signal processing and computational approaches using pattern recognition and artificial intelligence techniques combined with multisensor data fusion have the potential to meet the Army's requirements for next generation ARM.

Correlation Time of Ocean Ambient Noise Intensity in San Diego Bay and Target Recognition in Acoustic Daylight Images

NASA Astrophysics Data System (ADS)

Wadsworth, Adam J.

A method for passively detecting and imaging underwater targets using ambient noise as the sole source of illumination (named acoustic daylight) was successfully implemented in the form of the Acoustic Daylight Ocean Noise Imaging System (ADONIS). In a series of imaging experiments conducted in San Diego Bay, where the dominant source of high-frequency ambient noise is snapping shrimp, a large quantity of ambient noise intensity data was collected with the ADONIS (Epifanio, 1997). In a subset of the experimental data sets, fluctuations of time-averaged ambient noise intensity exhibited a diurnal pattern consistent with the increase in frequency of shrimp snapping near dawn and dusk. The same subset of experimental data is revisited here and the correlation time is estimated and analysed for sequences of ambient noise data several minutes in length, with the aim of detecting possible periodicities or other trends in the fluctuation of the shrimp-dominated ambient noise field. Using videos formed from sequences of acoustic daylight images along with other experimental information, candidate segments of static-configuration ADONIS raw ambient noise data were isolated. For each segment, the normalized intensity auto-correlation closely resembled the delta function, the auto-correlation of white noise. No intensity fluctuation patterns at timescales smaller than a few minutes were discernible, suggesting that the shrimp do not communicate, synchronise, or exhibit any periodicities in their snapping. Also presented here is a ADONIS-specific target recognition algorithm based on principal component analysis, along with basic experimental results using a database of acoustic daylight images.

Application of Quaternion in improving the quality of global sequence alignment scores for an ambiguous sequence target in Streptococcus pneumoniae DNA

NASA Astrophysics Data System (ADS)

Lestari, D.; Bustamam, A.; Novianti, T.; Ardaneswari, G.

2017-07-01

DNA sequence can be defined as a succession of letters, representing the order of nucleotides within DNA, using a permutation of four DNA base codes including adenine (A), guanine (G), cytosine (C), and thymine (T). The precise code of the sequences is determined using DNA sequencing methods and technologies, which have been developed since the 1970s and currently become highly developed, advanced and highly throughput sequencing technologies. So far, DNA sequencing has greatly accelerated biological and medical research and discovery. However, in some cases DNA sequencing could produce any ambiguous and not clear enough sequencing results that make them quite difficult to be determined whether these codes are A, T, G, or C. To solve these problems, in this study we can introduce other representation of DNA codes namely Quaternion Q = (PA, PT, PG, PC), where PA, PT, PG, PC are the probability of A, T, G, C bases that could appear in Q and PA + PT + PG + PC = 1. Furthermore, using Quaternion representations we are able to construct the improved scoring matrix for global sequence alignment processes, by applying a dot product method. Moreover, this scoring matrix produces better and higher quality of the match and mismatch score between two DNA base codes. In implementation, we applied the Needleman-Wunsch global sequence alignment algorithm using Octave, to analyze our target sequence which contains some ambiguous sequence data. The subject sequences are the DNA sequences of Streptococcus pneumoniae families obtained from the Genebank, meanwhile the target DNA sequence are received from our collaborator database. As the results we found the Quaternion representations improve the quality of the sequence alignment score and we can conclude that DNA sequence target has maximum similarity with Streptococcus pneumoniae.

Infrared target recognition based on improved joint local ternary pattern

NASA Astrophysics Data System (ADS)

Sun, Junding; Wu, Xiaosheng

2016-05-01

This paper presents a simple, efficient, yet robust approach, named joint orthogonal combination of local ternary pattern, for automatic forward-looking infrared target recognition. It gives more advantages to describe the macroscopic textures and microscopic textures by fusing variety of scales than the traditional LBP-based methods. In addition, it can effectively reduce the feature dimensionality. Further, the rotation invariant and uniform scheme, the robust LTP, and soft concave-convex partition are introduced to enhance its discriminative power. Experimental results demonstrate that the proposed method can achieve competitive results compared with the state-of-the-art methods.

Slp-76 is a critical determinant of NK-cell mediated recognition of missing-self targets.

PubMed

Lampe, Kristin; Endale, Mehari; Cashman, Siobhan; Fang, Hao; Mattner, Jochen; Hildeman, David; Hoebe, Kasper

2015-07-01

Absence of MHC class I expression is an important mechanism by which NK cells recognize a variety of target cells, yet the pathways underlying "missing-self" recognition, including the involvement of activating receptors, remain poorly understood. Using ethyl-N-nitrosourea mutagenesis in mice, we identified a germline mutant, designated Ace, with a marked defect in NK cell mediated recognition and elimination of "missing-self" targets. The causative mutation was linked to chromosome 11 and identified as a missense mutation (Thr428Ile) in the SH2 domain of Slp-76-a critical adapter molecule downstream of ITAM-containing surface receptors. The Slp-76 Ace mutation behaved as a hypomorphic allele-while no major defects were observed in conventional T-cell development/function, a marked defect in NK cell mediated elimination of β2-microglobulin (β2M) deficient target cells was observed. Further studies revealed Slp-76 to control NK-cell receptor expression and maturation; however, activation of Slp-76(ace/ace) NK cells through ITAM-containing NK-cell receptors or allogeneic/tumor target cells appeared largely unaffected. Imagestream analysis of the NK-β2M(-/-) target cell synapse revealed a specific defect in actin recruitment to the conjugate synapse in Slp-76(ace/ace) NK cells. Overall these studies establish Slp-76 as a critical determinant of NK-cell development and NK cell mediated elimination of missing-self target cells in mice. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Slp-76 is a critical determinant of NK cell-mediated recognition of missing-self targets

PubMed Central

Lampe, Kristin; Endale, Mehari; Cashman, Siobhan; Fang, Hao; Mattner, Jochen; Hildeman, David; Hoebe, Kasper

2015-01-01

Absence of MHC class I expression is an important mechanism by which NK cells recognize a variety of target cells, yet the pathways underlying “missing-self” recognition, including the involvement of activating receptors, remain poorly understood. Using ENU mutagenesis in mice, we identified a germline mutant, designated Ace, with a marked defect in NK cell-mediated recognition and elimination of “missing-self” targets. The causative mutation was linked to chromosome 11 and identified as a missense mutation [Thr428Ile] in the SH2 domain of Slp-76—a critical adapter molecule downstream of ITAM-containing surface receptors. The Slp-76 Ace mutation behaved as a hypomorphic allele—while no major defects were observed in conventional T cell development/function, a marked defect in NK cell-mediated elimination of β2-Microglobulin (β2M)-deficient target cells was observed. Further studies revealed Slp-76 to control NK cell receptor expression and maturation, however, activation of Slp-76ace/ace NK cells through ITAM-containing NK cell receptors or allogeneic/tumor target cells appeared largely unaffected. Imagestream analysis of the NK-β2M−/− target cell synapse, revealed a specific defect in actin recruitment to the conjugate synapse in Slp-76ace/ace NK cells. Overall these studies establish Slp-76 as a critical determinant of NK cell development and NK cell-mediated elimination of missing-self target cells. PMID:25929249

A protein block based fold recognition method for the annotation of twilight zone sequences.

PubMed

Suresh, V; Ganesan, K; Parthasarathy, S

2013-03-01

The description of protein backbone was recently improved with a group of structural fragments called Structural Alphabets instead of the regular three states (Helix, Sheet and Coil) secondary structure description. Protein Blocks is one of the Structural Alphabets used to describe each and every region of protein backbone including the coil. According to de Brevern (2000) the Protein Blocks has 16 structural fragments and each one has 5 residues in length. Protein Blocks fragments are highly informative among the available Structural Alphabets and it has been used for many applications. Here, we present a protein fold recognition method based on Protein Blocks for the annotation of twilight zone sequences. In our method, we align the predicted Protein Blocks of a query amino acid sequence with a library of assigned Protein Blocks of 953 known folds using the local pair-wise alignment. The alignment results with z-value ≥ 2.5 and P-value ≤ 0.08 are predicted as possible folds. Our method is able to recognize the possible folds for nearly 35.5% of the twilight zone sequences with their predicted Protein Block sequence obtained by pb_prediction, which is available at Protein Block Export server.

Invariant-feature-based adaptive automatic target recognition in obscured 3D point clouds

NASA Astrophysics Data System (ADS)

Khuon, Timothy; Kershner, Charles; Mattei, Enrico; Alverio, Arnel; Rand, Robert

2014-06-01

Target recognition and classification in a 3D point cloud is a non-trivial process due to the nature of the data collected from a sensor system. The signal can be corrupted by noise from the environment, electronic system, A/D converter, etc. Therefore, an adaptive system with a desired tolerance is required to perform classification and recognition optimally. The feature-based pattern recognition algorithm architecture as described below is particularly devised for solving a single-sensor classification non-parametrically. Feature set is extracted from an input point cloud, normalized, and classifier a neural network classifier. For instance, automatic target recognition in an urban area would require different feature sets from one in a dense foliage area. The figure above (see manuscript) illustrates the architecture of the feature based adaptive signature extraction of 3D point cloud including LIDAR, RADAR, and electro-optical data. This network takes a 3D cluster and classifies it into a specific class. The algorithm is a supervised and adaptive classifier with two modes: the training mode and the performing mode. For the training mode, a number of novel patterns are selected from actual or artificial data. A particular 3D cluster is input to the network as shown above for the decision class output. The network consists of three sequential functional modules. The first module is for feature extraction that extracts the input cluster into a set of singular value features or feature vector. Then the feature vector is input into the feature normalization module to normalize and balance it before being fed to the neural net classifier for the classification. The neural net can be trained by actual or artificial novel data until each trained output reaches the declared output within the defined tolerance. In case new novel data is added after the neural net has been learned, the training is then resumed until the neural net has incrementally learned with the new

Efficient Identification of Murine M2 Macrophage Peptide Targeting Ligands by Phage Display and Next-Generation Sequencing.

PubMed

Liu, Gary W; Livesay, Brynn R; Kacherovsky, Nataly A; Cieslewicz, Maryelise; Lutz, Emi; Waalkes, Adam; Jensen, Michael C; Salipante, Stephen J; Pun, Suzie H

2015-08-19

Peptide ligands are used to increase the specificity of drug carriers to their target cells and to facilitate intracellular delivery. One method to identify such peptide ligands, phage display, enables high-throughput screening of peptide libraries for ligands binding to therapeutic targets of interest. However, conventional methods for identifying target binders in a library by Sanger sequencing are low-throughput, labor-intensive, and provide a limited perspective (<0.01%) of the complete sequence space. Moreover, the small sample space can be dominated by nonspecific, preferentially amplifying "parasitic sequences" and plastic-binding sequences, which may lead to the identification of false positives or exclude the identification of target-binding sequences. To overcome these challenges, we employed next-generation Illumina sequencing to couple high-throughput screening and high-throughput sequencing, enabling more comprehensive access to the phage display library sequence space. In this work, we define the hallmarks of binding sequences in next-generation sequencing data, and develop a method that identifies several target-binding phage clones for murine, alternatively activated M2 macrophages with a high (100%) success rate: sequences and binding motifs were reproducibly present across biological replicates; binding motifs were identified across multiple unique sequences; and an unselected, amplified library accurately filtered out parasitic sequences. In addition, we validate the Multiple Em for Motif Elicitation tool as an efficient and principled means of discovering binding sequences.

Profiling of potential driver mutations in sarcomas by targeted next generation sequencing.

PubMed

Andersson, Carola; Fagman, Henrik; Hansson, Magnus; Enlund, Fredrik

2016-04-01

Comprehensive genetic profiling by massively parallel sequencing, commonly known as next generation sequencing (NGS), is becoming the foundation of personalized oncology. For sarcomas very few targeted treatments are currently in routine use. In clinical practice the preoperative diagnostic workup of soft tissue tumours largely relies on core needle biopsies. Although mostly sufficient for histopathological diagnosis, only very limited amounts of formalin fixated paraffin embedded tissue are often available for predictive mutation analysis. Targeted NGS may thus open up new possibilities for comprehensive characterization of scarce biopsies. We therefore set out to search for driver mutations by NGS in a cohort of 55 clinically and morphologically well characterized sarcomas using low input of DNA from formalin fixated paraffin embedded tissues. The aim was to investigate if there are any recurrent or targetable aberrations in cancer driver genes in addition to known chromosome translocations in different types of sarcomas. We employed a panel covering 207 mutation hotspots in 50 cancer-associated genes to analyse DNA from nine gastrointestinal stromal tumours, 14 synovial sarcomas, seven myxoid liposarcomas, 22 Ewing sarcomas and three Ewing-like small round cell tumours at a large sequencing depth to detect also mutations that are subclonal or occur at low allele frequencies. We found nine mutations in eight different potential driver genes, some of which are potentially actionable by currently existing targeted therapies. Even though no recurrent mutations in driver genes were found in the different sarcoma groups, we show that targeted NGS-based sequencing is clearly feasible in a diagnostic setting with very limited amounts of paraffin embedded tissue and may provide novel insights into mesenchymal cell signalling and potentially druggable targets. Interestingly, we also identify five non-synonymous sequence variants in 4 established cancer driver genes in DNA

Target recognition and scene interpretation in image/video understanding systems based on network-symbolic models

NASA Astrophysics Data System (ADS)

Kuvich, Gary

2004-08-01

Vision is only a part of a system that converts visual information into knowledge structures. These structures drive the vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, which is an interpretation of visual information in terms of these knowledge models. These mechanisms provide a reliable recognition if the object is occluded or cannot be recognized as a whole. It is hard to split the entire system apart, and reliable solutions to the target recognition problems are possible only within the solution of a more generic Image Understanding Problem. Brain reduces informational and computational complexities, using implicit symbolic coding of features, hierarchical compression, and selective processing of visual information. Biologically inspired Network-Symbolic representation, where both systematic structural/logical methods and neural/statistical methods are parts of a single mechanism, is the most feasible for such models. It converts visual information into relational Network-Symbolic structures, avoiding artificial precise computations of 3-dimensional models. Network-Symbolic Transformations derive abstract structures, which allows for invariant recognition of an object as exemplar of a class. Active vision helps creating consistent models. Attention, separation of figure from ground and perceptual grouping are special kinds of network-symbolic transformations. Such Image/Video Understanding Systems will be reliably recognizing targets.

An Optimized Transient Dual Luciferase Assay for Quantifying MicroRNA Directed Repression of Targeted Sequences

PubMed Central

Moyle, Richard L.; Carvalhais, Lilia C.; Pretorius, Lara-Simone; Nowak, Ekaterina; Subramaniam, Gayathery; Dalton-Morgan, Jessica; Schenk, Peer M.

2017-01-01

Studies investigating the action of small RNAs on computationally predicted target genes require some form of experimental validation. Classical molecular methods of validating microRNA action on target genes are laborious, while approaches that tag predicted target sequences to qualitative reporter genes encounter technical limitations. The aim of this study was to address the challenge of experimentally validating large numbers of computationally predicted microRNA-target transcript interactions using an optimized, quantitative, cost-effective, and scalable approach. The presented method combines transient expression via agroinfiltration of Nicotiana benthamiana leaves with a quantitative dual luciferase reporter system, where firefly luciferase is used to report the microRNA-target sequence interaction and Renilla luciferase is used as an internal standard to normalize expression between replicates. We report the appropriate concentration of N. benthamiana leaf extracts and dilution factor to apply in order to avoid inhibition of firefly LUC activity. Furthermore, the optimal ratio of microRNA precursor expression construct to reporter construct and duration of the incubation period post-agroinfiltration were determined. The optimized dual luciferase assay provides an efficient, repeatable and scalable method to validate and quantify microRNA action on predicted target sequences. The optimized assay was used to validate five predicted targets of rice microRNA miR529b, with as few as six technical replicates. The assay can be extended to assess other small RNA-target sequence interactions, including assessing the functionality of an artificial miRNA or an RNAi construct on a targeted sequence. PMID:28979287

Increase in Speech Recognition Due to Linguistic Mismatch between Target and Masker Speech: Monolingual and Simultaneous Bilingual Performance

ERIC Educational Resources Information Center

Calandruccio, Lauren; Zhou, Haibo

2014-01-01

Purpose: To examine whether improved speech recognition during linguistically mismatched target-masker experiments is due to linguistic unfamiliarity of the masker speech or linguistic dissimilarity between the target and masker speech. Method: Monolingual English speakers (n = 20) and English-Greek simultaneous bilinguals (n = 20) listened to…

Automatic target recognition using a feature-based optical neural network

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

1992-01-01

An optical neural network based upon the Neocognitron paradigm (K. Fukushima et al. 1983) is introduced. A novel aspect of the architectural design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator and updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intra-class fault tolerance and inter-class discrimination is achieved. A detailed system description is provided. Experimental demonstration of a two-layer neural network for space objects discrimination is also presented.

PNA containing isocytidine nucleobase: synthesis and recognition of double helical RNA

PubMed Central

Zengeya, Thomas; Li, Ming; Rozners, Eriks

2011-01-01

Peptide nucleic acid (PNA1) containing a 5-methylisocytidine (iC) nucleobase has been synthesized. Triple helix formation between PNA1 and RNA hairpins having variable base pairs interacting with iC was studied using isothermal titration calorimetry. The iC nucleobase recognized the proposed target, C-G inversion in polypurine tract of RNA, with slightly higher affinity than the natural nucleobases, though the sequence selectivity of recognition was low. Compared to non-modified PNA, PNA1 had lower affinity for its RNA target. PMID:21333533

Genome-wide evidence for local DNA methylation spreading from small RNA-targeted sequences in Arabidopsis.

PubMed

Ahmed, Ikhlak; Sarazin, Alexis; Bowler, Chris; Colot, Vincent; Quesneville, Hadi

2011-09-01

Transposable elements (TEs) and their relics play major roles in genome evolution. However, mobilization of TEs is usually deleterious and strongly repressed. In plants and mammals, this repression is typically associated with DNA methylation, but the relationship between this epigenetic mark and TE sequences has not been investigated systematically. Here, we present an improved annotation of TE sequences and use it to analyze genome-wide DNA methylation maps obtained at single-nucleotide resolution in Arabidopsis. We show that although the majority of TE sequences are methylated, ∼26% are not. Moreover, a significant fraction of TE sequences densely methylated at CG, CHG and CHH sites (where H = A, T or C) have no or few matching small interfering RNA (siRNAs) and are therefore unlikely to be targeted by the RNA-directed DNA methylation (RdDM) machinery. We provide evidence that these TE sequences acquire DNA methylation through spreading from adjacent siRNA-targeted regions. Further, we show that although both methylated and unmethylated TE sequences located in euchromatin tend to be more abundant closer to genes, this trend is least pronounced for methylated, siRNA-targeted TE sequences located 5' to genes. Based on these and other findings, we propose that spreading of DNA methylation through promoter regions explains at least in part the negative impact of siRNA-targeted TE sequences on neighboring gene expression.

[A new mechanism of ubiquitin-dependent proteolytic pathway--polyubiquitin chain recognition and proteasomal targeting].

PubMed

Kawahara, Hiroyuki; Yokosawa, Hideyoshi

2008-01-01

The RPN10 subunit of 26S proteasome and several UBA domain proteins can bind to the polyubiquitin chain and play a role as ubiquitin receptors of the 26S proteasome. Although it was thought that substrate recognition is an essential step in the proteasome-mediated protein degradation, deletion of rpn10 genes in yeast does not influence the viability of cells but instead causes only a mild phenotype, suggesting that the above ubiquitin receptors are redundantly involved in substrate delivery to the proteasome. However, their functional difference is still enigmatic. In this review, we summarize recent advances in polyubiquitin chain recognition/delivery system and provide potential applications to modulate this system as a probable target for drug development.

Evolution of I-SceI Homing Endonucleases with Increased DNA Recognition Site Specificity

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

Joshi, Rakesh; Ho, Kwok Ki; Tenney, Kristen

2013-09-18

Elucidating how homing endonucleases undergo changes in recognition site specificity will facilitate efforts to engineer proteins for gene therapy applications. I-SceI is a monomeric homing endonuclease that recognizes and cleaves within an 18-bp target. It tolerates limited degeneracy in its target sequence, including substitution of a C:G{sub +4} base pair for the wild-type A:T{sub +4} base pair. Libraries encoding randomized amino acids at I-SceI residue positions that contact or are proximal to A:T{sub +4} were used in conjunction with a bacterial one-hybrid system to select I-SceI derivatives that bind to recognition sites containing either the A:T{sub +4} or the C:G{submore » +4} base pairs. As expected, isolates encoding wild-type residues at the randomized positions were selected using either target sequence. All I-SceI proteins isolated using the C:G{sub +4} recognition site included small side-chain substitutions at G100 and either contained (K86R/G100T, K86R/G100S and K86R/G100C) or lacked (G100A, G100T) a K86R substitution. Interestingly, the binding affinities of the selected variants for the wild-type A:T{sub +4} target are 4- to 11-fold lower than that of wild-type I-SceI, whereas those for the C:G{sub +4} target are similar. The increased specificity of the mutant proteins is also evident in binding experiments in vivo. These differences in binding affinities account for the observed -36-fold difference in target preference between the K86R/G100T and wild-type proteins in DNA cleavage assays. An X-ray crystal structure of the K86R/G100T mutant protein bound to a DNA duplex containing the C:G{sub +4} substitution suggests how sequence specificity of a homing enzyme can increase. This biochemical and structural analysis defines one pathway by which site specificity is augmented for a homing endonuclease.« less

Reconsidering the role of temporal order in spoken word recognition.

PubMed

Toscano, Joseph C; Anderson, Nathaniel D; McMurray, Bob

2013-10-01

Models of spoken word recognition assume that words are represented as sequences of phonemes. We evaluated this assumption by examining phonemic anadromes, words that share the same phonemes but differ in their order (e.g., sub and bus). Using the visual-world paradigm, we found that listeners show more fixations to anadromes (e.g., sub when bus is the target) than to unrelated words (well) and to words that share the same vowel but not the same set of phonemes (sun). This contrasts with the predictions of existing models and suggests that words are not defined as strict sequences of phonemes.

Deep sequencing methods for protein engineering and design.

PubMed

Wrenbeck, Emily E; Faber, Matthew S; Whitehead, Timothy A

2017-08-01

The advent of next-generation sequencing (NGS) has revolutionized protein science, and the development of complementary methods enabling NGS-driven protein engineering have followed. In general, these experiments address the functional consequences of thousands of protein variants in a massively parallel manner using genotype-phenotype linked high-throughput functional screens followed by DNA counting via deep sequencing. We highlight the use of information rich datasets to engineer protein molecular recognition. Examples include the creation of multiple dual-affinity Fabs targeting structurally dissimilar epitopes and engineering of a broad germline-targeted anti-HIV-1 immunogen. Additionally, we highlight the generation of enzyme fitness landscapes for conducting fundamental studies of protein behavior and evolution. We conclude with discussion of technological advances. Copyright © 2016 Elsevier Ltd. All rights reserved.

Isolation and characterization of target sequences of the chicken CdxA homeobox gene.

PubMed Central

Margalit, Y; Yarus, S; Shapira, E; Gruenbaum, Y; Fainsod, A

1993-01-01

The DNA binding specificity of the chicken homeodomain protein CDXA was studied. Using a CDXA-glutathione-S-transferase fusion protein, DNA fragments containing the binding site for this protein were isolated. The sources of DNA were oligonucleotides with random sequence and chicken genomic DNA. The DNA fragments isolated were sequenced and tested in DNA binding assays. Sequencing revealed that most DNA fragments are AT rich which is a common feature of homeodomain binding sites. By electrophoretic mobility shift assays it was shown that the different target sequences isolated bind to the CDXA protein with different affinities. The specific sequences bound by the CDXA protein in the genomic fragments isolated, were determined by DNase I footprinting. From the footprinted sequences, the CDXA consensus binding site was determined. The CDXA protein binds the consensus sequence A, A/T, T, A/T, A, T, A/G. The CAUDAL binding site in the ftz promoter is also included in this consensus sequence. When tested, some of the genomic target sequences were capable of enhancing the transcriptional activity of reporter plasmids when introduced into CDXA expressing cells. This study determined the DNA sequence specificity of the CDXA protein and it also shows that this protein can further activate transcription in cells in culture. Images PMID:7909943

How proteins bind to DNA: target discrimination and dynamic sequence search by the telomeric protein TRF1

PubMed Central

2017-01-01

Abstract Target search as performed by DNA-binding proteins is a complex process, in which multiple factors contribute to both thermodynamic discrimination of the target sequence from overwhelmingly abundant off-target sites and kinetic acceleration of dynamic sequence interrogation. TRF1, the protein that binds to telomeric tandem repeats, faces an intriguing variant of the search problem where target sites are clustered within short fragments of chromosomal DNA. In this study, we use extensive (>0.5 ms in total) MD simulations to study the dynamical aspects of sequence-specific binding of TRF1 at both telomeric and non-cognate DNA. For the first time, we describe the spontaneous formation of a sequence-specific native protein–DNA complex in atomistic detail, and study the mechanism by which proteins avoid off-target binding while retaining high affinity for target sites. Our calculated free energy landscapes reproduce the thermodynamics of sequence-specific binding, while statistical approaches allow for a comprehensive description of intermediate stages of complex formation. PMID:28633355

Directing an artificial zinc finger protein to new targets by fusion to a non-DNA-binding domain.

PubMed

Lim, Wooi F; Burdach, Jon; Funnell, Alister P W; Pearson, Richard C M; Quinlan, Kate G R; Crossley, Merlin

2016-04-20

Transcription factors are often regarded as having two separable components: a DNA-binding domain (DBD) and a functional domain (FD), with the DBD thought to determine target gene recognition. While this holds true for DNA bindingin vitro, it appears thatin vivoFDs can also influence genomic targeting. We fused the FD from the well-characterized transcription factor Krüppel-like Factor 3 (KLF3) to an artificial zinc finger (AZF) protein originally designed to target the Vascular Endothelial Growth Factor-A (VEGF-A) gene promoter. We compared genome-wide occupancy of the KLF3FD-AZF fusion to that observed with AZF. AZF bound to theVEGF-Apromoter as predicted, but was also found to occupy approximately 25,000 other sites, a large number of which contained the expected AZF recognition sequence, GCTGGGGGC. Interestingly, addition of the KLF3 FD re-distributes the fusion protein to new sites, with total DNA occupancy detected at around 50,000 sites. A portion of these sites correspond to known KLF3-bound regions, while others contained sequences similar but not identical to the expected AZF recognition sequence. These results show that FDs can influence and may be useful in directing AZF DNA-binding proteins to specific targets and provide insights into how natural transcription factors operate. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

BreaKmer: detection of structural variation in targeted massively parallel sequencing data using kmers.

PubMed

Abo, Ryan P; Ducar, Matthew; Garcia, Elizabeth P; Thorner, Aaron R; Rojas-Rudilla, Vanesa; Lin, Ling; Sholl, Lynette M; Hahn, William C; Meyerson, Matthew; Lindeman, Neal I; Van Hummelen, Paul; MacConaill, Laura E

2015-02-18

Genomic structural variation (SV), a common hallmark of cancer, has important predictive and therapeutic implications. However, accurately detecting SV using high-throughput sequencing data remains challenging, especially for 'targeted' resequencing efforts. This is critically important in the clinical setting where targeted resequencing is frequently being applied to rapidly assess clinically actionable mutations in tumor biopsies in a cost-effective manner. We present BreaKmer, a novel approach that uses a 'kmer' strategy to assemble misaligned sequence reads for predicting insertions, deletions, inversions, tandem duplications and translocations at base-pair resolution in targeted resequencing data. Variants are predicted by realigning an assembled consensus sequence created from sequence reads that were abnormally aligned to the reference genome. Using targeted resequencing data from tumor specimens with orthogonally validated SV, non-tumor samples and whole-genome sequencing data, BreaKmer had a 97.4% overall sensitivity for known events and predicted 17 positively validated, novel variants. Relative to four publically available algorithms, BreaKmer detected SV with increased sensitivity and limited calls in non-tumor samples, key features for variant analysis of tumor specimens in both the clinical and research settings. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Unusual target site disruption by the rare-cutting HNH restriction endonuclease PacI

PubMed Central

Shen, Betty; Heiter, Daniel F.; Chan, Siu-Hong; Wang, Hua; Xu, Shuang-Yong; Morgan, Richard D.; Wilson, Geoffrey G.; Stoddard, Barry L.

2010-01-01

The crystal structure of the rare-cutting HNH restriction endonuclease PacI in complex with its eight base pair target recognition sequence 5'-TTAATTAA-3' has been determined to 1.9 Å resolution. The enzyme forms an extended homodimer, with each subunit containing two zinc-bound motifs surrounding a ββα-metal catalytic site. The latter is unusual in that a tyrosine residue likely initiates strand-cleavage. PacI dramatically distorts its target sequence from Watson-Crick duplex DNA basepairing, with every base separated from its original partner. Two bases on each strand are unpaired, four are engaged in non-canonical A:A and T:T base pairs, and the remaining two bases are matched with new Watson-Crick partners. This represents a highly unusual DNA binding mechanism for a restriction endonuclease, and implies that initial recognition of the target site might involve significantly different contacts from those visualized in the DNA-bound cocrystal structures. PMID:20541511

Implementation of an Autonomous Multi-Maneuver Targeting Sequence for Lunar Trans-Earth Injection

NASA Technical Reports Server (NTRS)

Whitley, Ryan J.; Williams, Jacob

2010-01-01

Using a fully analytic initial guess estimate as a first iterate, a targeting procedure that constructs a flyable burn maneuver sequence to transfer a spacecraft from any closed Moon orbit to a desired Earth entry state is developed and implemented. The algorithm is built to support the need for an anytime abort capability for Orion. Based on project requirements, the Orion spacecraft must be able to autonomously calculate the translational maneuver targets for an entire Lunar mission. Translational maneuver target sequences for the Orion spacecraft include Lunar Orbit Insertion (LOI), Trans-Earth Injection (TEI), and Trajectory Correction Maneuvers (TCMs). This onboard capability is generally assumed to be supplemental to redundant ground computation in nominal mission operations and considered as a viable alternative primarily in loss of communications contingencies. Of these maneuvers, the ability to accurately and consistently establish a flyable 3-burn TEI target sequence is especially critical. The TEI is the sole means by which the crew can successfully return from the Moon to a narrowly banded Earth Entry Interface (EI) state. This is made even more critical by the desire for global access on the lunar surface. Currently, the designed propellant load is based on fully optimized TEI solutions for the worst case geometries associated with the accepted range of epochs and landing sites. This presents two challenges for an autonomous algorithm: in addition to being feasible, the targets must include burn sequences that do not exceed the anticipated propellant load.

A novel probabilistic framework for event-based speech recognition

NASA Astrophysics Data System (ADS)

Juneja, Amit; Espy-Wilson, Carol

2003-10-01

One of the reasons for unsatisfactory performance of the state-of-the-art automatic speech recognition (ASR) systems is the inferior acoustic modeling of low-level acoustic-phonetic information in the speech signal. An acoustic-phonetic approach to ASR, on the other hand, explicitly targets linguistic information in the speech signal, but such a system for continuous speech recognition (CSR) is not known to exist. A probabilistic and statistical framework for CSR based on the idea of the representation of speech sounds by bundles of binary valued articulatory phonetic features is proposed. Multiple probabilistic sequences of linguistically motivated landmarks are obtained using binary classifiers of manner phonetic features-syllabic, sonorant and continuant-and the knowledge-based acoustic parameters (APs) that are acoustic correlates of those features. The landmarks are then used for the extraction of knowledge-based APs for source and place phonetic features and their binary classification. Probabilistic landmark sequences are constrained using manner class language models for isolated or connected word recognition. The proposed method could overcome the disadvantages encountered by the early acoustic-phonetic knowledge-based systems that led the ASR community to switch to systems highly dependent on statistical pattern analysis methods and probabilistic language or grammar models.

Comparison of taxon-specific versus general locus sets for targeted sequence capture in plant phylogenomics.

PubMed

Chau, John H; Rahfeldt, Wolfgang A; Olmstead, Richard G

2018-03-01

Targeted sequence capture can be used to efficiently gather sequence data for large numbers of loci, such as single-copy nuclear loci. Most published studies in plants have used taxon-specific locus sets developed individually for a clade using multiple genomic and transcriptomic resources. General locus sets can also be developed from loci that have been identified as single-copy and have orthologs in large clades of plants. We identify and compare a taxon-specific locus set and three general locus sets (conserved ortholog set [COSII], shared single-copy nuclear [APVO SSC] genes, and pentatricopeptide repeat [PPR] genes) for targeted sequence capture in Buddleja (Scrophulariaceae) and outgroups. We evaluate their performance in terms of assembly success, sequence variability, and resolution and support of inferred phylogenetic trees. The taxon-specific locus set had the most target loci. Assembly success was high for all locus sets in Buddleja samples. For outgroups, general locus sets had greater assembly success. Taxon-specific and PPR loci had the highest average variability. The taxon-specific data set produced the best-supported tree, but all data sets showed improved resolution over previous non-sequence capture data sets. General locus sets can be a useful source of sequence capture targets, especially if multiple genomic resources are not available for a taxon.

Phosphoenolpyruvate carboxykinase of Trypanosoma brucei is targeted to the glycosomes by a C-terminal sequence.

PubMed

Sommer, J M; Nguyen, T T; Wang, C C

1994-08-15

Import of proteins into the glycosomes of T. brucei resembles the peroxisomal protein import in that C-terminal SKL-like tripeptide sequences can function as targeting signals. Many of the glycosomal proteins do not, however, possess such C-terminal tripeptide signals. Among these, phosphoenolpyruvate carboxykinase (PEPCK (ATP)) was thought to be targeted to the glycosomes by an N-terminal or an internal targeting signal. A limited similarity to the N-terminal targeting signal of rat peroxisomal thiolase exists at the N-terminus of T. brucei PEPCK. However, we found that this peroxisomal targeting signal does not function for glycosomal protein import in T. brucei. Further studies of the PEPCK gene revealed that the C-terminus of the predicted protein does not correspond to the previously deduced protein sequence of 472 amino acids due to a -1 frame shift error in the original DNA sequence. Readjusting the reading frame of the sequence results in a predicted protein of 525 amino acids in length ending in a tripeptide serine-arginine-leucine (SRL), which is a potential targeting signal for import into the glycosomes. A fusion protein of firefly luciferase, without its own C-terminal SKL targeting signal, and T. brucei PEPCK is efficiently imported into the glycosomes when expressed in procyclic trypanosomes. Deletion of the C-terminal SRL tripeptide or the last 29 amino acids of PEPCK reduced the import only by about 50%, while a deletion of the last 47 amino acids completely abolished the import. These results suggest that T. brucei PEPCK may contain a second, internal glycosomal targeting signal upstream of the C-terminal SRL sequence.

Mapping a nucleolar targeting sequence of an RNA binding nucleolar protein, Nop25

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

Fujiwara, Takashi; Suzuki, Shunji; Kanno, Motoko

2006-06-10

Nop25 is a putative RNA binding nucleolar protein associated with rRNA transcription. The present study was undertaken to determine the mechanism of Nop25 localization in the nucleolus. Deletion experiments of Nop25 amino acid sequence showed Nop25 to contain a nuclear targeting sequence in the N-terminal and a nucleolar targeting sequence in the C-terminal. By expressing derivative peptides from the C-terminal as GFP-fusion proteins in the cells, a lysine and arginine residue-enriched peptide (KRKHPRRAQDSTKKPPSATRTSKTQRRRR) allowed a GFP-fusion protein to be transported and fully retained in the nucleolus. When the peptide was fused with cMyc epitope and expressed in the cells, amore » cMyc epitope was then detected in the nucleolus. Nop25 did not localize in the nucleolus by deletion of the peptide from Nop25. Furthermore, deletion of a subdomain (KRKHPRRAQ) in the peptide or amino acid substitution of lysine and arginine residues in the subdomain resulted in the loss of Nop25 nucleolar localization. These results suggest that the lysine and arginine residue-enriched peptide is the most prominent nucleolar targeting sequence of Nop25 and that the long stretch of basic residues might play an important role in the nucleolar localization of Nop25. Although Nop25 contained putative SUMOylation, phosphorylation and glycosylation sites, the amino acid substitution in these sites had no effect on the nucleolar localization, thus suggesting that these post-translational modifications did not contribute to the localization of Nop25 in the nucleolus. The treatment of the cells, which expressed a GFP-fusion protein with a nucleolar targeting sequence of Nop25, with RNase A resulted in a complete dislocation of the protein from the nucleolus. These data suggested that the nucleolar targeting sequence might therefore play an important role in the binding of Nop25 to RNA molecules and that the RNA binding of Nop25 might be essential for the nucleolar localization of Nop25.« less

TCRmodel: high resolution modeling of T cell receptors from sequence.

PubMed

Gowthaman, Ragul; Pierce, Brian G

2018-05-22

T cell receptors (TCRs), along with antibodies, are responsible for specific antigen recognition in the adaptive immune response, and millions of unique TCRs are estimated to be present in each individual. Understanding the structural basis of TCR targeting has implications in vaccine design, autoimmunity, as well as T cell therapies for cancer. Given advances in deep sequencing leading to immune repertoire-level TCR sequence data, fast and accurate modeling methods are needed to elucidate shared and unique 3D structural features of these molecules which lead to their antigen targeting and cross-reactivity. We developed a new algorithm in the program Rosetta to model TCRs from sequence, and implemented this functionality in a web server, TCRmodel. This web server provides an easy to use interface, and models are generated quickly that users can investigate in the browser and download. Benchmarking of this method using a set of nonredundant recently released TCR crystal structures shows that models are accurate and compare favorably to models from another available modeling method. This server enables the community to obtain insights into TCRs of interest, and can be combined with methods to model and design TCR recognition of antigens. The TCRmodel server is available at: http://tcrmodel.ibbr.umd.edu/.

Enzyme-triggered Gelation: Targeting Proteases with Internal Cleavage Sites

PubMed Central

Bremmer, Steven C.

2014-01-01

A generalizable method for detecting protease activity via gelation is described. A recognition sequence is used to target the protease of interest while a second protease is used to remove the residual residues from the gelator scaffold. Using this approach, selective assays for both MMP-9 and PSA are demonstrated. PMID:24394494

A Bioinformatic Pipeline for Monitoring of the Mutational Stability of Viral Drug Targets with Deep-Sequencing Technology.

PubMed

Kravatsky, Yuri; Chechetkin, Vladimir; Fedoseeva, Daria; Gorbacheva, Maria; Kravatskaya, Galina; Kretova, Olga; Tchurikov, Nickolai

2017-11-23

The efficient development of antiviral drugs, including efficient antiviral small interfering RNAs (siRNAs), requires continuous monitoring of the strict correspondence between a drug and the related highly variable viral DNA/RNA target(s). Deep sequencing is able to provide an assessment of both the general target conservation and the frequency of particular mutations in the different target sites. The aim of this study was to develop a reliable bioinformatic pipeline for the analysis of millions of short, deep sequencing reads corresponding to selected highly variable viral sequences that are drug target(s). The suggested bioinformatic pipeline combines the available programs and the ad hoc scripts based on an original algorithm of the search for the conserved targets in the deep sequencing data. We also present the statistical criteria for the threshold of reliable mutation detection and for the assessment of variations between corresponding data sets. These criteria are robust against the possible sequencing errors in the reads. As an example, the bioinformatic pipeline is applied to the study of the conservation of RNA interference (RNAi) targets in human immunodeficiency virus 1 (HIV-1) subtype A. The developed pipeline is freely available to download at the website http://virmut.eimb.ru/. Brief comments and comparisons between VirMut and other pipelines are also presented.

Experience of targeted Usher exome sequencing as a clinical test

PubMed Central

Besnard, Thomas; García-García, Gema; Baux, David; Vaché, Christel; Faugère, Valérie; Larrieu, Lise; Léonard, Susana; Millan, Jose M; Malcolm, Sue; Claustres, Mireille; Roux, Anne-Françoise

2014-01-01

We show that massively parallel targeted sequencing of 19 genes provides a new and reliable strategy for molecular diagnosis of Usher syndrome (USH) and nonsyndromic deafness, particularly appropriate for these disorders characterized by a high clinical and genetic heterogeneity and a complex structure of several of the genes involved. A series of 71 patients including Usher patients previously screened by Sanger sequencing plus newly referred patients was studied. Ninety-eight percent of the variants previously identified by Sanger sequencing were found by next-generation sequencing (NGS). NGS proved to be efficient as it offers analysis of all relevant genes which is laborious to reach with Sanger sequencing. Among the 13 newly referred Usher patients, both mutations in the same gene were identified in 77% of cases (10 patients) and one candidate pathogenic variant in two additional patients. This work can be considered as pilot for implementing NGS for genetically heterogeneous diseases in clinical service. PMID:24498627

EM connectomics reveals axonal target variation in a sequence-generating network

PubMed Central

Narayanan, Rajeevan T; Svara, Fabian; Egger, Robert; Oberlaender, Marcel; Denk, Winfried; Long, Michael A

2017-01-01

The sequential activation of neurons has been observed in various areas of the brain, but in no case is the underlying network structure well understood. Here we examined the circuit anatomy of zebra finch HVC, a cortical region that generates sequences underlying the temporal progression of the song. We combined serial block-face electron microscopy with light microscopy to determine the cell types targeted by HVC(RA) neurons, which control song timing. Close to their soma, axons almost exclusively targeted inhibitory interneurons, consistent with what had been found with electrical recordings from pairs of cells. Conversely, far from the soma the targets were mostly other excitatory neurons, about half of these being other HVC(RA) cells. Both observations are consistent with the notion that the neural sequences that pace the song are generated by global synaptic chains in HVC embedded within local inhibitory networks. DOI: http://dx.doi.org/10.7554/eLife.24364.001 PMID:28346140

A statistical approach to detection of copy number variations in PCR-enriched targeted sequencing data.

PubMed

Demidov, German; Simakova, Tamara; Vnuchkova, Julia; Bragin, Anton

2016-10-22

Multiplex polymerase chain reaction (PCR) is a common enrichment technique for targeted massive parallel sequencing (MPS) protocols. MPS is widely used in biomedical research and clinical diagnostics as the fast and accurate tool for the detection of short genetic variations. However, identification of larger variations such as structure variants and copy number variations (CNV) is still being a challenge for targeted MPS. Some approaches and tools for structural variants detection were proposed, but they have limitations and often require datasets of certain type, size and expected number of amplicons affected by CNVs. In the paper, we describe novel algorithm for high-resolution germinal CNV detection in the PCR-enriched targeted sequencing data and present accompanying tool. We have developed a machine learning algorithm for the detection of large duplications and deletions in the targeted sequencing data generated with PCR-based enrichment step. We have performed verification studies and established the algorithm's sensitivity and specificity. We have compared developed tool with other available methods applicable for the described data and revealed its higher performance. We showed that our method has high specificity and sensitivity for high-resolution copy number detection in targeted sequencing data using large cohort of samples.

SAR target recognition using behaviour library of different shapes in different incidence angles and polarisations

NASA Astrophysics Data System (ADS)

Fallahpour, Mojtaba Behzad; Dehghani, Hamid; Jabbar Rashidi, Ali; Sheikhi, Abbas

2018-05-01

Target recognition is one of the most important issues in the interpretation of the synthetic aperture radar (SAR) images. Modelling, analysis, and recognition of the effects of influential parameters in the SAR can provide a better understanding of the SAR imaging systems, and therefore facilitates the interpretation of the produced images. Influential parameters in SAR images can be divided into five general categories of radar, radar platform, channel, imaging region, and processing section, each of which has different physical, structural, hardware, and software sub-parameters with clear roles in the finally formed images. In this paper, for the first time, a behaviour library that includes the effects of polarisation, incidence angle, and shape of targets, as radar and imaging region sub-parameters, in the SAR images are extracted. This library shows that the created pattern for each of cylindrical, conical, and cubic shapes is unique, and due to their unique properties these types of shapes can be recognised in the SAR images. This capability is applied to data acquired with the Canadian RADARSAT1 satellite.

A bottom-up model of spatial attention predicts human error patterns in rapid scene recognition.

PubMed

Einhäuser, Wolfgang; Mundhenk, T Nathan; Baldi, Pierre; Koch, Christof; Itti, Laurent

2007-07-20

Humans demonstrate a peculiar ability to detect complex targets in rapidly presented natural scenes. Recent studies suggest that (nearly) no focal attention is required for overall performance in such tasks. Little is known, however, of how detection performance varies from trial to trial and which stages in the processing hierarchy limit performance: bottom-up visual processing (attentional selection and/or recognition) or top-down factors (e.g., decision-making, memory, or alertness fluctuations)? To investigate the relative contribution of these factors, eight human observers performed an animal detection task in natural scenes presented at 20 Hz. Trial-by-trial performance was highly consistent across observers, far exceeding the prediction of independent errors. This consistency demonstrates that performance is not primarily limited by idiosyncratic factors but by visual processing. Two statistical stimulus properties, contrast variation in the target image and the information-theoretical measure of "surprise" in adjacent images, predict performance on a trial-by-trial basis. These measures are tightly related to spatial attention, demonstrating that spatial attention and rapid target detection share common mechanisms. To isolate the causal contribution of the surprise measure, eight additional observers performed the animal detection task in sequences that were reordered versions of those all subjects had correctly recognized in the first experiment. Reordering increased surprise before and/or after the target while keeping the target and distractors themselves unchanged. Surprise enhancement impaired target detection in all observers. Consequently, and contrary to several previously published findings, our results demonstrate that attentional limitations, rather than target recognition alone, affect the detection of targets in rapidly presented visual sequences.

Pattern-Recognition System for Approaching a Known Target

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance; Cheng, Yang

2008-01-01

A closed-loop pattern-recognition system is designed to provide guidance for maneuvering a small exploratory robotic vehicle (rover) on Mars to return to a landed spacecraft to deliver soil and rock samples that the spacecraft would subsequently bring back to Earth. The system could be adapted to terrestrial use in guiding mobile robots to approach known structures that humans could not approach safely, for such purposes as reconnaissance in military or law-enforcement applications, terrestrial scientific exploration, and removal of explosive or other hazardous items. The system has been demonstrated in experiments in which the Field Integrated Design and Operations (FIDO) rover (a prototype Mars rover equipped with a video camera for guidance) is made to return to a mockup of Mars-lander spacecraft. The FIDO rover camera autonomously acquires an image of the lander from a distance of 125 m in an outdoor environment. Then under guidance by an algorithm that performs fusion of multiple line and texture features in digitized images acquired by the camera, the rover traverses the intervening terrain, using features derived from images of the lander truss structure. Then by use of precise pattern matching for determining the position and orientation of the rover relative to the lander, the rover aligns itself with the bottom of ramps extending from the lander, in preparation for climbing the ramps to deliver samples to the lander. The most innovative aspect of the system is a set of pattern-recognition algorithms that govern a three-phase visual-guidance sequence for approaching the lander. During the first phase, a multifeature fusion algorithm integrates the outputs of a horizontal-line-detection algorithm and a wavelet-transform-based visual-area-of-interest algorithm for detecting the lander from a significant distance. The horizontal-line-detection algorithm is used to determine candidate lander locations based on detection of a horizontal deck that is part of the

In vivo gene correction with targeted sequence substitution through microhomology-mediated end joining.

PubMed

Shin, Jeong Hong; Jung, Soobin; Ramakrishna, Suresh; Kim, Hyongbum Henry; Lee, Junwon

2018-07-07

Genome editing technology using programmable nucleases has rapidly evolved in recent years. The primary mechanism to achieve precise integration of a transgene is mainly based on homology-directed repair (HDR). However, an HDR-based genome-editing approach is less efficient than non-homologous end-joining (NHEJ). Recently, a microhomology-mediated end-joining (MMEJ)-based transgene integration approach was developed, showing feasibility both in vitro and in vivo. We expanded this method to achieve targeted sequence substitution (TSS) of mutated sequences with normal sequences using double-guide RNAs (gRNAs), and a donor template flanking the microhomologies and target sequence of the gRNAs in vitro and in vivo. Our method could realize more efficient sequence substitution than the HDR-based method in vitro using a reporter cell line, and led to the survival of a hereditary tyrosinemia mouse model in vivo. The proposed MMEJ-based TSS approach could provide a novel therapeutic strategy, in addition to HDR, to achieve gene correction from a mutated sequence to a normal sequence. Copyright © 2018 Elsevier Inc. All rights reserved.

Biosensors for DNA sequence detection

NASA Technical Reports Server (NTRS)

Vercoutere, Wenonah; Akeson, Mark

2002-01-01

DNA biosensors are being developed as alternatives to conventional DNA microarrays. These devices couple signal transduction directly to sequence recognition. Some of the most sensitive and functional technologies use fibre optics or electrochemical sensors in combination with DNA hybridization. In a shift from sequence recognition by hybridization, two emerging single-molecule techniques read sequence composition using zero-mode waveguides or electrical impedance in nanoscale pores.

Pattern recognition of the targets with help of polarization properties of the signal

NASA Astrophysics Data System (ADS)

Ponomaryov, Volodymyr I.; de Rivera, Luis N.; Castellanos, Aldo B.; Popov, Anatoly V.

1999-10-01

We proposed to use the possibility of recognition of the targets on background of the scattering from the surface, weather objects with the help of polarimetric 3-cm radar. It has been investigated such polarization characteristics: the amplitudes of the polarization matrix elements; an anisotropy coefficient; depolarization coefficient; asymmetry coefficient; the energy section was less than 1 dB at ranges up to 15 km and less than 1.5 dB at ranges up to 100 km. During the experiments urban objects and 6 various ships of small displacement having the closest values of the backscattering cross-section were used. The analysis has shown: the factor of the polarization selection for anisotropy objects and weather objects had the values about 0.02-0.08 Isotropy had the values of polarimetric correlation factor for hydrometers about 0.7-0.8, for earth surface about 0.8-0.9, for sea surface - from 0.33 to 0.7. The results of the work of recognition algorithm of a class 'concrete objects', and 'metal objects' are submitted as example in the paper. The result of experiments have shown that the probability of correct recognition of the identified objects was in the limits from 0.93 to 0.97.

Action Recognition in a Crowded Environment

PubMed Central

Nieuwenhuis, Judith; Bülthoff, Isabelle; Barraclough, Nick; de la Rosa, Stephan

2017-01-01

So far, action recognition has been mainly examined with small point-light human stimuli presented alone within a narrow central area of the observer’s visual field. Yet, we need to recognize the actions of life-size humans viewed alone or surrounded by bystanders, whether they are seen in central or peripheral vision. Here, we examined the mechanisms in central vision and far periphery (40° eccentricity) involved in the recognition of the actions of a life-size actor (target) and their sensitivity to the presence of a crowd surrounding the target. In Experiment 1, we used an action adaptation paradigm to probe whether static or idly moving crowds might interfere with the recognition of a target’s action (hug or clap). We found that this type of crowds whose movements were dissimilar to the target action hardly affected action recognition in central and peripheral vision. In Experiment 2, we examined whether crowd actions that were more similar to the target actions affected action recognition. Indeed, the presence of that crowd diminished adaptation aftereffects in central vision as wells as in the periphery. We replicated Experiment 2 using a recognition task instead of an adaptation paradigm. With this task, we found evidence of decreased action recognition accuracy, but this was significant in peripheral vision only. Our results suggest that the presence of a crowd carrying out actions similar to that of the target affects its recognition. We outline how these results can be understood in terms of high-level crowding effects that operate on action-sensitive perceptual channels. PMID:29308177

Noninvasive Prenatal Detection of Trisomy 21 by Targeted Semiconductor Sequencing: A Technical Feasibility Study.

PubMed

Xi, Yanwei; Arbabi, Aryan; McNaughton, Amy J M; Hamilton, Alison; Hull, Danna; Perras, Helene; Chiu, Tillie; Morrison, Shawna; Goldsmith, Claire; Creede, Emilie; Anger, Gregory J; Honeywell, Christina; Cloutier, Mireille; Macchio, Natasha; Kiss, Courtney; Liu, Xudong; Crocker, Susan; Davies, Gregory A; Brudno, Michael; Armour, Christine M

2017-01-01

To develop an alternate noninvasive prenatal testing method for the assessment of trisomy 21 (T21) using a targeted semiconductor sequencing approach. A customized AmpliSeq panel was designed with 1,067 primer pairs targeting specific regions on chromosomes 21, 18, 13, and others. A total of 235 samples, including 30 affected with T21, were sequenced with an Ion Torrent Proton sequencer, and a method was developed for assessing the probability of fetal aneuploidy via derivation of a risk score. Application of the derived risk score yields a bimodal distribution, with the affected samples clustering near 1.0 and the unaffected near 0. For a risk score cutoff of 0.345, above which all would be considered at "high risk," all 30 T21-positive pregnancies were correctly predicted to be affected, and 199 of the 205 non-T21 samples were correctly predicted. The average hands-on time spent on library preparation and sequencing was 19 h in total, and the average number of reads of sequence obtained was 3.75 million per sample. With the described targeted sequencing approach on the semiconductor platform using a custom-designed library and a probabilistic statistical approach, we have demonstrated the feasibility of an alternate method of assessment for fetal T21. © 2017 S. Karger AG, Basel.

DNA recognition by an RNA-guided bacterial Argonaute

PubMed Central

Doudna, Jennifer A.

2017-01-01

Argonaute (Ago) proteins are widespread in prokaryotes and eukaryotes and share a four-domain architecture capable of RNA- or DNA-guided nucleic acid recognition. Previous studies identified a prokaryotic Argonaute protein from the eubacterium Marinitoga piezophila (MpAgo), which binds preferentially to 5′-hydroxylated guide RNAs and cleaves single-stranded RNA (ssRNA) and DNA (ssDNA) targets. Here we present a 3.2 Å resolution crystal structure of MpAgo bound to a 21-nucleotide RNA guide and a complementary 21-nucleotide ssDNA substrate. Comparison of this ternary complex to other target-bound Argonaute structures reveals a unique orientation of the N-terminal domain, resulting in a straight helical axis of the entire RNA-DNA heteroduplex through the central cleft of the protein. Additionally, mismatches introduced into the heteroduplex reduce MpAgo cleavage efficiency with a symmetric profile centered around the middle of the helix. This pattern differs from the canonical mismatch tolerance of other Argonautes, which display decreased cleavage efficiency for substrates bearing sequence mismatches to the 5′ region of the guide strand. This structural analysis of MpAgo bound to a hybrid helix advances our understanding of the diversity of target recognition mechanisms by Argonaute proteins. PMID:28520746

Target recognition for ladar range image using slice image

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Wang, Liang

2015-12-01

A shape descriptor and a complete shape-based recognition system using slice images as geometric feature descriptor for ladar range images are introduced. A slice image is a two-dimensional image generated by three-dimensional Hough transform and the corresponding mathematical transformation. The system consists of two processes, the model library construction and recognition. In the model library construction process, a series of range images are obtained after the model object is sampled at preset attitude angles. Then, all the range images are converted into slice images. The number of slice images is reduced by clustering analysis and finding a representation to reduce the size of the model library. In the recognition process, the slice image of the scene is compared with the slice image in the model library. The recognition results depend on the comparison. Simulated ladar range images are used to analyze the recognition and misjudgment rates, and comparison between the slice image representation method and moment invariants representation method is performed. The experimental results show that whether in conditions without noise or with ladar noise, the system has a high recognition rate and low misjudgment rate. The comparison experiment demonstrates that the slice image has better representation ability than moment invariants.

PDNAsite: Identification of DNA-binding Site from Protein Sequence by Incorporating Spatial and Sequence Context

PubMed Central

Zhou, Jiyun; Xu, Ruifeng; He, Yulan; Lu, Qin; Wang, Hongpeng; Kong, Bing

2016-01-01

Protein-DNA interactions are involved in many fundamental biological processes essential for cellular function. Most of the existing computational approaches employed only the sequence context of the target residue for its prediction. In the present study, for each target residue, we applied both the spatial context and the sequence context to construct the feature space. Subsequently, Latent Semantic Analysis (LSA) was applied to remove the redundancies in the feature space. Finally, a predictor (PDNAsite) was developed through the integration of the support vector machines (SVM) classifier and ensemble learning. Results on the PDNA-62 and the PDNA-224 datasets demonstrate that features extracted from spatial context provide more information than those from sequence context and the combination of them gives more performance gain. An analysis of the number of binding sites in the spatial context of the target site indicates that the interactions between binding sites next to each other are important for protein-DNA recognition and their binding ability. The comparison between our proposed PDNAsite method and the existing methods indicate that PDNAsite outperforms most of the existing methods and is a useful tool for DNA-binding site identification. A web-server of our predictor (http://hlt.hitsz.edu.cn:8080/PDNAsite/) is made available for free public accessible to the biological research community. PMID:27282833

Molecular characterization of oral squamous cell carcinoma using targeted next-generation sequencing.

PubMed

Er, Tze-Kiong; Wang, Yen-Yun; Chen, Chih-Chieh; Herreros-Villanueva, Marta; Liu, Ta-Chih; Yuan, Shyng-Shiou F

2015-10-01

Many genetic factors play an important role in the development of oral squamous cell carcinoma. The aim of this study was to assess the mutational profile in oral squamous cell carcinoma using formalin-fixed, paraffin-embedded tumors from a Taiwanese population by performing targeted sequencing of 26 cancer-associated genes that are frequently mutated in solid tumors. Next-generation sequencing was performed in 50 formalin-fixed, paraffin-embedded tumor specimens obtained from patients with oral squamous cell carcinoma. Genetic alterations in the 26 cancer-associated genes were detected using a deep sequencing (>1000X) approach. TP53, PIK3CA, MET, APC, CDH1, and FBXW7 were most frequently mutated genes. Most remarkably, TP53 mutations and PIK3CA mutations, which accounted for 68% and 18% of tumors, respectively, were more prevalent in a Taiwanese population. Other genes including MET (4%), APC (4%), CDH1 (2%), and FBXW7 (2%) were identified in our population. In summary, our study shows the feasibility of performing targeted sequencing using formalin-fixed, paraffin-embedded samples. Additionally, this study also reports the mutational landscape of oral squamous cell carcinoma in the Taiwanese population. We believe that this study will shed new light on fundamental aspects in understanding the molecular pathogenesis of oral squamous cell carcinoma and may aid in the development of new targeted therapies. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Single-Stranded γPNAs for In Vivo Site-Specific Genome Editing via Watson-Crick Recognition

PubMed Central

Bahal, Raman; Quijano, Elias; McNeer, Nicole Ali; Liu, Yanfeng; Bhunia, Dinesh C.; López-Giráldez, Francesco; Fields, Rachel J.; Saltzman, W. Mark; Ly, Danith H.; Glazer, Peter M.

2014-01-01

Triplex-forming peptide nucleic acids (PNAs) facilitate gene editing by stimulating recombination of donor DNAs within genomic DNA via site-specific formation of altered helical structures that further stimulate DNA repair. However, PNAs designed for triplex formation are sequence restricted to homopurine sites. Herein we describe a novel strategy where next generation single-stranded gamma PNAs (γPNAs) containing miniPEG substitutions at the gamma position can target genomic DNA in mouse bone marrow at mixed-sequence sites to induce targeted gene editing. In addition to enhanced binding, γPNAs confer increased solubility and improved formulation into poly(lactic-co-glycolic acid) (PLGA) nanoparticles for efficient intracellular delivery. Single-stranded γPNAs induce targeted gene editing at frequencies of 0.8% in mouse bone marrow cells treated ex vivo and 0.1% in vivo via IV injection, without detectable toxicity. These results suggest that γPNAs may provide a new tool for induced gene editing based on Watson-Crick recognition without sequence restriction. PMID:25174576

Single-stranded γPNAs for in vivo site-specific genome editing via Watson-Crick recognition.

PubMed

Bahal, Raman; Quijano, Elias; McNeer, Nicole A; Liu, Yanfeng; Bhunia, Dinesh C; Lopez-Giraldez, Francesco; Fields, Rachel J; Saltzman, William M; Ly, Danith H; Glazer, Peter M

2014-01-01

Triplex-forming peptide nucleic acids (PNAs) facilitate gene editing by stimulating recombination of donor DNAs within genomic DNA via site-specific formation of altered helical structures that further stimulate DNA repair. However, PNAs designed for triplex formation are sequence restricted to homopurine sites. Herein we describe a novel strategy where next generation single-stranded gamma PNAs (γPNAs) containing miniPEG substitutions at the gamma position can target genomic DNA in mouse bone marrow at mixed-sequence sites to induce targeted gene editing. In addition to enhanced binding, γPNAs confer increased solubility and improved formulation into poly(lactic-co-glycolic acid) (PLGA) nanoparticles for efficient intracellular delivery. Single-stranded γPNAs induce targeted gene editing at frequencies of 0.8% in mouse bone marrow cells treated ex vivo and 0.1% in vivo via IV injection, without detectable toxicity. These results suggest that γPNAs may provide a new tool for induced gene editing based on Watson-Crick recognition without sequence restriction.

Target recognition based on the moment functions of radar signatures

NASA Astrophysics Data System (ADS)

Kim, Kyung-Tae; Kim, Hyo-Tae

2002-03-01

In this paper, we present the results of target recognition research based on the moment functions of various radar signatures, such as time-frequency signatures, range profiles, and scattering centers. The proposed approach utilizes geometrical moments or central moments of the obtained radar signatures. In particular, we derived exact and closed form expressions of the geometrical moments of the adaptive Gaussian representation (AGR), which is one of the adaptive joint time-frequency techniques, and also computed the central moments of range profiles and one-dimensional (1-D) scattering centers on a target, which are obtained by various super-resolution techniques. The obtained moment functions are further processed to provide small dimensional and redundancy-free feature vectors, and classified via a neural network approach or a Bayes classifier. The performances of the proposed technique are demonstrated using a simulated radar cross section (RCS) data set, or a measured RCS data set of various scaled aircraft models, obtained at the Pohang University of Science and Technology (POSTECH) compact range facility. Results show that the techniques in this paper can not only provide reliable classification accuracy, but also save computational resources.

High-accuracy and robust face recognition system based on optical parallel correlator using a temporal image sequence

NASA Astrophysics Data System (ADS)

Watanabe, Eriko; Ishikawa, Mami; Ohta, Maiko; Kodate, Kashiko

2005-09-01

Face recognition is used in a wide range of security systems, such as monitoring credit card use, searching for individuals with street cameras via Internet and maintaining immigration control. There are still many technical subjects under study. For instance, the number of images that can be stored is limited under the current system, and the rate of recognition must be improved to account for photo shots taken at different angles under various conditions. We implemented a fully automatic Fast Face Recognition Optical Correlator (FARCO) system by using a 1000 frame/s optical parallel correlator designed and assembled by us. Operational speed for the 1: N (i.e. matching a pair of images among N, where N refers to the number of images in the database) identification experiment (4000 face images) amounts to less than 1.5 seconds, including the pre/post processing. From trial 1: N identification experiments using FARCO, we acquired low error rates of 2.6% False Reject Rate and 1.3% False Accept Rate. By making the most of the high-speed data-processing capability of this system, much more robustness can be achieved for various recognition conditions when large-category data are registered for a single person. We propose a face recognition algorithm for the FARCO while employing a temporal image sequence of moving images. Applying this algorithm to a natural posture, a two times higher recognition rate scored compared with our conventional system. The system has high potential for future use in a variety of purposes such as search for criminal suspects by use of street and airport video cameras, registration of babies at hospitals or handling of an immeasurable number of images in a database.

Discovery of Influenza A Virus Sequence Pairs and Their Combinations for Simultaneous Heterosubtypic Targeting that Hedge against Antiviral Resistance

PubMed Central

Lin, Jing; Pramono, Zacharias Aloysius Dwi; Maurer-Stroh, Sebastian

2016-01-01

The multiple circulating human influenza A virus subtypes coupled with the perpetual genomic mutations and segment reassortment events challenge the development of effective therapeutics. The capacity to drug most RNAs motivates the investigation on viral RNA targets. 123,060 segment sequences from 35,938 strains of the most prevalent subtypes also infecting humans–H1N1, 2009 pandemic H1N1, H3N2, H5N1 and H7N9, were used to identify 1,183 conserved RNA target sequences (≥15-mer) in the internal segments. 100% theoretical coverage in simultaneous heterosubtypic targeting is achieved by pairing specific sequences from the same segment (“Duals”) or from two segments (“Doubles”); 1,662 Duals and 28,463 Doubles identified. By combining specific Duals and/or Doubles to form a target graph wherein an edge connecting two vertices (target sequences) represents a Dual or Double, it is possible to hedge against antiviral resistance besides maintaining 100% heterosubtypic coverage. To evaluate the hedging potential, we define the hedge-factor as the minimum number of resistant target sequences that will render the graph to become resistant i.e. eliminate all the edges therein; a target sequence or a graph is considered resistant when it cannot achieve 100% heterosubtypic coverage. In an n-vertices graph (n ≥ 3), the hedge-factor is maximal (= n– 1) when it is a complete graph i.e. every distinct pair in a graph is either a Dual or Double. Computational analyses uncover an extensive number of complete graphs of different sizes. Monte Carlo simulations show that the mutation counts and time elapsed for a target graph to become resistant increase with the hedge-factor. Incidentally, target sequences which were reported to reduce virus titre in experiments are included in our target graphs. The identity of target sequence pairs for heterosubtypic targeting and their combinations for hedging antiviral resistance are useful toolkits to construct target graphs for

Fine tuning cellular recognition: The function of the leucine rich repeat (LRR) trans-membrane protein, LRT, in muscle targeting to tendon cells.

PubMed

Gilsohn, Eli; Volk, Talila

2010-01-01

The formation of complex tissues during embryonic development is often accompanied by directed cellular migration towards a target tissue. Specific mutual recognition between the migrating cell and its target tissue leads to the arrest of the cell migratory behavior and subsequent contact formation between the two interacting cell types. Recent studies implicated a novel family of surface proteins containing a trans-membrane domain and single leucine-rich repeat (LRR) domain in inter-cellular recognition and the arrest of cell migration. Here, we describe the involvement of a novel LRR surface protein, LRT, in targeting migrating muscles towards their corresponding tendon cells in the Drosophila embryo. LRT is specifically expressed by the target tendon cells and is essential for arresting the migratory behavior of the muscle cells. Additional studies in Drosophila S2 cultured cells suggest that LRT forms a protein complex with the Roundabout (Robo) receptor, essential for guiding muscles towards their tendon partners. Genetic analysis supports a model in which LRT performs its activity non-autonomously through its interaction with the Robo receptors expressed on the muscle surfaces. These results suggest a novel mechanism of intercellular recognition through interactions between LRR family members and Robo receptors.

Robust Small Target Co-Detection from Airborne Infrared Image Sequences.

PubMed

Gao, Jingli; Wen, Chenglin; Liu, Meiqin

2017-09-29

In this paper, a novel infrared target co-detection model combining the self-correlation features of backgrounds and the commonality features of targets in the spatio-temporal domain is proposed to detect small targets in a sequence of infrared images with complex backgrounds. Firstly, a dense target extraction model based on nonlinear weights is proposed, which can better suppress background of images and enhance small targets than weights of singular values. Secondly, a sparse target extraction model based on entry-wise weighted robust principal component analysis is proposed. The entry-wise weight adaptively incorporates structural prior in terms of local weighted entropy, thus, it can extract real targets accurately and suppress background clutters efficiently. Finally, the commonality of targets in the spatio-temporal domain are used to construct target refinement model for false alarms suppression and target confirmation. Since real targets could appear in both of the dense and sparse reconstruction maps of a single frame, and form trajectories after tracklet association of consecutive frames, the location correlation of the dense and sparse reconstruction maps for a single frame and tracklet association of the location correlation maps for successive frames have strong ability to discriminate between small targets and background clutters. Experimental results demonstrate that the proposed small target co-detection method can not only suppress background clutters effectively, but also detect targets accurately even if with target-like interference.

The minimal amount of starting DNA for Agilent’s hybrid capture-based targeted massively parallel sequencing

PubMed Central

Chung, Jongsuk; Son, Dae-Soon; Jeon, Hyo-Jeong; Kim, Kyoung-Mee; Park, Gahee; Ryu, Gyu Ha; Park, Woong-Yang; Park, Donghyun

2016-01-01

Targeted capture massively parallel sequencing is increasingly being used in clinical settings, and as costs continue to decline, use of this technology may become routine in health care. However, a limited amount of tissue has often been a challenge in meeting quality requirements. To offer a practical guideline for the minimum amount of input DNA for targeted sequencing, we optimized and evaluated the performance of targeted sequencing depending on the input DNA amount. First, using various amounts of input DNA, we compared commercially available library construction kits and selected Agilent’s SureSelect-XT and KAPA Biosystems’ Hyper Prep kits as the kits most compatible with targeted deep sequencing using Agilent’s SureSelect custom capture. Then, we optimized the adapter ligation conditions of the Hyper Prep kit to improve library construction efficiency and adapted multiplexed hybrid selection to reduce the cost of sequencing. In this study, we systematically evaluated the performance of the optimized protocol depending on the amount of input DNA, ranging from 6.25 to 200 ng, suggesting the minimal input DNA amounts based on coverage depths required for specific applications. PMID:27220682

CRISPR-Cas9 nuclear dynamics and target recognition in living cells

PubMed Central

Ma, Hanhui; Tu, Li-Chun; Zhang, Shaojie; Grunwald, David

2016-01-01

The bacterial CRISPR-Cas9 system has been repurposed for genome engineering, transcription modulation, and chromosome imaging in eukaryotic cells. However, the nuclear dynamics of clustered regularly interspaced short palindromic repeats (CRISPR)–associated protein 9 (Cas9) guide RNAs and target interrogation are not well defined in living cells. Here, we deployed a dual-color CRISPR system to directly measure the stability of both Cas9 and guide RNA. We found that Cas9 is essential for guide RNA stability and that the nuclear Cas9–guide RNA complex levels limit the targeting efficiency. Fluorescence recovery after photobleaching measurements revealed that single mismatches in the guide RNA seed sequence reduce the target residence time from >3 h to as low as <2 min in a nucleotide identity- and position-dependent manner. We further show that the duration of target residence correlates with cleavage activity. These results reveal that CRISPR discriminates between genuine versus mismatched targets for genome editing via radical alterations in residence time. PMID:27551060

Modeling side-chains using molecular dynamics improve recognition of binding region in CAPRI targets.

PubMed

Camacho, Carlos J

2005-08-01

The CAPRI-II experiment added an extra level of complexity to the problem of predicting protein-protein interactions by including 5 targets for which participants had to build or complete the 3-dimensional (3D) structure of either the receptor or ligand based on the structure of a close homolog. In this article, we describe how modeling key side-chains using molecular dynamics (MD) in explicit solvent improved the recognition of the binding region of a free energy- based computational docking method. In particular, we show that MD is able to predict with relatively high accuracy the rotamer conformation of the anchor side-chains important for molecular recognition as suggested by Rajamani et al. (Proc Natl Acad Sci USA 2004;101:11287-11292). As expected, the conformations are some of the most common rotamers for the given residue, while latch side-chains that undergo induced fit upon binding are forced into less common conformations. Using these models as starting conformations in conjunction with the rigid-body docking server ClusPro and the flexible docking algorithm SmoothDock, we produced valuable predictions for 6 of the 9 targets in CAPRI-II, missing only the 3 targets that underwent significant structural rearrangements upon binding. We also show that our free energy- based scoring function, consisting of the sum of van der Waals, Coulombic electrostatic with a distance-dependent dielectric, and desolvation free energy successfully discriminates the nativelike conformation of our submitted predictions. The latter emphasizes the critical role that thermodynamics plays on our methodology, and validates the generality of the algorithm to predict protein interactions.

Detection of Somatic Mutations in Gastroenteropancreatic Neuroendocrine Tumors Using Targeted Deep Sequencing.

PubMed

Backman, Samuel; Norlén, Olov; Eriksson, Barbro; Skogseid, Britt; Stålberg, Peter; Crona, Joakim

2017-02-01

Mutations affecting the mechanistic target of rapamycin (MTOR) signalling pathway are frequent in human cancer and have been identified in up to 15% of pancreatic neuroendocrine tumours (NETs). Grade A evidence supports the efficacy of MTOR inhibition with everolimus in pancreatic NETs. Although a significant proportion of patients experience disease stabilization, only a minority will show objective tumour responses. It has been proposed that genomic mutations resulting in activation of MTOR signalling could be used to predict sensitivity to everolimus. Patients with NETs that underwent treatment with everolimus at our Institution were identified and those with available tumour tissue were selected for further analysis. Targeted next-generation sequencing (NGS) was used to re-sequence 22 genes that were selected on the basis of documented involvement in the MTOR signalling pathway or in the tumourigenesis of gastroenterpancreatic NETs. Radiological responses were documented using Response Evaluation Criteria in Solid Tumours. Six patients were identified, one had a partial response and four had stable disease. Sequencing of tumour tissue resulted in a median sequence depth of 667.1 (range=404-1301) with 1-fold coverage of 95.9-96.5% and 10-fold coverage of 87.6-92.2%. A total of 494 genetic variants were discovered, four of which were identified as pathogenic. All pathogenic variants were validated using Sanger sequencing and were found exclusively in menin 1 (MEN1) and death domain associated protein (DAXX) genes. No mutations in the MTOR pathway-related genes were observed. Targeted NGS is a feasible method with high diagnostic yield for genetic characterization of pancreatic NETs. A potential association between mutations in NETs and response to everolimus should be investigated by future studies. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Perceptual fluency and affect without recognition.

PubMed

Anand, P; Sternthal, B

1991-05-01

A dichotic listening task was used to investigate the affect-without-recognition phenomenon. Subjects performed a distractor task by responding to the information presented in one ear while ignoring the target information presented in the other ear. The subjects' recognition of and affect toward the target information as well as toward foils was measured. The results offer evidence for the affect-without-recognition phenomenon. Furthermore, the data suggest that the subjects' affect toward the stimuli depended primarily on the extent to which the stimuli were perceived as familiar (i.e., subjective familiarity), and this perception was influenced by the ear in which the distractor or the target information was presented. These data are interpreted in terms of current models of recognition memory and hemispheric lateralization.

'2A-Like' Signal Sequences Mediating Translational Recoding: A Novel Form of Dual Protein Targeting.

PubMed

Roulston, Claire; Luke, Garry A; de Felipe, Pablo; Ruan, Lin; Cope, Jonathan; Nicholson, John; Sukhodub, Andriy; Tilsner, Jens; Ryan, Martin D

2016-08-01

We report the initial characterization of an N-terminal oligopeptide '2A-like' sequence that is able to function both as a signal sequence and as a translational recoding element. Owing to this translational recoding activity, two forms of nascent polypeptide are synthesized: (i) when 2A-mediated translational recoding has not occurred: the nascent polypeptide is fused to the 2A-like N-terminal signal sequence and the fusion translation product is targeted to the exocytic pathway, and, (ii) a translation product where 2A-mediated translational recoding has occurred: the 2A-like signal sequence is synthesized as a separate translation product and, therefore, the nascent (downstream) polypeptide lacks the 2A-like signal sequence and is localized to the cytoplasm. This type of dual-functional signal sequence results, therefore, in the partitioning of the translation products between the two sub-cellular sites and represents a newly described form of dual protein targeting. © 2016 The Authors. Traffic published by John Wiley & Sons Ltd.

Research on application of LADAR in ground vehicle recognition

NASA Astrophysics Data System (ADS)

Lan, Jinhui; Shen, Zhuoxun

2009-11-01

For the requirement of many practical applications in the field of military, the research of 3D target recognition is active. The representation that captures the salient attributes of a 3D target independent of the viewing angle will be especially useful to the automatic 3D target recognition system. This paper presents a new approach of image generation based on Laser Detection and Ranging (LADAR) data. Range image of target is obtained by transformation of point cloud. In order to extract features of different ground vehicle targets and to recognize targets, zernike moment properties of typical ground vehicle targets are researched in this paper. A technique of support vector machine is applied to the classification and recognition of target. The new method of image generation and feature representation has been applied to the outdoor experiments. Through outdoor experiments, it can be proven that the method of image generation is stability, the moments are effective to be used as features for recognition, and the LADAR can be applied to the field of 3D target recognition.

Performance evaluation of Sanger sequencing for the diagnosis of primary hyperoxaluria and comparison with targeted next generation sequencing

PubMed Central

Williams, Emma L; Bagg, Eleanor A L; Mueller, Michael; Vandrovcova, Jana; Aitman, Timothy J; Rumsby, Gill

2015-01-01

Definitive diagnosis of primary hyperoxaluria (PH) currently utilizes sequential Sanger sequencing of the AGXT, GRPHR, and HOGA1 genes but efficacy is unproven. This analysis is time-consuming, relatively expensive, and delays in diagnosis and inappropriate treatment can occur if not pursued early in the diagnostic work-up. We reviewed testing outcomes of Sanger sequencing in 200 consecutive patient samples referred for analysis. In addition, the Illumina Truseq custom amplicon system was evaluated for paralleled next-generation sequencing (NGS) of AGXT,GRHPR, and HOGA1 in 90 known PH patients. AGXT sequencing was requested in all patients, permitting a diagnosis of PH1 in 50%. All remaining patients underwent targeted exon sequencing of GRHPR and HOGA1 with 8% diagnosed with PH2 and 8% with PH3. Complete sequencing of both GRHPR and HOGA1 was not requested in 25% of patients referred leaving their diagnosis in doubt. NGS analysis showed 98% agreement with Sanger sequencing and both approaches had 100% diagnostic specificity. Diagnostic sensitivity of Sanger sequencing was 98% and for NGS it was 97%. NGS has comparable diagnostic performance to Sanger sequencing for the diagnosis of PH and, if implemented, would screen for all forms of PH simultaneously ensuring prompt diagnosis at decreased cost. PMID:25629080

A conserved mechanism for replication origin recognition and binding in archaea.

PubMed

Majerník, Alan I; Chong, James P J

2008-01-15

To date, methanogens are the only group within the archaea where firing DNA replication origins have not been demonstrated in vivo. In the present study we show that a previously identified cluster of ORB (origin recognition box) sequences do indeed function as an origin of replication in vivo in the archaeon Methanothermobacter thermautotrophicus. Although the consensus sequence of ORBs in M. thermautotrophicus is somewhat conserved when compared with ORB sequences in other archaea, the Cdc6-1 protein from M. thermautotrophicus (termed MthCdc6-1) displays sequence-specific binding that is selective for the MthORB sequence and does not recognize ORBs from other archaeal species. Stabilization of in vitro MthORB DNA binding by MthCdc6-1 requires additional conserved sequences 3' to those originally described for M. thermautotrophicus. By testing synthetic sequences bearing mutations in the MthORB consensus sequence, we show that Cdc6/ORB binding is critically dependent on the presence of an invariant guanine found in all archaeal ORB sequences. Mutation of a universally conserved arginine residue in the recognition helix of the winged helix domain of archaeal Cdc6-1 shows that specific origin sequence recognition is dependent on the interaction of this arginine residue with the invariant guanine. Recognition of a mutated origin sequence can be achieved by mutation of the conserved arginine residue to a lysine or glutamine residue. Thus despite a number of differences in protein and DNA sequences between species, the mechanism of origin recognition and binding appears to be conserved throughout the archaea.

Recognition Tunneling

PubMed Central

Lindsay, Stuart; He, Jin; Sankey, Otto; Hapala, Prokop; Jelinek, Pavel; Zhang, Peiming; Chang, Shuai; Huang, Shuo

2010-01-01

Single molecules in a tunnel junction can now be interrogated reliably using chemically-functionalized electrodes. Monitoring stochastic bonding fluctuations between a ligand bound to one electrode and its target bound to a second electrode (“tethered molecule-pair” configuration) gives insight into the nature of the intermolecular bonding at a single molecule-pair level, and defines the requirements for reproducible tunneling data. Simulations show that there is an instability in the tunnel gap at large currents, and this results in a multiplicity of contacts with a corresponding spread in the measured currents. At small currents (i.e. large gaps) the gap is stable, and functionalizing a pair of electrodes with recognition reagents (the “free analyte” configuration) can generate a distinct tunneling signal when an analyte molecule is trapped in the gap. This opens up a new interface between chemistry and electronics with immediate implications for rapid sequencing of single DNA molecules. PMID:20522930

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease.

PubMed

Dilliott, Allison A; Farhan, Sali M K; Ghani, Mahdi; Sato, Christine; Liang, Eric; Zhang, Ming; McIntyre, Adam D; Cao, Henian; Racacho, Lemuel; Robinson, John F; Strong, Michael J; Masellis, Mario; Bulman, Dennis E; Rogaeva, Ekaterina; Lang, Anthony; Tartaglia, Carmela; Finger, Elizabeth; Zinman, Lorne; Turnbull, John; Freedman, Morris; Swartz, Rick; Black, Sandra E; Hegele, Robert A

2018-04-04

Next-generation sequencing (NGS) is quickly revolutionizing how research into the genetic determinants of constitutional disease is performed. The technique is highly efficient with millions of sequencing reads being produced in a short time span and at relatively low cost. Specifically, targeted NGS is able to focus investigations to genomic regions of particular interest based on the disease of study. Not only does this further reduce costs and increase the speed of the process, but it lessens the computational burden that often accompanies NGS. Although targeted NGS is restricted to certain regions of the genome, preventing identification of potential novel loci of interest, it can be an excellent technique when faced with a phenotypically and genetically heterogeneous disease, for which there are previously known genetic associations. Because of the complex nature of the sequencing technique, it is important to closely adhere to protocols and methodologies in order to achieve sequencing reads of high coverage and quality. Further, once sequencing reads are obtained, a sophisticated bioinformatics workflow is utilized to accurately map reads to a reference genome, to call variants, and to ensure the variants pass quality metrics. Variants must also be annotated and curated based on their clinical significance, which can be standardized by applying the American College of Medical Genetics and Genomics Pathogenicity Guidelines. The methods presented herein will display the steps involved in generating and analyzing NGS data from a targeted sequencing panel, using the ONDRISeq neurodegenerative disease panel as a model, to identify variants that may be of clinical significance.

Targeted sequencing of plant genomes

Treesearch

Mark D. Huynh

2014-01-01

Next-generation sequencing (NGS) has revolutionized the field of genetics by providing a means for fast and relatively affordable sequencing. With the advancement of NGS, wholegenome sequencing (WGS) has become more commonplace. However, sequencing an entire genome is still not cost effective or even beneficial in all cases. In studies that do not require a whole-...

Non-Adjacent Consonant Sequence Patterns in English Target Words during the First-Word Period

ERIC Educational Resources Information Center

Aoyama, Katsura; Davis, Barbara L.

2017-01-01

The goal of this study was to investigate non-adjacent consonant sequence patterns in target words during the first-word period in infants learning American English. In the spontaneous speech of eighteen participants, target words with a Consonant-Vowel-Consonant (C[subscript 1]VC[subscript 2]) shape were analyzed. Target words were grouped into…

StarScan: a web server for scanning small RNA targets from degradome sequencing data.

PubMed

Liu, Shun; Li, Jun-Hao; Wu, Jie; Zhou, Ke-Ren; Zhou, Hui; Yang, Jian-Hua; Qu, Liang-Hu

2015-07-01

Endogenous small non-coding RNAs (sRNAs), including microRNAs, PIWI-interacting RNAs and small interfering RNAs, play important gene regulatory roles in animals and plants by pairing to the protein-coding and non-coding transcripts. However, computationally assigning these various sRNAs to their regulatory target genes remains technically challenging. Recently, a high-throughput degradome sequencing method was applied to identify biologically relevant sRNA cleavage sites. In this study, an integrated web-based tool, StarScan (sRNA target Scan), was developed for scanning sRNA targets using degradome sequencing data from 20 species. Given a sRNA sequence from plants or animals, our web server performs an ultrafast and exhaustive search for potential sRNA-target interactions in annotated and unannotated genomic regions. The interactions between small RNAs and target transcripts were further evaluated using a novel tool, alignScore. A novel tool, degradomeBinomTest, was developed to quantify the abundance of degradome fragments located at the 9-11th nucleotide from the sRNA 5' end. This is the first web server for discovering potential sRNA-mediated RNA cleavage events in plants and animals, which affords mechanistic insights into the regulatory roles of sRNAs. The StarScan web server is available at http://mirlab.sysu.edu.cn/starscan/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Infrared variation reduction by simultaneous background suppression and target contrast enhancement for deep convolutional neural network-based automatic target recognition

NASA Astrophysics Data System (ADS)

Kim, Sungho

2017-06-01

Automatic target recognition (ATR) is a traditionally challenging problem in military applications because of the wide range of infrared (IR) image variations and the limited number of training images. IR variations are caused by various three-dimensional target poses, noncooperative weather conditions (fog and rain), and difficult target acquisition environments. Recently, deep convolutional neural network-based approaches for RGB images (RGB-CNN) showed breakthrough performance in computer vision problems, such as object detection and classification. The direct use of RGB-CNN to the IR ATR problem fails to work because of the IR database problems (limited database size and IR image variations). An IR variation-reduced deep CNN (IVR-CNN) to cope with the problems is presented. The problem of limited IR database size is solved by a commercial thermal simulator (OKTAL-SE). The second problem of IR variations is mitigated by the proposed shifted ramp function-based intensity transformation. This can suppress the background and enhance the target contrast simultaneously. The experimental results on the synthesized IR images generated by the thermal simulator (OKTAL-SE) validated the feasibility of IVR-CNN for military ATR applications.

Exploring 3D Human Action Recognition: from Offline to Online.

PubMed

Liu, Zhenyu; Li, Rui; Tan, Jianrong

2018-02-20

With the introduction of cost-effective depth sensors, a tremendous amount of research has been devoted to studying human action recognition using 3D motion data. However, most existing methods work in an offline fashion, i.e., they operate on a segmented sequence. There are a few methods specifically designed for online action recognition, which continually predicts action labels as a stream sequence proceeds. In view of this fact, we propose a question: can we draw inspirations and borrow techniques or descriptors from existing offline methods, and then apply these to online action recognition? Note that extending offline techniques or descriptors to online applications is not straightforward, since at least two problems-including real-time performance and sequence segmentation-are usually not considered in offline action recognition. In this paper, we give a positive answer to the question. To develop applicable online action recognition methods, we carefully explore feature extraction, sequence segmentation, computational costs, and classifier selection. The effectiveness of the developed methods is validated on the MSR 3D Online Action dataset and the MSR Daily Activity 3D dataset.

Exploring 3D Human Action Recognition: from Offline to Online

PubMed Central

Li, Rui; Liu, Zhenyu; Tan, Jianrong

2018-01-01

With the introduction of cost-effective depth sensors, a tremendous amount of research has been devoted to studying human action recognition using 3D motion data. However, most existing methods work in an offline fashion, i.e., they operate on a segmented sequence. There are a few methods specifically designed for online action recognition, which continually predicts action labels as a stream sequence proceeds. In view of this fact, we propose a question: can we draw inspirations and borrow techniques or descriptors from existing offline methods, and then apply these to online action recognition? Note that extending offline techniques or descriptors to online applications is not straightforward, since at least two problems—including real-time performance and sequence segmentation—are usually not considered in offline action recognition. In this paper, we give a positive answer to the question. To develop applicable online action recognition methods, we carefully explore feature extraction, sequence segmentation, computational costs, and classifier selection. The effectiveness of the developed methods is validated on the MSR 3D Online Action dataset and the MSR Daily Activity 3D dataset. PMID:29461502

Programmable and multiparameter DNA-based logic platform for cancer recognition and targeted therapy.

PubMed

You, Mingxu; Zhu, Guizhi; Chen, Tao; Donovan, Michael J; Tan, Weihong

2015-01-21

The specific inventory of molecules on diseased cell surfaces (e.g., cancer cells) provides clinicians an opportunity for accurate diagnosis and intervention. With the discovery of panels of cancer markers, carrying out analyses of multiple cell-surface markers is conceivable. As a trial to accomplish this, we have recently designed a DNA-based device that is capable of performing autonomous logic-based analysis of two or three cancer cell-surface markers. Combining the specific target-recognition properties of DNA aptamers with toehold-mediated strand displacement reactions, multicellular marker-based cancer analysis can be realized based on modular AND, OR, and NOT Boolean logic gates. Specifically, we report here a general approach for assembling these modular logic gates to execute programmable and higher-order profiling of multiple coexisting cell-surface markers, including several found on cancer cells, with the capacity to report a diagnostic signal and/or deliver targeted photodynamic therapy. The success of this strategy demonstrates the potential of DNA nanotechnology in facilitating targeted disease diagnosis and effective therapy.

Programmable and Multiparameter DNA-Based Logic Platform For Cancer Recognition and Targeted Therapy

PubMed Central

2014-01-01

The specific inventory of molecules on diseased cell surfaces (e.g., cancer cells) provides clinicians an opportunity for accurate diagnosis and intervention. With the discovery of panels of cancer markers, carrying out analyses of multiple cell-surface markers is conceivable. As a trial to accomplish this, we have recently designed a DNA-based device that is capable of performing autonomous logic-based analysis of two or three cancer cell-surface markers. Combining the specific target-recognition properties of DNA aptamers with toehold-mediated strand displacement reactions, multicellular marker-based cancer analysis can be realized based on modular AND, OR, and NOT Boolean logic gates. Specifically, we report here a general approach for assembling these modular logic gates to execute programmable and higher-order profiling of multiple coexisting cell-surface markers, including several found on cancer cells, with the capacity to report a diagnostic signal and/or deliver targeted photodynamic therapy. The success of this strategy demonstrates the potential of DNA nanotechnology in facilitating targeted disease diagnosis and effective therapy. PMID:25361164

A distributed automatic target recognition system using multiple low resolution sensors

NASA Astrophysics Data System (ADS)

Yue, Zhanfeng; Lakshmi Narasimha, Pramod; Topiwala, Pankaj

2008-04-01

In this paper, we propose a multi-agent system which uses swarming techniques to perform high accuracy Automatic Target Recognition (ATR) in a distributed manner. The proposed system can co-operatively share the information from low-resolution images of different looks and use this information to perform high accuracy ATR. An advanced, multiple-agent Unmanned Aerial Vehicle (UAV) systems-based approach is proposed which integrates the processing capabilities, combines detection reporting with live video exchange, and swarm behavior modalities that dramatically surpass individual sensor system performance levels. We employ real-time block-based motion analysis and compensation scheme for efficient estimation and correction of camera jitter, global motion of the camera/scene and the effects of atmospheric turbulence. Our optimized Partition Weighted Sum (PWS) approach requires only bitshifts and additions, yet achieves a stunning 16X pixel resolution enhancement, which is moreover parallizable. We develop advanced, adaptive particle-filtering based algorithms to robustly track multiple mobile targets by adaptively changing the appearance model of the selected targets. The collaborative ATR system utilizes the homographies between the sensors induced by the ground plane to overlap the local observation with the received images from other UAVs. The motion of the UAVs distorts estimated homography frame to frame. A robust dynamic homography estimation algorithm is proposed to address this, by using the homography decomposition and the ground plane surface estimation.

Divided attention enhances the recognition of emotional stimuli: evidence from the attentional boost effect.

PubMed

Rossi-Arnaud, Clelia; Spataro, Pietro; Costanzi, Marco; Saraulli, Daniele; Cestari, Vincenzo

2018-01-01

The present study examined predictions of the early-phase-elevated-attention hypothesis of the attentional boost effect (ABE), which suggests that transient increases in attention at encoding, as instantiated in the ABE paradigm, should enhance the recognition of neutral and positive items (whose encoding is mostly based on controlled processes), while having small or null effects on the recognition of negative items (whose encoding is primarily based on automatic processes). Participants were presented a sequence of negative, neutral and positive stimuli (pictures in Experiment 1, words in Experiment 2) associated to target (red) squares, distractor (green) squares or no squares (baseline condition). They were told to attend to the pictures/words and simultaneously press the spacebar of the computer when a red square appeared. In a later recognition task, stimuli associated to target squares were recognised better than stimuli associated to distractor squares, replicating the standard ABE. More importantly, we also found that: (a) the memory enhancement following target detection occurred with all types of stimuli (neutral, negative and positive) and (b) the advantage of negative stimuli over neutral stimuli was intact in the DA condition. These findings suggest that the encoding of negative stimuli depends on both controlled (attention-dependent) and automatic (attention-independent) processes.

Assessing the performance of a covert automatic target recognition algorithm

NASA Astrophysics Data System (ADS)

Ehrman, Lisa M.; Lanterman, Aaron D.

2005-05-01

Passive radar systems exploit illuminators of opportunity, such as TV and FM radio, to illuminate potential targets. Doing so allows them to operate covertly and inexpensively. Our research seeks to enhance passive radar systems by adding automatic target recognition (ATR) capabilities. In previous papers we proposed conducting ATR by comparing the radar cross section (RCS) of aircraft detected by a passive radar system to the precomputed RCS of aircraft in the target class. To effectively model the low-frequency setting, the comparison is made via a Rician likelihood model. Monte Carlo simulations indicate that the approach is viable. This paper builds on that work by developing a method for quickly assessing the potential performance of the ATR algorithm without using exhaustive Monte Carlo trials. This method exploits the relation between the probability of error in a binary hypothesis test under the Bayesian framework to the Chernoff information. Since the data are well-modeled as Rician, we begin by deriving a closed-form approximation for the Chernoff information between two Rician densities. This leads to an approximation for the probability of error in the classification algorithm that is a function of the number of available measurements. We conclude with an application that would be particularly cumbersome to accomplish via Monte Carlo trials, but that can be quickly addressed using the Chernoff information approach. This application evaluates the length of time that an aircraft must be tracked before the probability of error in the ATR algorithm drops below a desired threshold.

Structural biology of antibody recognition of carbohydrate epitopes and potential uses for targeted cancer immunotherapies.

PubMed

Dingjan, Tamir; Spendlove, Ian; Durrant, Lindy G; Scott, Andrew M; Yuriev, Elizabeth; Ramsland, Paul A

2015-10-01

Monoclonal antibodies represent the most successful class of biopharmaceuticals for the treatment of cancer. Mechanisms of action of therapeutic antibodies are very diverse and reflect their ability to engage in antibody-dependent effector mechanisms, internalize to deliver cytotoxic payloads, and display direct effects on cells by lysis or by modulating the biological pathways of their target antigens. Importantly, one of the universal changes in cancer is glycosylation and carbohydrate-binding antibodies can be produced to selectively recognize tumor cells over normal tissues. A promising group of cell surface antibody targets consists of carbohydrates presented as glycolipids or glycoproteins. In this review, we outline the basic principles of antibody-based targeting of carbohydrate antigens in cancer. We also present a detailed structural view of antibody recognition and the conformational properties of a series of related tissue-blood group (Lewis) carbohydrates that are being pursued as potential targets of cancer immunotherapy. Copyright © 2015 Elsevier Ltd. All rights reserved.

Microcinematographic and electron microscopic analysis of target cell lysis induced by cytotoxic T lymphocytes.

PubMed Central

Matter, A

1979-01-01

A study was carried out to determine the sequence of events of T-cell mediated target cell lysis in microcinematography and electron microscopy. Highly efficient cytotoxic T lymphocytes (CTL) were generated in vivo and in vitro using preimmunized spleen cells and purification procedures. Such CTL were highly specific. This specificity correlated well with the number of adhesions formed between CTL and targets and this criterion was used to study killer-target cell interaction. Microcinematography showed that target cell lysis at the single cell level, despite time variations, could be clearly separated into three phases: (a) a recognition phase, visible by random crawling of CTL over the target cell surface until firm contact was established; (b) a post-recognition phase, during which firm contact between CTL and target was maintained without gross modification of either cell; (c) a phase of target cell disintegration, mainly characterized by vigorous blebbing of the cell membrane resulting in a motionless carcass of the target cell but not in its total dissolution. Only later this carcass decayed and formed a necrotic ghost. Electron microscopic observations were put into sequence according to microcinematography. Post-recognition phase was characterized by a tight apposition of the membranes of CTL and target cell. No gap junctions could be observed. During target cell disintegration, profound cytoplasmic and nuclear changes occurred simultaneous with surface blebbing. Most noticeable were extensive internal vacuolization, mitochondrial swelling, nuclear pycnosis and dissolution of the nucleolus. These observations suggested that target cell lysis does not start with a surface phenomenon similar to complement lysis, but a process involving practically the whole cell simultaneously. It is conceivable, therefore, that the signal from the CTL is transmitted across the target cell, and that the switch to sudden cell death is manipulated deep inside the cell. Images

Trends in Correlation-Based Pattern Recognition and Tracking in Forward-Looking Infrared Imagery

PubMed Central

Alam, Mohammad S.; Bhuiyan, Sharif M. A.

2014-01-01

In this paper, we review the recent trends and advancements on correlation-based pattern recognition and tracking in forward-looking infrared (FLIR) imagery. In particular, we discuss matched filter-based correlation techniques for target detection and tracking which are widely used for various real time applications. We analyze and present test results involving recently reported matched filters such as the maximum average correlation height (MACH) filter and its variants, and distance classifier correlation filter (DCCF) and its variants. Test results are presented for both single/multiple target detection and tracking using various real-life FLIR image sequences. PMID:25061840

Targeted next generation sequencing for molecular diagnosis of Usher syndrome.

PubMed

Aparisi, María J; Aller, Elena; Fuster-García, Carla; García-García, Gema; Rodrigo, Regina; Vázquez-Manrique, Rafael P; Blanco-Kelly, Fiona; Ayuso, Carmen; Roux, Anne-Françoise; Jaijo, Teresa; Millán, José M

2014-11-18

Usher syndrome is an autosomal recessive disease that associates sensorineural hearing loss, retinitis pigmentosa and, in some cases, vestibular dysfunction. It is clinically and genetically heterogeneous. To date, 10 genes have been associated with the disease, making its molecular diagnosis based on Sanger sequencing, expensive and time-consuming. Consequently, the aim of the present study was to develop a molecular diagnostics method for Usher syndrome, based on targeted next generation sequencing. A custom HaloPlex panel for Illumina platforms was designed to capture all exons of the 10 known causative Usher syndrome genes (MYO7A, USH1C, CDH23, PCDH15, USH1G, CIB2, USH2A, GPR98, DFNB31 and CLRN1), the two Usher syndrome-related genes (HARS and PDZD7) and the two candidate genes VEZT and MYO15A. A cohort of 44 patients suffering from Usher syndrome was selected for this study. This cohort was divided into two groups: a test group of 11 patients with known mutations and another group of 33 patients with unknown mutations. Forty USH patients were successfully sequenced, 8 USH patients from the test group and 32 patients from the group composed of USH patients without genetic diagnosis. We were able to detect biallelic mutations in one USH gene in 22 out of 32 USH patients (68.75%) and to identify 79.7% of the expected mutated alleles. Fifty-three different mutations were detected. These mutations included 21 missense, 8 nonsense, 9 frameshifts, 9 intronic mutations and 6 large rearrangements. Targeted next generation sequencing allowed us to detect both point mutations and large rearrangements in a single experiment, minimizing the economic cost of the study, increasing the detection ratio of the genetic cause of the disease and improving the genetic diagnosis of Usher syndrome patients.

TALE-PvuII fusion proteins--novel tools for gene targeting.

PubMed

Yanik, Mert; Alzubi, Jamal; Lahaye, Thomas; Cathomen, Toni; Pingoud, Alfred; Wende, Wolfgang

2013-01-01

Zinc finger nucleases (ZFNs) consist of zinc fingers as DNA-binding module and the non-specific DNA-cleavage domain of the restriction endonuclease FokI as DNA-cleavage module. This architecture is also used by TALE nucleases (TALENs), in which the DNA-binding modules of the ZFNs have been replaced by DNA-binding domains based on transcription activator like effector (TALE) proteins. Both TALENs and ZFNs are programmable nucleases which rely on the dimerization of FokI to induce double-strand DNA cleavage at the target site after recognition of the target DNA by the respective DNA-binding module. TALENs seem to have an advantage over ZFNs, as the assembly of TALE proteins is easier than that of ZFNs. Here, we present evidence that variant TALENs can be produced by replacing the catalytic domain of FokI with the restriction endonuclease PvuII. These fusion proteins recognize only the composite recognition site consisting of the target site of the TALE protein and the PvuII recognition sequence (addressed site), but not isolated TALE or PvuII recognition sites (unaddressed sites), even at high excess of protein over DNA and long incubation times. In vitro, their preference for an addressed over an unaddressed site is > 34,000-fold. Moreover, TALE-PvuII fusion proteins are active in cellula with minimal cytotoxicity.

A Dual-Specific Targeting Approach Based on the Simultaneous Recognition of Duplex and Quadruplex Motifs.

PubMed

Nguyen, Thi Quynh Ngoc; Lim, Kah Wai; Phan, Anh Tuân

2017-09-20

Small-molecule ligands targeting nucleic acids have been explored as potential therapeutic agents. Duplex groove-binding ligands have been shown to recognize DNA in a sequence-specific manner. On the other hand, quadruplex-binding ligands exhibit high selectivity between quadruplex and duplex, but show limited discrimination between different quadruplex structures. Here we propose a dual-specific approach through the simultaneous application of duplex- and quadruplex-binders. We demonstrated that a quadruplex-specific ligand and a duplex-specific ligand can simultaneously interact at two separate binding sites of a quadruplex-duplex hybrid harbouring both quadruplex and duplex structural elements. Such a dual-specific targeting strategy would combine the sequence specificity of duplex-binders and the strong binding affinity of quadruplex-binders, potentially allowing the specific targeting of unique quadruplex structures. Future research can be directed towards the development of conjugated compounds targeting specific genomic quadruplex-duplex sites, for which the linker would be highly context-dependent in terms of length and flexibility, as well as the attachment points onto both ligands.

Increase in Speech Recognition due to Linguistic Mismatch Between Target and Masker Speech: Monolingual and Simultaneous Bilingual Performance

PubMed Central

Calandruccio, Lauren; Zhou, Haibo

2014-01-01

Purpose To examine whether improved speech recognition during linguistically mismatched target–masker experiments is due to linguistic unfamiliarity of the masker speech or linguistic dissimilarity between the target and masker speech. Method Monolingual English speakers (n = 20) and English–Greek simultaneous bilinguals (n = 20) listened to English sentences in the presence of competing English and Greek speech. Data were analyzed using mixed-effects regression models to determine differences in English recogition performance between the 2 groups and 2 masker conditions. Results Results indicated that English sentence recognition for monolinguals and simultaneous English–Greek bilinguals improved when the masker speech changed from competing English to competing Greek speech. Conclusion The improvement in speech recognition that has been observed for linguistically mismatched target–masker experiments cannot be simply explained by the masker language being linguistically unknown or unfamiliar to the listeners. Listeners can improve their speech recognition in linguistically mismatched target–masker experiments even when the listener is able to obtain meaningful linguistic information from the masker speech. PMID:24167230

Recognition of DNA abasic site nanocavity by fluorophore-switched probe: Suitable for all sequence environments

NASA Astrophysics Data System (ADS)

Wang, Ying; Hu, Yuehua; Wu, Tao; Zhang, Lihua; Liu, Hua; Zhou, Xiaoshun; Shao, Yong

2016-01-01

Removal of a damaged base in DNA produces an abasic site (AP site) nanocavity. If left un-repaired in vivo by the specific enzyme, this nanocavity will result in nucleotide mutation in the following DNA replication. Therefore, selective recognition of AP site nanocavity by small molecules is important for identification of such DNA damage and development of genetic drugs. In this work, we investigate the fluorescence behavior of isoquinoline alkaloids including palmatine (PAL), berberine (BER), epiberberine (EPI), jatrorrhizine (JAT), coptisine (COP), coralyne (COR), worenine (WOR), berberrubine (BEU), sanguinarine (SAN), chelerythrine (CHE), and nitidine (NIT) upon binding with the AP nanocavity. PAL is screened out as the most efficient fluorophore-switched probe to recognize the AP nanocavity over the fully matched DNA. Its fluorescence enhancement occurs for all of the AP nanocavity sequence environments, which has not been achieved by the previously used probes. The bridged π conjugation effect should partially contribute to the AP nanocavity-specific fluorescence, as opposed to the solvent effect. Due to the strong binding with the AP nanocavity, PAL will find wide applications in the DNA damage recognition and sensor development.

Molecular recognition of glyconanoparticles by RCA and E. coli K88 - designing transports for targeted therapy.

PubMed

Gallegos-Tabanico, Amed; Sarabia-Sainz, Jose A; Sarabia-Sainz, H Manuel; Carrillo Torres, Roberto; Guzman-Partida, Ana M; Monfort, Gabriela Ramos-Clamont; Silva-Campa, Erika; Burgara-Estrella, Alexel J; Angulo-Molina, Aracely; Acosta-Elias, Mónica; Pedroza-Montero, Martín; Vazquez-Moreno, Luz

2017-01-01

The targeted drug delivery has been studied as one of the main methods in medicine to ensure successful treatments of diseases. Pharmaceutical sciences are using micro or nano carriers to obtain a controlled delivery of drugs, able to selectively interact with pathogens, cells or tissues. In this work, we modified bovine serum albumin (BSA) with lactose, obtaining a neoglycan (BSA-Lac). Subsequently, we synthesized glyconanoparticles (NPBSA-Lac) with the premise that it would be recognized by microbial galactose specific lectins. NPBSA-Lac were tested for bio-recognition with adhesins of E. coli K88 and Ricinus communis agglutinin I (RCA). Glycation of BSA with lactose was analyzed by electrophoresis, infrared spectroscopy and fluorescence. Approximately 41 lactoses per BSA molecule were estimated. Nanoparticles were obtained using water in oil emulsion method and spheroid morphology with a range size of 300-500 nm was observed. Specific recognition of NPBSA-Lac by RCA and E. coli K88 was displayed by aggregation of nanoparticles analyzed by dynamic light scattering and atomic force microscopy. The results indicate that the lactosylated nanovectors could be targeted at the E. coli K88 adhesin and potentially could be used as a transporter for an antibacterial drug.

Foundations for a syntatic pattern recognition system for genomic DNA sequences. [Annual] report, 1 December 1991--31 March 1993

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

Searles, D.B.

1993-03-01

The goal of the proposed work is the creation of a software system that will perform sophisticated pattern recognition and related functions at a level of abstraction and with expressive power beyond current general-purpose pattern-matching systems for biological sequences; and with a more uniform language, environment, and graphical user interface, and with greater flexibility, extensibility, embeddability, and ability to incorporate other algorithms, than current special-purpose analytic software.

A flexible and economical barcoding approach for highly multiplexed amplicon sequencing of diverse target genes

PubMed Central

Herbold, Craig W.; Pelikan, Claus; Kuzyk, Orest; Hausmann, Bela; Angel, Roey; Berry, David; Loy, Alexander

2015-01-01

High throughput sequencing of phylogenetic and functional gene amplicons provides tremendous insight into the structure and functional potential of complex microbial communities. Here, we introduce a highly adaptable and economical PCR approach to barcoding and pooling libraries of numerous target genes. In this approach, we replace gene- and sequencing platform-specific fusion primers with general, interchangeable barcoding primers, enabling nearly limitless customized barcode-primer combinations. Compared to barcoding with long fusion primers, our multiple-target gene approach is more economical because it overall requires lower number of primers and is based on short primers with generally lower synthesis and purification costs. To highlight our approach, we pooled over 900 different small-subunit rRNA and functional gene amplicon libraries obtained from various environmental or host-associated microbial community samples into a single, paired-end Illumina MiSeq run. Although the amplicon regions ranged in size from approximately 290 to 720 bp, we found no significant systematic sequencing bias related to amplicon length or gene target. Our results indicate that this flexible multiplexing approach produces large, diverse, and high quality sets of amplicon sequence data for modern studies in microbial ecology. PMID:26236305

Design of a sensitive aptasensor based on magnetic microbeads-assisted strand displacement amplification and target recycling.

PubMed

Li, Ying; Ji, Xiaoting; Song, Weiling; Guo, Yingshu

2013-04-03

A cross-circular amplification system for sensitive detection of adenosine triphosphate (ATP) in cancer cells was developed based on aptamer-target interaction, magnetic microbeads (MBs)-assisted strand displacement amplification and target recycling. Here we described a new recognition probe possessing two parts, the ATP aptamer and the extension part. The recognition probe was firstly immobilized on the surface of MBs and hybridized with its complementary sequence to form a duplex. When combined with ATP, the probe changed its conformation, revealing the extension part in single-strand form, which further served as a toehold for subsequent target recycling. The released complementary sequence of the probe acted as the catalyst of the MB-assisted strand displacement reaction. Incorporated with target recycling, a large amount of biotin-tagged MB complexes were formed to stimulate the generation of chemiluminescence (CL) signal in the presence of luminol and H2O2 by incorporating with streptavidin-HRP, reaching a detection limit of ATP as low as 6.1×10(-10)M. Moreover, sample assays of ATP in Ramos Burkitt's lymphoma B cells were performed, which confirmed the reliability and practicality of the protocol. Copyright © 2013 Elsevier B.V. All rights reserved.

Electrophoretic mobility shift assay reveals a novel recognition sequence for Setaria italica NAC protein.

PubMed

Puranik, Swati; Kumar, Karunesh; Srivastava, Prem S; Prasad, Manoj

2011-10-01

The NAC (NAM/ATAF1,2/CUC2) proteins are among the largest family of plant transcription factors. Its members have been associated with diverse plant processes and intricately regulate the expression of several genes. Inspite of this immense progress, knowledge of their DNA-binding properties are still limited. In our recent publication,1 we reported isolation of a membrane-associated NAC domain protein from Setaria italica (SiNAC). Transactivation analysis revealed that it was a functionally active transcription factor as it could stimulate expression of reporter genes in vivo. Truncations of the transmembrane region of the protein lead to its nuclear localization. Here we describe expression and purification of SiNAC DNA-binding domain. We further report identification of a novel DNA-binding site, [C/G][A/T][T/A][G/C]TC[C/G][A/T][C/G][G/C] for SiNAC by electrophoretic mobility shift assay. The SiNAC-GST protein could bind to the NAC recognition sequence in vitro as well as to sequences where some bases had been reshuffled. The results presented here contribute to our understanding of the DNA-binding specificity of SiNAC protein.

Electrophoretic mobility shift assay reveals a novel recognition sequence for Setaria italica NAC protein

PubMed Central

Puranik, Swati; Kumar, Karunesh; Srivastava, Prem S

2011-01-01

The NAC (NAM/ATAF1,2/CUC2) proteins are among the largest family of plant transcription factors. Its members have been associated with diverse plant processes and intricately regulate the expression of several genes. Inspite of this immense progress, knowledge of their DNA-binding properties are still limited. In our recent publication,1 we reported isolation of a membrane-associated NAC domain protein from Setaria italica (SiNAC). Transactivation analysis revealed that it was a functionally active transcription factor as it could stimulate expression of reporter genes in vivo. Truncation of the transmembrane region of the protein lead to its nuclear localization. Here we describe expression and purification of SiNAC DNA-binding domain. We further report identification of a novel DNA-binding site, [C/G][A/T] [T/A][G/C]TC[C/G][A/T][C/G][G/C] for SiNAC by electrophoretic mobility shift assay. The SiNAC-GST protein could bind to the NAC recognition sequence in vitro as well as to sequences where some bases had been reshuffled. The results presented here contribute to our understanding of the DNA-binding specificity of SiNAC protein. PMID:21918373

Method to amplify variable sequences without imposing primer sequences

DOEpatents

Bradbury, Andrew M.; Zeytun, Ahmet

2006-11-14

The present invention provides methods of amplifying target sequences without including regions flanking the target sequence in the amplified product or imposing amplification primer sequences on the amplified product. Also provided are methods of preparing a library from such amplified target sequences.

Structural Basis for the Altered PAM Recognition by Engineered CRISPR-Cpf1.

PubMed

Nishimasu, Hiroshi; Yamano, Takashi; Gao, Linyi; Zhang, Feng; Ishitani, Ryuichiro; Nureki, Osamu

2017-07-06

The RNA-guided Cpf1 nuclease cleaves double-stranded DNA targets complementary to the CRISPR RNA (crRNA), and it has been harnessed for genome editing technologies. Recently, Acidaminococcus sp. BV3L6 (AsCpf1) was engineered to recognize altered DNA sequences as the protospacer adjacent motif (PAM), thereby expanding the target range of Cpf1-mediated genome editing. Whereas wild-type AsCpf1 recognizes the TTTV PAM, the RVR (S542R/K548V/N552R) and RR (S542R/K607R) variants can efficiently recognize the TATV and TYCV PAMs, respectively. However, their PAM recognition mechanisms remained unknown. Here we present the 2.0 Å resolution crystal structures of the RVR and RR variants bound to a crRNA and its target DNA. The structures revealed that the RVR and RR variants primarily recognize the PAM-complementary nucleotides via the substituted residues. Our high-resolution structures delineated the altered PAM recognition mechanisms of the AsCpf1 variants, providing a basis for the further engineering of CRISPR-Cpf1. Copyright © 2017 Elsevier Inc. All rights reserved.

Impact of surfactants on the target recognition of Fab-conjugated PLGA nanoparticles.

PubMed

Kennedy, Patrick J; Perreira, Ines; Ferreira, Daniel; Nestor, Marika; Oliveira, Carla; Granja, Pedro L; Sarmento, Bruno

2018-06-01

Targeted drug delivery with nanoparticles (NPs) requires proper surface ligand presentation and availability. Surfactants are often used as stabilizers in the production of targeted NPs. Here, we evaluated the impact of surfactants on ligand functionalization and downstream molecular recognition. Our model system consisted of fluorescent poly(lactic-co-glycolic acid) (PLGA) NPs that were nanoprecipitated in one of a small panel of commonly-used surfactants followed by equivalent washes and conjugation of an engineered Fab antibody fragment. Size, polydispersity index and zeta potential were determined by dynamic light scattering and laser Doppler anemometry, and Fab presence on the NPs was assessed by enzyme-linked immunosorbent assay. Most importantly, Fab-decorated NP binding to the cell surface receptor was monitored by fluorescence-activated cell sorting. 2% polyvinyl alcohol, 1% sodium cholate, 0.5% Pluronic F127 (F127) and 2% Tween-80 were initially tested. Of the four surfactants tested, PLGA NPs in 0.5% F127 and 2% Tween-80 had the highest cell binding. These two surfactants were then retested in two different concentrations, 0.5% and 2%. The Fab-decorated PLGA NPs in 2% F127 had the highest cell binding. This study highlights the impact of common surfactants and their concentrations on the downstream targeting of ligand-decorated NPs. Similar principles should be applied in the development of future targeted nanosystems where surfactants are employed. Copyright © 2018 Elsevier B.V. All rights reserved.

Vigilante: Ultrafast Smart Sensor for Target Recognition and Precision Tracking in a Simulated CMD Scenario

NASA Technical Reports Server (NTRS)

Uldomkesmalee, Suraphol; Suddarth, Steven C.

1997-01-01

VIGILANTE is an ultrafast smart sensor testbed for generic Automatic Target Recognition (ATR) applications with a series of capability demonstration focussed on cruise missile defense (CMD). VIGILANTE's sensor/processor architecture is based on next-generation UV/visible/IR sensors and a tera-operations per second sugar-cube processor, as well as supporting airborne vehicle. Excellent results of efficient ATR methodologies that use an eigenvectors/neural network combination and feature-based precision tracking have been demonstrated in the laboratory environment.

Chemiresistive and Gravimetric Dual-Mode Gas Sensor toward Target Recognition and Differentiation.

PubMed

Chen, Yan; Zhang, Hao; Feng, Zhihong; Zhang, Hongxiang; Zhang, Rui; Yu, Yuanyuan; Tao, Jin; Zhao, Hongyuan; Guo, Wenlan; Pang, Wei; Duan, Xuexin; Liu, Jing; Zhang, Daihua

2016-08-24

We demonstrate a dual-mode gas sensor for simultaneous and independent acquisition of electrical and mechanical signals from the same gas adsorption event. The device integrates a graphene field-effect transistor (FET) with a piezoelectric resonator in a seamless manner by leveraging multiple structural and functional synergies. Dual signals resulting from independent physical processes, i.e., mass attachment and charge transfer can reflect intrinsic properties of gas molecules and potentially enable target recognition and quantification at the same time. Fabrication of the device is based on standard Integrated Circuit (IC) foundry processes and fully compatible with system-on-a-chip (SoC) integration to achieve extremely small form factors. In addition, the ability of simultaneous measurements of mass adsorption and charge transfer guides us to a more precise understanding of the interactions between graphene and various gas molecules. Besides its practical functions, the device serves as an effective tool to quantitatively investigate the physical processes and sensing mechanisms for a large library of sensing materials and target analytes.

TALE-PvuII Fusion Proteins – Novel Tools for Gene Targeting

PubMed Central

Yanik, Mert; Alzubi, Jamal; Lahaye, Thomas; Cathomen, Toni; Pingoud, Alfred; Wende, Wolfgang

2013-01-01

Zinc finger nucleases (ZFNs) consist of zinc fingers as DNA-binding module and the non-specific DNA-cleavage domain of the restriction endonuclease FokI as DNA-cleavage module. This architecture is also used by TALE nucleases (TALENs), in which the DNA-binding modules of the ZFNs have been replaced by DNA-binding domains based on transcription activator like effector (TALE) proteins. Both TALENs and ZFNs are programmable nucleases which rely on the dimerization of FokI to induce double-strand DNA cleavage at the target site after recognition of the target DNA by the respective DNA-binding module. TALENs seem to have an advantage over ZFNs, as the assembly of TALE proteins is easier than that of ZFNs. Here, we present evidence that variant TALENs can be produced by replacing the catalytic domain of FokI with the restriction endonuclease PvuII. These fusion proteins recognize only the composite recognition site consisting of the target site of the TALE protein and the PvuII recognition sequence (addressed site), but not isolated TALE or PvuII recognition sites (unaddressed sites), even at high excess of protein over DNA and long incubation times. In vitro, their preference for an addressed over an unaddressed site is > 34,000-fold. Moreover, TALE-PvuII fusion proteins are active in cellula with minimal cytotoxicity. PMID:24349308

An RRM–ZnF RNA recognition module targets RBM10 to exonic sequences to promote exon exclusion

PubMed Central

Collins, Katherine M.; Kainov, Yaroslav A.; Christodolou, Evangelos; Ray, Debashish; Morris, Quaid; Hughes, Timothy; Taylor, Ian A.

2017-01-01

Abstract RBM10 is an RNA-binding protein that plays an essential role in development and is frequently mutated in the context of human disease. RBM10 recognizes a diverse set of RNA motifs in introns and exons and regulates alternative splicing. However, the molecular mechanisms underlying this seemingly relaxed sequence specificity are not understood and functional studies have focused on 3΄ intronic sites only. Here, we dissect the RNA code recognized by RBM10 and relate it to the splicing regulatory function of this protein. We show that a two-domain RRM1–ZnF unit recognizes a GGA-centered motif enriched in RBM10 exonic sites with high affinity and specificity and test that the interaction with these exonic sequences promotes exon skipping. Importantly, a second RRM domain (RRM2) of RBM10 recognizes a C-rich sequence, which explains its known interaction with the intronic 3΄ site of NUMB exon 9 contributing to regulation of the Notch pathway in cancer. Together, these findings explain RBM10's broad RNA specificity and suggest that RBM10 functions as a splicing regulator using two RNA-binding units with different specificities to promote exon skipping. PMID:28379442

An RRM-ZnF RNA recognition module targets RBM10 to exonic sequences to promote exon exclusion.

PubMed

Collins, Katherine M; Kainov, Yaroslav A; Christodolou, Evangelos; Ray, Debashish; Morris, Quaid; Hughes, Timothy; Taylor, Ian A; Makeyev, Eugene V; Ramos, Andres

2017-06-20

RBM10 is an RNA-binding protein that plays an essential role in development and is frequently mutated in the context of human disease. RBM10 recognizes a diverse set of RNA motifs in introns and exons and regulates alternative splicing. However, the molecular mechanisms underlying this seemingly relaxed sequence specificity are not understood and functional studies have focused on 3΄ intronic sites only. Here, we dissect the RNA code recognized by RBM10 and relate it to the splicing regulatory function of this protein. We show that a two-domain RRM1-ZnF unit recognizes a GGA-centered motif enriched in RBM10 exonic sites with high affinity and specificity and test that the interaction with these exonic sequences promotes exon skipping. Importantly, a second RRM domain (RRM2) of RBM10 recognizes a C-rich sequence, which explains its known interaction with the intronic 3΄ site of NUMB exon 9 contributing to regulation of the Notch pathway in cancer. Together, these findings explain RBM10's broad RNA specificity and suggest that RBM10 functions as a splicing regulator using two RNA-binding units with different specificities to promote exon skipping. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Computer program for the IBM personal computer which searches for approximate matches to short oligonucleotide sequences in long target DNA sequences.

PubMed Central

Myers, E W; Mount, D W

1986-01-01

We describe a program which may be used to find approximate matches to a short predefined DNA sequence in a larger target DNA sequence. The program predicts the usefulness of specific DNA probes and sequencing primers and finds nearly identical sequences that might represent the same regulatory signal. The program is written in the C programming language and will run on virtually any computer system with a C compiler, such as the IBM/PC and other computers running under the MS/DOS and UNIX operating systems. The program has been integrated into an existing software package for the IBM personal computer (see article by Mount and Conrad, this volume). Some examples of its use are given. PMID:3753785

Textual emotion recognition for enhancing enterprise computing

NASA Astrophysics Data System (ADS)

Quan, Changqin; Ren, Fuji

2016-05-01

The growing interest in affective computing (AC) brings a lot of valuable research topics that can meet different application demands in enterprise systems. The present study explores a sub area of AC techniques - textual emotion recognition for enhancing enterprise computing. Multi-label emotion recognition in text is able to provide a more comprehensive understanding of emotions than single label emotion recognition. A representation of 'emotion state in text' is proposed to encompass the multidimensional emotions in text. It ensures the description in a formal way of the configurations of basic emotions as well as of the relations between them. Our method allows recognition of the emotions for the words bear indirect emotions, emotion ambiguity and multiple emotions. We further investigate the effect of word order for emotional expression by comparing the performances of bag-of-words model and sequence model for multi-label sentence emotion recognition. The experiments show that the classification results under sequence model are better than under bag-of-words model. And homogeneous Markov model showed promising results of multi-label sentence emotion recognition. This emotion recognition system is able to provide a convenient way to acquire valuable emotion information and to improve enterprise competitive ability in many aspects.

Deep Recurrent Neural Networks for Human Activity Recognition

PubMed Central

Murad, Abdulmajid

2017-01-01

Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs. PMID:29113103

Deep Recurrent Neural Networks for Human Activity Recognition.

PubMed

Murad, Abdulmajid; Pyun, Jae-Young

2017-11-06

Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs.

Individual microRNAs (miRNAs) display distinct mRNA targeting "rules".

PubMed

Wang, Wang-Xia; Wilfred, Bernard R; Xie, Kevin; Jennings, Mary H; Hu, Yanling Hu; Stromberg, Arnold J; Nelson, Peter T

2010-01-01

MicroRNAs (miRNAs) guide Argonaute (AGO)-containing microribonucleoprotein (miRNP) complexes to target mRNAs.It has been assumed that miRNAs behave similarly to each other with regard to mRNA target recognition. The usual assumptions, which are based on prior studies, are that miRNAs target preferentially sequences in the 3'UTR of mRNAs,guided by the 5' "seed" portion of the miRNAs. Here we isolated AGO- and miRNA-containing miRNPs from human H4 tumor cells by co-immunoprecipitation (co-IP) with anti-AGO antibody. Cells were transfected with miR-107, miR-124,miR-128, miR-320, or a negative control miRNA. Co-IPed RNAs were subjected to downstream high-density Affymetrix Human Gene 1.0 ST microarray analyses using an assay we validated previously-a "RIP-Chip" experimental design. RIP-Chip data provided a list of mRNAs recruited into the AGO-miRNP in correlation to each miRNA. These experimentally identified miRNA targets were analyzed for complementary six nucleotide "seed" sequences within the transfected miRNAs. We found that miR-124 targets tended to have sequences in the 3'UTR that would be recognized by the 5' seed of miR-124, as described in previous studies. By contrast, miR-107 targets tended to have 'seed' sequences in the mRNA open reading frame, but not the 3' UTR. Further, mRNA targets of miR-128 and miR-320 are less enriched for 6-mer seed sequences in comparison to miR-107 and miR-124. In sum, our data support the importance of the 5' seed in determining binding characteristics for some miRNAs; however, the "binding rules" are complex, and individual miRNAs can have distinct sequence determinants that lead to mRNA targeting.

Phosphotyrosine recognition domains: the typical, the atypical and the versatile

PubMed Central

2012-01-01

SH2 domains are long known prominent players in the field of phosphotyrosine recognition within signaling protein networks. However, over the years they have been joined by an increasing number of other protein domain families that can, at least with some of their members, also recognise pTyr residues in a sequence-specific context. This superfamily of pTyr recognition modules, which includes substantial fractions of the PTB domains, as well as much smaller, or even single member fractions like the HYB domain, the PKCδ and PKCθ C2 domains and RKIP, represents a fascinating, medically relevant and hence intensely studied part of the cellular signaling architecture of metazoans. Protein tyrosine phosphorylation clearly serves a plethora of functions and pTyr recognition domains are used in a similarly wide range of interaction modes, which encompass, for example, partner protein switching, tandem recognition functionalities and the interaction with catalytically active protein domains. If looked upon closely enough, virtually no pTyr recognition and regulation event is an exact mirror image of another one in the same cell. Thus, the more we learn about the biology and ultrastructural details of pTyr recognition domains, the more does it become apparent that nature cleverly combines and varies a few basic principles to generate a sheer endless number of sophisticated and highly effective recognition/regulation events that are, under normal conditions, elegantly orchestrated in time and space. This knowledge is also valuable when exploring pTyr reader domains as diagnostic tools, drug targets or therapeutic reagents to combat human diseases. PMID:23134684

The recognition and modification sites for the bacterial type I restriction systems KpnAI, StySEAI, StySENI and StySGI

PubMed Central

Kasarjian, Julie K. A.; Hidaka, Masumi; Horiuchi, Takashi; Iida, Masatake; Ryu, Junichi

2004-01-01

Using an in vivo plasmid transformation method, we have determined the DNA sequences recognized by the KpnAI, StySEAI, StySENI and StySGI R-M systems from Klebsiella oxytoca strain M5a1, Salmonella eastbourne, Salmonella enteritidis and Salmonella gelsenkirchen, respectively. These type I restriction-modification systems were originally identified using traditional phage assay, and described here is the plasmid transformation test and computer program used to determine their DNA recognition sequences. For this test, we constructed two sets of plasmids, pL and pE, that contain phage lambda and Escherichia coli K-12 chromosomal DNA fragments, respectively. Further, using the methylation sensitivities of various known type II restriction enzymes, we identified the target adenines for methylation (listed in bold italics below as A or T in case of the complementary strand). The recognition sequence and methylation sites are GAA(6N)TGCC (KpnAI), ACA(6N)TYCA (StySEAI), CGA(6N)TACC (StySENI) and TAAC(7N)RTCG (StySGI). These DNA recognition sequences all have a typical type I bipartite pattern and represent three novel specificities and one isoschizomer (StySENI). For confirmation, oligonucleotides containing each of the predicted sequences were synthesized, cloned into plasmid pMECA and transformed into each strain, resulting in a large reduction in efficiency of transformation (EOT). PMID:15199175

Clinical Validation of Copy Number Variant Detection from Targeted Next-Generation Sequencing Panels.

PubMed

Kerkhof, Jennifer; Schenkel, Laila C; Reilly, Jack; McRobbie, Sheri; Aref-Eshghi, Erfan; Stuart, Alan; Rupar, C Anthony; Adams, Paul; Hegele, Robert A; Lin, Hanxin; Rodenhiser, David; Knoll, Joan; Ainsworth, Peter J; Sadikovic, Bekim

2017-11-01

Next-generation sequencing (NGS) technology has rapidly replaced Sanger sequencing in the assessment of sequence variations in clinical genetics laboratories. One major limitation of current NGS approaches is the ability to detect copy number variations (CNVs) approximately >50 bp. Because these represent a major mutational burden in many genetic disorders, parallel CNV assessment using alternate supplemental methods, along with the NGS analysis, is normally required, resulting in increased labor, costs, and turnaround times. The objective of this study was to clinically validate a novel CNV detection algorithm using targeted clinical NGS gene panel data. We have applied this approach in a retrospective cohort of 391 samples and a prospective cohort of 2375 samples and found a 100% sensitivity (95% CI, 89%-100%) for 37 unique events and a high degree of specificity to detect CNVs across nine distinct targeted NGS gene panels. This NGS CNV pipeline enables stand-alone first-tier assessment for CNV and sequence variants in a clinical laboratory setting, dispensing with the need for parallel CNV analysis using classic techniques, such as microarray, long-range PCR, or multiplex ligation-dependent probe amplification. This NGS CNV pipeline can also be applied to the assessment of complex genomic regions, including pseudogenic DNA sequences, such as the PMS2CL gene, and to mitochondrial genome heteroplasmy detection. Copyright © 2017 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

Multi-source feature extraction and target recognition in wireless sensor networks based on adaptive distributed wavelet compression algorithms

NASA Astrophysics Data System (ADS)

Hortos, William S.

2008-04-01

Proposed distributed wavelet-based algorithms are a means to compress sensor data received at the nodes forming a wireless sensor network (WSN) by exchanging information between neighboring sensor nodes. Local collaboration among nodes compacts the measurements, yielding a reduced fused set with equivalent information at far fewer nodes. Nodes may be equipped with multiple sensor types, each capable of sensing distinct phenomena: thermal, humidity, chemical, voltage, or image signals with low or no frequency content as well as audio, seismic or video signals within defined frequency ranges. Compression of the multi-source data through wavelet-based methods, distributed at active nodes, reduces downstream processing and storage requirements along the paths to sink nodes; it also enables noise suppression and more energy-efficient query routing within the WSN. Targets are first detected by the multiple sensors; then wavelet compression and data fusion are applied to the target returns, followed by feature extraction from the reduced data; feature data are input to target recognition/classification routines; targets are tracked during their sojourns through the area monitored by the WSN. Algorithms to perform these tasks are implemented in a distributed manner, based on a partition of the WSN into clusters of nodes. In this work, a scheme of collaborative processing is applied for hierarchical data aggregation and decorrelation, based on the sensor data itself and any redundant information, enabled by a distributed, in-cluster wavelet transform with lifting that allows multiple levels of resolution. The wavelet-based compression algorithm significantly decreases RF bandwidth and other resource use in target processing tasks. Following wavelet compression, features are extracted. The objective of feature extraction is to maximize the probabilities of correct target classification based on multi-source sensor measurements, while minimizing the resource expenditures at

A Compact Methodology to Understand, Evaluate, and Predict the Performance of Automatic Target Recognition

PubMed Central

Li, Yanpeng; Li, Xiang; Wang, Hongqiang; Chen, Yiping; Zhuang, Zhaowen; Cheng, Yongqiang; Deng, Bin; Wang, Liandong; Zeng, Yonghu; Gao, Lei

2014-01-01

This paper offers a compacted mechanism to carry out the performance evaluation work for an automatic target recognition (ATR) system: (a) a standard description of the ATR system's output is suggested, a quantity to indicate the operating condition is presented based on the principle of feature extraction in pattern recognition, and a series of indexes to assess the output in different aspects are developed with the application of statistics; (b) performance of the ATR system is interpreted by a quality factor based on knowledge of engineering mathematics; (c) through a novel utility called “context-probability” estimation proposed based on probability, performance prediction for an ATR system is realized. The simulation result shows that the performance of an ATR system can be accounted for and forecasted by the above-mentioned measures. Compared to existing technologies, the novel method can offer more objective performance conclusions for an ATR system. These conclusions may be helpful in knowing the practical capability of the tested ATR system. At the same time, the generalization performance of the proposed method is good. PMID:24967605

Integration of targeted sequencing and NIPT into clinical practice in a Chinese family with maple syrup urine disease.

PubMed

You, Yanqin; Sun, Yan; Li, Xuchao; Li, Yali; Wei, Xiaoming; Chen, Fang; Ge, Huijuan; Lan, Zhangzhang; Zhu, Qian; Tang, Ying; Wang, Shujuan; Gao, Ya; Jiang, Fuman; Song, Jiaping; Shi, Quan; Zhu, Xuan; Mu, Feng; Dong, Wei; Gao, Vince; Jiang, Hui; Yi, Xin; Wang, Wei; Gao, Zhiying

2014-08-01

This article demonstrates a prominent noninvasive prenatal approach to assist the clinical diagnosis of a single-gene disorder disease, maple syrup urine disease, using targeted sequencing knowledge from the affected family. The method reported here combines novel mutant discovery in known genes by targeted massively parallel sequencing with noninvasive prenatal testing. By applying this new strategy, we successfully revealed novel mutations in the gene BCKDHA (Ex2_4dup and c.392A>G) in this Chinese family and developed a prenatal haplotype-assisted approach to noninvasively detect the genotype of the fetus (transmitted from both parents). This is the first report of integration of targeted sequencing and noninvasive prenatal testing into clinical practice. Our study has demonstrated that this massively parallel sequencing-based strategy can potentially be used for single-gene disorder diagnosis in the future.

[Screening specific recognition motif of RNA-binding proteins by SELEX in combination with next-generation sequencing technique].

PubMed

Zhang, Lu; Xu, Jinhao; Ma, Jinbiao

2016-07-25

RNA-binding protein exerts important biological function by specifically recognizing RNA motif. SELEX (Systematic evolution of ligands by exponential enrichment), an in vitro selection method, can obtain consensus motif with high-affinity and specificity for many target molecules from DNA or RNA libraries. Here, we combined SELEX with next-generation sequencing to study the protein-RNA interaction in vitro. A pool of RNAs with 20 bp random sequences were transcribed by T7 promoter, and target protein was inserted into plasmid containing SBP-tag, which can be captured by streptavidin beads. Through only one cycle, the specific RNA motif can be obtained, which dramatically improved the selection efficiency. Using this method, we found that human hnRNP A1 RRMs domain (UP1 domain) bound RNA motifs containing AGG and AG sequences. The EMSA experiment indicated that hnRNP A1 RRMs could bind the obtained RNA motif. Taken together, this method provides a rapid and effective method to study the RNA binding specificity of proteins.

Genetic diagnosis of familial hypercholesterolaemia by targeted next-generation sequencing

PubMed Central

Maglio, C; Mancina, R M; Motta, B M; Stef, M; Pirazzi, C; Palacios, L; Askaryar, N; Borén, J; Wiklund, O; Romeo, S

2014-01-01

Maglio C., Mancina R. M., Motta B. M., Stef M., Pirazzi C., Palacios L., Askaryar N., Borén J., Wiklund O., Romeo S. (University of Gothenburg, Gothenburg, Sweden; University Magna Graecia of Catanzaro, Italy; University of Milan, Italy; Progenika Biopharma SA, Derio, Spain). Genetic diagnosis of familial hypercholesterolaemia by targeted next-generation sequencing. Objectives The aim of this study was to combine clinical criteria and next-generation sequencing (pyrosequencing) to establish a diagnosis of familial hypercholesterolaemia (FH). Design, setting and subjects A total of 77 subjects with a Dutch Lipid Clinic Network score of ≥3 (possible, probable or definite FH clinical diagnosis) were recruited from the Lipid Clinic at Sahlgrenska Hospital, Gothenburg, Sweden. Next-generation sequencing was performed in all subjects using SEQPRO LIPO RS, a kit that detects mutations in the low-density lipoprotein receptor (LDLR), apolipoprotein B (APOB), proprotein convertase subtilisin/kexin type 9 (PCSK9) and LDLR adapter protein 1 (LDLRAP1) genes; copy-number variations in the LDLR gene were also examined. Results A total of 26 mutations were detected in 50 subjects (65% success rate). Amongst these, 23 mutations were in the LDLR gene, two in the APOB gene and one in the PCSK9 gene. Four mutations with unknown pathogenicity were detected in LDLR. Of these, three mutations (Gly505Asp, Ile585Thr and Gln660Arg) have been previously reported in subjects with FH, but their pathogenicity has not been proved. The fourth, a mutation in LDLR affecting a splicing site (exon 6–intron 6) has not previously been reported; it was found to segregate with high cholesterol levels in the family of the proband. Conclusions Using a combination of clinical criteria and targeted next-generation sequencing, we have achieved FH diagnosis with a high success rate. Furthermore, we identified a new splicing-site mutation in the LDLR gene. PMID:24785115

Radar HRRP Target Recognition Based on Stacked Autoencoder and Extreme Learning Machine

PubMed Central

Liu, Yongxiang; Huo, Kai; Zhang, Zhongshuai

2018-01-01

A novel radar high-resolution range profile (HRRP) target recognition method based on a stacked autoencoder (SAE) and extreme learning machine (ELM) is presented in this paper. As a key component of deep structure, the SAE does not only learn features by making use of data, it also obtains feature expressions at different levels of data. However, with the deep structure, it is hard to achieve good generalization performance with a fast learning speed. ELM, as a new learning algorithm for single hidden layer feedforward neural networks (SLFNs), has attracted great interest from various fields for its fast learning speed and good generalization performance. However, ELM needs more hidden nodes than conventional tuning-based learning algorithms due to the random set of input weights and hidden biases. In addition, the existing ELM methods cannot utilize the class information of targets well. To solve this problem, a regularized ELM method based on the class information of the target is proposed. In this paper, SAE and the regularized ELM are combined to make full use of their advantages and make up for each of their shortcomings. The effectiveness of the proposed method is demonstrated by experiments with measured radar HRRP data. The experimental results show that the proposed method can achieve good performance in the two aspects of real-time and accuracy, especially when only a few training samples are available. PMID:29320453

Radar HRRP Target Recognition Based on Stacked Autoencoder and Extreme Learning Machine.

PubMed

Zhao, Feixiang; Liu, Yongxiang; Huo, Kai; Zhang, Shuanghui; Zhang, Zhongshuai

2018-01-10

A novel radar high-resolution range profile (HRRP) target recognition method based on a stacked autoencoder (SAE) and extreme learning machine (ELM) is presented in this paper. As a key component of deep structure, the SAE does not only learn features by making use of data, it also obtains feature expressions at different levels of data. However, with the deep structure, it is hard to achieve good generalization performance with a fast learning speed. ELM, as a new learning algorithm for single hidden layer feedforward neural networks (SLFNs), has attracted great interest from various fields for its fast learning speed and good generalization performance. However, ELM needs more hidden nodes than conventional tuning-based learning algorithms due to the random set of input weights and hidden biases. In addition, the existing ELM methods cannot utilize the class information of targets well. To solve this problem, a regularized ELM method based on the class information of the target is proposed. In this paper, SAE and the regularized ELM are combined to make full use of their advantages and make up for each of their shortcomings. The effectiveness of the proposed method is demonstrated by experiments with measured radar HRRP data. The experimental results show that the proposed method can achieve good performance in the two aspects of real-time and accuracy, especially when only a few training samples are available.

Molecular basis for the wide range of affinity found in Csr/Rsm protein-RNA recognition.

PubMed

Duss, Olivier; Michel, Erich; Diarra dit Konté, Nana; Schubert, Mario; Allain, Frédéric H-T

2014-04-01

The carbon storage regulator/regulator of secondary metabolism (Csr/Rsm) type of small non-coding RNAs (sRNAs) is widespread throughout bacteria and acts by sequestering the global translation repressor protein CsrA/RsmE from the ribosome binding site of a subset of mRNAs. Although we have previously described the molecular basis of a high affinity RNA target bound to RsmE, it remains unknown how other lower affinity targets are recognized by the same protein. Here, we have determined the nuclear magnetic resonance solution structures of five separate GGA binding motifs of the sRNA RsmZ of Pseudomonas fluorescens in complex with RsmE. The structures explain how the variation of sequence and structural context of the GGA binding motifs modulate the binding affinity for RsmE by five orders of magnitude (∼10 nM to ∼3 mM, Kd). Furthermore, we see that conformational adaptation of protein side-chains and RNA enable recognition of different RNA sequences by the same protein contributing to binding affinity without conferring specificity. Overall, our findings illustrate how the variability in the Csr/Rsm protein-RNA recognition allows a fine-tuning of the competition between mRNAs and sRNAs for the CsrA/RsmE protein.

Songbirds use spectral shape, not pitch, for sound pattern recognition

PubMed Central

Bregman, Micah R.; Patel, Aniruddh D.; Gentner, Timothy Q.

2016-01-01

Humans easily recognize “transposed” musical melodies shifted up or down in log frequency. Surprisingly, songbirds seem to lack this capacity, although they can learn to recognize human melodies and use complex acoustic sequences for communication. Decades of research have led to the widespread belief that songbirds, unlike humans, are strongly biased to use absolute pitch (AP) in melody recognition. This work relies almost exclusively on acoustically simple stimuli that may belie sensitivities to more complex spectral features. Here, we investigate melody recognition in a species of songbird, the European Starling (Sturnus vulgaris), using tone sequences that vary in both pitch and timbre. We find that small manipulations altering either pitch or timbre independently can drive melody recognition to chance, suggesting that both percepts are poor descriptors of the perceptual cues used by birds for this task. Instead we show that melody recognition can generalize even in the absence of pitch, as long as the spectral shapes of the constituent tones are preserved. These results challenge conventional views regarding the use of pitch cues in nonhuman auditory sequence recognition. PMID:26811447

Colorimetric biosensing of targeted gene sequence using dual nanoparticle platforms

PubMed Central

Thavanathan, Jeevan; Huang, Nay Ming; Thong, Kwai Lin

2015-01-01

We have developed a colorimetric biosensor using a dual platform of gold nanoparticles and graphene oxide sheets for the detection of Salmonella enterica. The presence of the invA gene in S. enterica causes a change in color of the biosensor from its original pinkish-red to a light purplish solution. This occurs through the aggregation of the primary gold nanoparticles–conjugated DNA probe onto the surface of the secondary graphene oxide–conjugated DNA probe through DNA hybridization with the targeted DNA sequence. Spectrophotometry analysis showed a shift in wavelength from 525 nm to 600 nm with 1 μM of DNA target. Specificity testing revealed that the biosensor was able to detect various serovars of the S. enterica while no color change was observed with the other bacterial species. Sensitivity testing revealed the limit of detection was at 1 nM of DNA target. This proves the effectiveness of the biosensor in the detection of S. enterica through DNA hybridization. PMID:25897217

Sequence-based design of bioactive small molecules that target precursor microRNAs.

PubMed

Velagapudi, Sai Pradeep; Gallo, Steven M; Disney, Matthew D

2014-04-01

Oligonucleotides are designed to target RNA using base pairing rules, but they can be hampered by poor cellular delivery and nonspecific stimulation of the immune system. Small molecules are preferred as lead drugs or probes but cannot be designed from sequence. Herein, we describe an approach termed Inforna that designs lead small molecules for RNA from solely sequence. Inforna was applied to all human microRNA hairpin precursors, and it identified bioactive small molecules that inhibit biogenesis by binding nuclease-processing sites (44% hit rate). Among 27 lead interactions, the most avid interaction is between a benzimidazole (1) and precursor microRNA-96. Compound 1 selectively inhibits biogenesis of microRNA-96, upregulating a protein target (FOXO1) and inducing apoptosis in cancer cells. Apoptosis is ablated when FOXO1 mRNA expression is knocked down by an siRNA, validating compound selectivity. Markedly, microRNA profiling shows that 1 only affects microRNA-96 biogenesis and is at least as selective as an oligonucleotide.

Sequence-based design of bioactive small molecules that target precursor microRNAs

PubMed Central

Velagapudi, Sai Pradeep; Gallo, Steven M.; Disney, Matthew D.

2014-01-01

Oligonucleotides are designed to target RNA using base pairing rules, however, they are hampered by poor cellular delivery and non-specific stimulation of the immune system. Small molecules are preferred as lead drugs or probes, but cannot be designed from sequence. Herein, we describe an approach termed Inforna that designs lead small molecules for RNA from solely sequence. Inforna was applied to all human microRNA precursors and identified bioactive small molecules that inhibit biogenesis by binding to nuclease processing sites (41% hit rate). Amongst 29 lead interactions, the most avid interaction is between a benzimidazole (1) and precursor microRNA-96. Compound 1 selectively inhibits biogenesis of microRNA-96, upregulating a protein target (FOXO1) and inducing apoptosis in cancer cells. Apoptosis is ablated when FOXO1 mRNA expression is knocked down by an siRNA, validating compound selectivity. Importantly, microRNA profiling shows that 1 only significantly effects microRNA-96 biogenesis and is more selective than an oligonucleotide. PMID:24509821

Two-Way Gold Nanoparticle Label-Free Sensing of Specific Sequence and Small Molecule Targets Using Switchable Concatemers.

PubMed

Zhu, Longjiao; Shao, Xiangli; Luo, Yunbo; Huang, Kunlung; Xu, Wentao

2017-05-19

A two-way colorimetric biosensor based on unmodified gold nanoparticles (GNPs) and a switchable double-stranded DNA (dsDNA) concatemer have been demonstrated. Two hairpin probes (H1 and H2) were first designed that provided the fuels to assemble the dsDNA concatemers via hybridization chain reaction (HCR). A functional hairpin (FH) was rationally designed to recognize the target sequences. All the hairpins contained a single-stranded DNA (ssDNA) loop and sticky end to prevent GNPs from salt-induced aggregation. In the presence of target sequence, the capture probe blocked in the FH recognizes the target to form a duplex DNA, which causes the release of the initiator probe by FH conformational change. This process then starts the alternate-opening of H1 and H2 through HCR, and dsDNA concatemers grow from the target sequence. As a result, unmodified GNPs undergo salt-induced aggregation because the formed dsDNA concatemers are stiffer and provide less stabilization. A light purple-to-blue color variation was observed in the bulk solution, termed the light-off sensing way. Furthermore, H1 ingeniously inserted an aptamer sequence to generate dsDNA concatemers with multiple small molecule binding sites. In the presence of small molecule targets, concatemers can be disassembled into mixtures with ssDNA sticky ends. A blue-to-purple reverse color variation was observed due to the regeneration of the ssDNA, termed the light-on way. The two-way biosensor can detect both nucleic acids and small molecule targets with one sensing device. This switchable sensing element is label-free, enzyme-free, and sophisticated-instrumentation-free. The detection limits of both targets were below nanomolar.

RNA editing of microRNA prevents RNA-induced silencing complex recognition of target mRNA

PubMed Central

Cui, Yalei; Huang, Tianzhi; Zhang, Xiaobo

2015-01-01

MicroRNAs (miRNAs) integrate with Argonaut (Ago) to create the RNA-induced silencing complex, and regulate gene expression by silencing target mRNAs. RNA editing of miRNA may affect miRNA processing, assembly of the Ago complex and target mRNA binding. However, the function of edited miRNA, assembled within the Ago complex, has not been extensively investigated. In this study, sequence analysis of the Ago complex of Marsupenaeus japonicus shrimp infected with white spot syndrome virus (WSSV) revealed that host ADAR (adenosine deaminase acting on RNA) catalysed A-to-I RNA editing of a viral miRNA (WSSV-miR-N12) at the +16 site. This editing of the non-seed sequence did not affect association of the edited miRNA with the Ago protein, but inhibited interaction between the miRNA and its target gene (wsv399). The WSSV early gene wsv399 inhibited WSSV infection. As a result, the RNA editing of miRNA caused virus latency. Our results highlight a novel example of miRNA editing in the miRNA-induced silencing complex. PMID:26674414

Determinants for DNA target structure selectivity of the human LINE-1 retrotransposon endonuclease.

PubMed

Repanas, Kostas; Zingler, Nora; Layer, Liliana E; Schumann, Gerald G; Perrakis, Anastassis; Weichenrieder, Oliver

2007-01-01

The human LINE-1 endonuclease (L1-EN) is the targeting endonuclease encoded by the human LINE-1 (L1) retrotransposon. L1-EN guides the genomic integration of new L1 and Alu elements that presently account for approximately 28% of the human genome. L1-EN bears considerable technological interest, because its target selectivity may ultimately be engineered to allow the site-specific integration of DNA into defined genomic locations. Based on the crystal structure, we generated L1-EN mutants to analyze and manipulate DNA target site recognition. Crystal structures and their dynamic and functional analysis show entire loop grafts to be feasible, resulting in altered specificity, while individual point mutations do not change the nicking pattern of L1-EN. Structural parameters of the DNA target seem more important for recognition than the nucleotide sequence, and nicking profiles on DNA oligonucleotides in vitro are less well defined than the respective integration site consensus in vivo. This suggests that additional factors other than the DNA nicking specificity of L1-EN contribute to the targeted integration of non-LTR retrotransposons.

Facial Affect Recognition in Violent and Nonviolent Antisocial Behavior Subtypes.

PubMed

Schönenberg, Michael; Mayer, Sarah Verena; Christian, Sandra; Louis, Katharina; Jusyte, Aiste

2016-10-01

Prior studies provide evidence for impaired recognition of distress cues in individuals exhibiting antisocial behavior. However, it remains unclear whether this deficit is generally associated with antisociality or may be specific to violent behavior only. To examine whether there are meaningful differences between the two behavioral dimensions rule-breaking and aggression, violent and nonviolent incarcerated offenders as well as control participants were presented with an animated face recognition task in which a video sequence of a neutral face changed into an expression of one of the six basic emotions. The participants were instructed to press a button as soon as they were able to identify the emotional expression, allowing for an assessment of the perceived emotion onset. Both aggressive and nonaggressive offenders demonstrated a delayed perception of primarily fearful facial cues as compared to controls. These results suggest the importance of targeting impaired emotional processing in both types of antisocial behavior.

Optical implementation of a feature-based neural network with application to automatic target recognition

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Stoner, William W.

1993-01-01

An optical neural network based on the neocognitron paradigm is introduced. A novel aspect of the architecture design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by feeding back the ouput of the feature correlator interatively to the input spatial light modulator and by updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intraclass fault tolerance and interclass discrimination is achieved. A detailed system description is provided. Experimental demonstrations of a two-layer neural network for space-object discrimination is also presented.

Captured metagenomics: large-scale targeting of genes based on ‘sequence capture’ reveals functional diversity in soils

PubMed Central

Manoharan, Lokeshwaran; Kushwaha, Sandeep K.; Hedlund, Katarina; Ahrén, Dag

2015-01-01

Microbial enzyme diversity is a key to understand many ecosystem processes. Whole metagenome sequencing (WMG) obtains information on functional genes, but it is costly and inefficient due to large amount of sequencing that is required. In this study, we have applied a captured metagenomics technique for functional genes in soil microorganisms, as an alternative to WMG. Large-scale targeting of functional genes, coding for enzymes related to organic matter degradation, was applied to two agricultural soil communities through captured metagenomics. Captured metagenomics uses custom-designed, hybridization-based oligonucleotide probes that enrich functional genes of interest in metagenomic libraries where only probe-bound DNA fragments are sequenced. The captured metagenomes were highly enriched with targeted genes while maintaining their target diversity and their taxonomic distribution correlated well with the traditional ribosomal sequencing. The captured metagenomes were highly enriched with genes related to organic matter degradation; at least five times more than similar, publicly available soil WMG projects. This target enrichment technique also preserves the functional representation of the soils, thereby facilitating comparative metagenomics projects. Here, we present the first study that applies the captured metagenomics approach in large scale, and this novel method allows deep investigations of central ecosystem processes by studying functional gene abundances. PMID:26490729

A robust algorithm for automated target recognition using precomputed radar cross sections

NASA Astrophysics Data System (ADS)

Ehrman, Lisa M.; Lanterman, Aaron D.

2004-09-01

Passive radar is an emerging technology that offers a number of unique benefits, including covert operation. Many such systems are already capable of detecting and tracking aircraft. The goal of this work is to develop a robust algorithm for adding automated target recognition (ATR) capabilities to existing passive radar systems. In previous papers, we proposed conducting ATR by comparing the precomputed RCS of known targets to that of detected targets. To make the precomputed RCS as accurate as possible, a coordinated flight model is used to estimate aircraft orientation. Once the aircraft's position and orientation are known, it is possible to determine the incident and observed angles on the aircraft, relative to the transmitter and receiver. This makes it possible to extract the appropriate radar cross section (RCS) from our simulated database. This RCS is then scaled to account for propagation losses and the receiver's antenna gain. A Rician likelihood model compares these expected signals from different targets to the received target profile. We have previously employed Monte Carlo runs to gauge the probability of error in the ATR algorithm; however, generation of a statistically significant set of Monte Carlo runs is computationally intensive. As an alternative to Monte Carlo runs, we derive the relative entropy (also known as Kullback-Liebler distance) between two Rician distributions. Since the probability of Type II error in our hypothesis testing problem can be expressed as a function of the relative entropy via Stein's Lemma, this provides us with a computationally efficient method for determining an upper bound on our algorithm's performance. It also provides great insight into the types of classification errors we can expect from our algorithm. This paper compares the numerically approximated probability of Type II error with the results obtained from a set of Monte Carlo runs.

Whole CMV Proteome Pattern Recognition Analysis after HSCT Identifies Unique Epitope Targets Associated with the CMV Status

PubMed Central

Pérez-Bercoff, Lena; Valentini, Davide; Gaseitsiwe, Simani; Mahdavifar, Shahnaz; Schutkowski, Mike; Poiret, Thomas; Pérez-Bercoff, Åsa; Ljungman, Per; Maeurer, Markus J.

2014-01-01

Cytomegalovirus (CMV) infection represents a vital complication after Hematopoietic Stem Cell Transplantation (HSCT). We screened the entire CMV proteome to visualize the humoral target epitope-focus profile in serum after HSCT. IgG profiling from four patient groups (donor and/or recipient +/− for CMV) was performed at 6, 12 and 24 months after HSCT using microarray slides containing 17174 of 15mer-peptides overlapping by 4 aa covering 214 proteins from CMV. Data were analyzed using maSigPro, PAM and the ‘exclusive recognition analysis (ERA)’ to identify unique CMV epitope responses for each patient group. The ‘exclusive recognition analysis’ of serum epitope patterns segregated best 12 months after HSCT for the D+/R+ group (versus D−/R−). Epitopes were derived from UL123 (IE1), UL99 (pp28), UL32 (pp150), this changed at 24 months to 2 strongly recognized peptides provided from UL123 and UL100. Strongly (IgG) recognized CMV targets elicited also robust cytokine production in T-cells from patients after HSCT defined by intracellular cytokine staining (IL-2, TNF, IFN and IL-17). High-content peptide microarrays allow epitope profiling of entire viral proteomes; this approach can be useful to map relevant targets for diagnostics and therapy in patients with well defined clinical endpoints. Peptide microarray analysis visualizes the breadth of B-cell immune reconstitution after HSCT and provides a useful tool to gauge immune reconstitution. PMID:24740411

Automatic target recognition and detection in infrared imagery under cluttered background

NASA Astrophysics Data System (ADS)

Gundogdu, Erhan; Koç, Aykut; Alatan, A. Aydın.

2017-10-01

Visual object classification has long been studied in visible spectrum by utilizing conventional cameras. Since the labeled images has recently increased in number, it is possible to train deep Convolutional Neural Networks (CNN) with significant amount of parameters. As the infrared (IR) sensor technology has been improved during the last two decades, labeled images extracted from IR sensors have been started to be used for object detection and recognition tasks. We address the problem of infrared object recognition and detection by exploiting 15K images from the real-field with long-wave and mid-wave IR sensors. For feature learning, a stacked denoising autoencoder is trained in this IR dataset. To recognize the objects, the trained stacked denoising autoencoder is fine-tuned according to the binary classification loss of the target object. Once the training is completed, the test samples are propagated over the network, and the probability of the test sample belonging to a class is computed. Moreover, the trained classifier is utilized in a detect-by-classification method, where the classification is performed in a set of candidate object boxes and the maximum confidence score in a particular location is accepted as the score of the detected object. To decrease the computational complexity, the detection step at every frame is avoided by running an efficient correlation filter based tracker. The detection part is performed when the tracker confidence is below a pre-defined threshold. The experiments conducted on the real field images demonstrate that the proposed detection and tracking framework presents satisfactory results for detecting tanks under cluttered background.

Heterologous mitochondrial targeting sequences can deliver functional proteins into mitochondria.

PubMed

Marcus, Dana; Lichtenstein, Michal; Cohen, Natali; Hadad, Rita; Erlich-Hadad, Tal; Greif, Hagar; Lorberboum-Galski, Haya

2016-12-01

Mitochondrial Targeting Sequences (MTSs) are responsible for trafficking nuclear-encoded proteins into mitochondria. Once entering the mitochondria, the MTS is recognized and cleaved off. Some MTSs are long and undergo two-step processing, as in the case of the human frataxin (FXN) protein (80aa), implicated in Friedreich's ataxia (FA). Therefore, we chose the FXN protein to examine whether nuclear-encoded mitochondrial proteins can efficiently be targeted via a heterologous MTS (hMTS) and deliver a functional protein into mitochondria. We examined three hMTSs; that of citrate synthase (cs), lipoamide deydrogenase (LAD) and C6ORF66 (ORF), as classically MTS sequences, known to be removed by one-step processing, to deliver FXN into mitochondria, in the form of fusion proteins. We demonstrate that using hMTSs for delivering FXN results in the production of 4-5-fold larger amounts of the fusion proteins, and at 4-5-fold higher concentrations. Moreover, hMTSs delivered a functional FXN protein into the mitochondria even more efficiently than the native MTSfxn, as evidenced by the rescue of FA patients' cells from oxidative stress; demonstrating a 18%-54% increase in cell survival; and a 13%-33% increase in ATP levels, as compared to the fusion protein carrying the native MTS. One fusion protein with MTScs increased aconitase activity within patients' cells, by 400-fold. The implications form our studies are of vast importance for both basic and translational research of mitochondrial proteins as any mitochondrial protein can be delivered efficiently by an hMTS. Moreover, effective targeting of functional proteins is important for restoration of mitochondrial function and treatment of related disorders. Copyright © 2016 Elsevier Ltd. All rights reserved.

An SRY mutation causing human sex reversal resolves a general mechanism of structure-specific DNA recognition: application to the four-way DNA junction.

PubMed

Peters, R; King, C Y; Ukiyama, E; Falsafi, S; Donahoe, P K; Weiss, M A

1995-04-11

SRY, a genetic "master switch" for male development in mammals, exhibits two biochemical activities: sequence-specific recognition of duplex DNA and sequence-independent binding to the sharp angles of four-way DNA junctions. Here, we distinguish between these activities by analysis of a mutant SRY associated with human sex reversal (46, XY female with pure gonadal dysgenesis). The substitution (168T in human SRY) alters a nonpolar side chain in the minor-groove DNA recognition alpha-helix of the HMG box [Haqq, C.M., King, C.-Y., Ukiyama, E., Haqq, T.N., Falsalfi, S., Donahoe, P.K., & Weiss, M.A. (1994) Science 266, 1494-1500]. The native (but not mutant) side chain inserts between specific base pairs in duplex DNA, interrupting base stacking at a site of induced DNA bending. Isotope-aided 1H-NMR spectroscopy demonstrates that analogous side-chain insertion occurs on binding of SRY to a four-way junction, establishing a shared mechanism of sequence- and structure-specific DNA binding. Although the mutant DNA-binding domain exhibits > 50-fold reduction in sequence-specific DNA recognition, near wild-type affinity for four-way junctions is retained. Our results (i) identify a shared SRY-DNA contact at a site of either induced or intrinsic DNA bending, (ii) demonstrate that this contact is not required to bind an intrinsically bent DNA target, and (iii) rationalize patterns of sequence conservation or diversity among HMG boxes. Clinical association of the I68T mutation with human sex reversal supports the hypothesis that specific DNA recognition by SRY is required for male sex determination.

Structural basis of DNA folding and recognition in an AMP-DNA aptamer complex: distinct architectures but common recognition motifs for DNA and RNA aptamers complexed to AMP.

PubMed

Lin, C H; Patel, D J

1997-11-01

Structural studies by nuclear magnetic resonance (NMR) of RNA and DNA aptamer complexes identified through in vitro selection and amplification have provided a wealth of information on RNA and DNA tertiary structure and molecular recognition in solution. The RNA and DNA aptamers that target ATP (and AMP) with micromolar affinity exhibit distinct binding site sequences and secondary structures. We report below on the tertiary structure of the AMP-DNA aptamer complex in solution and compare it with the previously reported tertiary structure of the AMP-RNA aptamer complex in solution. The solution structure of the AMP-DNA aptamer complex shows, surprisingly, that two AMP molecules are intercalated at adjacent sites within a rectangular widened minor groove. Complex formation involves adaptive binding where the asymmetric internal bubble of the free DNA aptamer zippers up through formation of a continuous six-base mismatch segment which includes a pair of adjacent three-base platforms. The AMP molecules pair through their Watson-Crick edges with the minor groove edges of guanine residues. These recognition G.A mismatches are flanked by sheared G.A and reversed Hoogsteen G.G mismatch pairs. The AMP-DNA aptamer and AMP-RNA aptamer complexes have distinct tertiary structures and binding stoichiometries. Nevertheless, both complexes have similar structural features and recognition alignments in their binding pockets. Specifically, AMP targets both DNA and RNA aptamers by intercalating between purine bases and through identical G.A mismatch formation. The recognition G.A mismatch stacks with a reversed Hoogsteen G.G mismatch in one direction and with an adenine base in the other direction in both complexes. It is striking that DNA and RNA aptamers selected independently from libraries of 10(14) molecules in each case utilize identical mismatch alignments for molecular recognition with micromolar affinity within binding-site pockets containing common structural elements.

Synthesis of mouse centromere-targeted polyamides and physico-chemical studies of their interaction with the target double-stranded DNA.

PubMed

Nozeret, Karine; Bonan, Marc; Yarmoluk, Serguiy M; Novopashina, Darya S; Boutorine, Alexandre S

2015-09-01

Synthetic minor groove-binding pyrrole-imidazole polyamides labeled by fluorophores are promising candidates for fluorescence imaging of double-stranded DNA in isolated chromosomes or fixed and living cells. We synthesized nine hairpin and two head-to-head tandem polyamides targeting repeated sequences from mouse major satellites. Their interaction with synthetic target dsDNA has been studied by physico-chemical methods in vitro before and after coupling to various fluorophores. Great variability in affinities and fluorescence properties reveals a conclusion that these properties do not only rely on recognition rules, but also on other known and unknown structural factors. Individual testing of each probe is needed before cellular applications. Copyright © 2015 Elsevier Ltd. All rights reserved.

Hierarchical Context Modeling for Video Event Recognition.

PubMed

Wang, Xiaoyang; Ji, Qiang

2016-10-11

Current video event recognition research remains largely target-centered. For real-world surveillance videos, targetcentered event recognition faces great challenges due to large intra-class target variation, limited image resolution, and poor detection and tracking results. To mitigate these challenges, we introduced a context-augmented video event recognition approach. Specifically, we explicitly capture different types of contexts from three levels including image level, semantic level, and prior level. At the image level, we introduce two types of contextual features including the appearance context features and interaction context features to capture the appearance of context objects and their interactions with the target objects. At the semantic level, we propose a deep model based on deep Boltzmann machine to learn event object representations and their interactions. At the prior level, we utilize two types of prior-level contexts including scene priming and dynamic cueing. Finally, we introduce a hierarchical context model that systematically integrates the contextual information at different levels. Through the hierarchical context model, contexts at different levels jointly contribute to the event recognition. We evaluate the hierarchical context model for event recognition on benchmark surveillance video datasets. Results show that incorporating contexts in each level can improve event recognition performance, and jointly integrating three levels of contexts through our hierarchical model achieves the best performance.

Crystal structure and novel recognition motif of rho ADP-ribosylating C3 exoenzyme from Clostridium botulinum: structural insights for recognition specificity and catalysis.

PubMed

Han, S; Arvai, A S; Clancy, S B; Tainer, J A

2001-01-05

Clostridium botulinum C3 exoenzyme inactivates the small GTP-binding protein family Rho by ADP-ribosylating asparagine 41, which depolymerizes the actin cytoskeleton. C3 thus represents a major family of the bacterial toxins that transfer the ADP-ribose moiety of NAD to specific amino acids in acceptor proteins to modify key biological activities in eukaryotic cells, including protein synthesis, differentiation, transformation, and intracellular signaling. The 1.7 A resolution C3 exoenzyme structure establishes the conserved features of the core NAD-binding beta-sandwich fold with other ADP-ribosylating toxins despite little sequence conservation. Importantly, the central core of the C3 exoenzyme structure is distinguished by the absence of an active site loop observed in many other ADP-ribosylating toxins. Unlike the ADP-ribosylating toxins that possess the active site loop near the central core, the C3 exoenzyme replaces the active site loop with an alpha-helix, alpha3. Moreover, structural and sequence similarities with the catalytic domain of vegetative insecticidal protein 2 (VIP2), an actin ADP-ribosyltransferase, unexpectedly implicates two adjacent, protruding turns, which join beta5 and beta6 of the toxin core fold, as a novel recognition specificity motif for this newly defined toxin family. Turn 1 evidently positions the solvent-exposed, aromatic side-chain of Phe209 to interact with the hydrophobic region of Rho adjacent to its GTP-binding site. Turn 2 evidently both places the Gln212 side-chain for hydrogen bonding to recognize Rho Asn41 for nucleophilic attack on the anomeric carbon of NAD ribose and holds the key Glu214 catalytic side-chain in the adjacent catalytic pocket. This proposed bipartite ADP-ribosylating toxin turn-turn (ARTT) motif places the VIP2 and C3 toxin classes into a single ARTT family characterized by analogous target protein recognition via turn 1 aromatic and turn 2 hydrogen-bonding side-chain moieties. Turn 2 centrally anchors

Computational optimisation of targeted DNA sequencing for cancer detection

NASA Astrophysics Data System (ADS)

Martinez, Pierre; McGranahan, Nicholas; Birkbak, Nicolai Juul; Gerlinger, Marco; Swanton, Charles

2013-12-01

Despite recent progress thanks to next-generation sequencing technologies, personalised cancer medicine is still hampered by intra-tumour heterogeneity and drug resistance. As most patients with advanced metastatic disease face poor survival, there is need to improve early diagnosis. Analysing circulating tumour DNA (ctDNA) might represent a non-invasive method to detect mutations in patients, facilitating early detection. In this article, we define reduced gene panels from publicly available datasets as a first step to assess and optimise the potential of targeted ctDNA scans for early tumour detection. Dividing 4,467 samples into one discovery and two independent validation cohorts, we show that up to 76% of 10 cancer types harbour at least one mutation in a panel of only 25 genes, with high sensitivity across most tumour types. Our analyses demonstrate that targeting ``hotspot'' regions would introduce biases towards in-frame mutations and would compromise the reproducibility of tumour detection.

Targeted cancer exome sequencing reveals recurrent mutations in myeloproliferative neoplasms

PubMed Central

Tenedini, E; Bernardis, I; Artusi, V; Artuso, L; Roncaglia, E; Guglielmelli, P; Pieri, L; Bogani, C; Biamonte, F; Rotunno, G; Mannarelli, C; Bianchi, E; Pancrazzi, A; Fanelli, T; Malagoli Tagliazucchi, G; Ferrari, S; Manfredini, R; Vannucchi, A M; Tagliafico, E

2014-01-01

With the intent of dissecting the molecular complexity of Philadelphia-negative myeloproliferative neoplasms (MPN), we designed a target enrichment panel to explore, using next-generation sequencing (NGS), the mutational status of an extensive list of 2000 cancer-associated genes and microRNAs. The genomic DNA of granulocytes and in vitro-expanded CD3+T-lymphocytes, as a germline control, was target-enriched and sequenced in a learning cohort of 20 MPN patients using Roche 454 technology. We identified 141 genuine somatic mutations, most of which were not previously described. To test the frequency of the identified variants, a larger validation cohort of 189 MPN patients was additionally screened for these mutations using Ion Torrent AmpliSeq NGS. Excluding the genes already described in MPN, for 8 genes (SCRIB, MIR662, BARD1, TCF12, FAT4, DAP3, POLG and NRAS), we demonstrated a mutation frequency between 3 and 8%. We also found that mutations at codon 12 of NRAS (NRASG12V and NRASG12D) were significantly associated, for primary myelofibrosis (PMF), with highest dynamic international prognostic scoring system (DIPSS)-plus score categories. This association was then confirmed in 66 additional PMF patients composing a final dataset of 168 PMF showing a NRAS mutation frequency of 4.7%, which was associated with a worse outcome, as defined by the DIPSS plus score. PMID:24150215

Retrotransposon insertion targeting: a mechanism for homogenization of centromere sequences on nonhomologous chromosomes.

PubMed

Birchler, James A; Presting, Gernot G

2012-04-01

The centromeres of most eukaryotic organisms consist of highly repetitive arrays that are similar across nonhomologous chromosomes. These sequences evolve rapidly, thus posing a mystery as to how such arrays can be homogenized. Recent work in species in which centromere-enriched retrotransposons occur indicates that these elements preferentially insert into the centromeric regions. In two different Arabidopsis species, a related element was recognized in which the specificity for such targeting was altered. These observations provide a partial explanation for how homogenization of centromere DNA sequences occurs.

Structure of the PSD-95/MAP1A complex reveals a unique target recognition mode of the MAGUK GK domain.

PubMed

Xia, Yitian; Shang, Yuan; Zhang, Rongguang; Zhu, Jinwei

2017-08-10

The PSD-95 family of membrane-associated guanylate kinases (MAGUKs) are major synaptic scaffold proteins and play crucial roles in the dynamic regulation of dendritic remodelling, which is understood to be the foundation of synaptogenesis and synaptic plasticity. The guanylate kinase (GK) domain of MAGUK family proteins functions as a phosphor-peptide binding module. However, the GK domain of PSD-95 has been found to directly bind to a peptide sequence within the C-terminal region of neuronal-specific microtubule-associated protein 1A (MAP1A), although the detailed molecular mechanism governing this phosphorylation-independent interaction at the atomic level is missing. In the present study, we determine the crystal structure of PSD-95 GK in complex with the MAP1A peptide at 2.6-Å resolution. The complex structure reveals that, unlike a linear and elongated conformation in the phosphor-peptide/GK complexes, the MAP1A peptide adopts a unique conformation with a stretch of hydrophobic residues far from each other in the primary sequence clustering and interacting with the 'hydrophobic site' of PSD-95 GK and a highly conserved aspartic acid of MAP1A (D2117) mimicking the phosphor-serine/threonine in binding to the 'phosphor-site' of PSD-95 GK. We demonstrate that the MAP1A peptide may undergo a conformational transition upon binding to PSD-95 GK. Further structural comparison of known DLG GK-mediated complexes reveals the target recognition specificity and versatility of DLG GKs. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

Control of working memory: effects of attention training on target recognition and distractor salience in an auditory selection task.

PubMed

Melara, Robert D; Tong, Yunxia; Rao, Aparna

2012-01-09

Behavioral and electrophysiological measures of target and distractor processing were examined in an auditory selective attention task before and after three weeks of distractor suppression training. Behaviorally, training improved target recognition and led to less conservative and more rapid responding. Training also effectively shortened the temporal distance between distractors and targets needed to achieve a fixed level of target sensitivity. The effects of training on event-related potentials were restricted to the distracting stimulus: earlier N1 latency, enhanced P2 amplitude, and weakened P3 amplitude. Nevertheless, as distractor P2 amplitude increased, so too did target P3 amplitude, connecting experience-dependent changes in distractor processing with greater distinctiveness of targets in working memory. We consider the effects of attention training on the processing priorities, representational noise, and inhibitory processes operating in working memory. Copyright © 2011 Elsevier B.V. All rights reserved.

Sensitive and Specific Target Sequences Selected from Retrotransposons of Schistosoma japonicum for the Diagnosis of Schistosomiasis

PubMed Central

Xu, Jing; Zhu, Xing-Quan; Wang, Sheng-Yue; Xia, Chao-Ming

2012-01-01

Background Schistosomiasis japonica is a serious debilitating and sometimes fatal disease. Accurate diagnostic tests play a key role in patient management and control of the disease. However, currently available diagnostic methods are not ideal, and the detection of the parasite DNA in blood samples has turned out to be one of the most promising tools for the diagnosis of schistosomiasis. In our previous investigations, a 230-bp sequence from the highly repetitive retrotransposon SjR2 was identified and it showed high sensitivity and specificity for detecting Schistosoma japonicum DNA in the sera of rabbit model and patients. Recently, 29 retrotransposons were found in S. japonicum genome by our group. The present study highlighted the key factors for selecting a new perspective sensitive target DNA sequence for the diagnosis of schistosomiasis, which can serve as example for other parasitic pathogens. Methodology/Principal Findings In this study, we demonstrated that the key factors based on the bioinformatic analysis for selecting target sequence are the higher genome proportion, repetitive complete copies and partial copies, and active ESTs than the others in the chromosome genome. New primers based on 25 novel retrotransposons and SjR2 were designed and their sensitivity and specificity for detecting S. japonicum DNA were compared. The results showed that a new 303-bp sequence from non-long terminal repeat (LTR) retrotransposon (SjCHGCS19) had high sensitivity and specificity. The 303-bp target sequence was amplified from the sera of rabbit model at 3 d post-infection by nested-PCR and it became negative at 17 weeks post-treatment. Furthermore, the percentage sensitivity of the nested-PCR was 97.67% in 43 serum samples of S. japonicum-infected patients. Conclusions/Significance Our findings highlighted the key factors based on the bioinformatic analysis for selecting target sequence from S. japonicum genome, which provide basis for establishing powerful

Intact suppression of increased false recognition in schizophrenia.

PubMed

Weiss, Anthony P; Dodson, Chad S; Goff, Donald C; Schacter, Daniel L; Heckers, Stephan

2002-09-01

Recognition memory is impaired in patients with schizophrenia, as they rely largely on item familiarity, rather than conscious recollection, to make mnemonic decisions. False recognition of novel items (foils) is increased in schizophrenia and may relate to this deficit in conscious recollection. By studying pictures of the target word during encoding, healthy adults can suppress false recognition. This study examined the effect of pictorial encoding on subsequent recognition of repeated foils in patients with schizophrenia. The study included 40 patients with schizophrenia and 32 healthy comparison subjects. After incidental encoding of 60 words or pictures, subjects were tested for recognition of target items intermixed with 60 new foils. These new foils were subsequently repeated following either a two- or 24-word delay. Subjects were instructed to label these repeated foils as new and not to mistake them for old target words. Schizophrenic patients showed greater overall false recognition of repeated foils. The rate of false recognition of repeated foils was lower after picture encoding than after word encoding. Despite higher levels of false recognition of repeated new items, patients and comparison subjects demonstrated a similar degree of false recognition suppression after picture, as compared to word, encoding. Patients with schizophrenia displayed greater false recognition of repeated foils than comparison subjects, suggesting both a decrement of item- (or source-) specific recollection and a consequent reliance on familiarity in schizophrenia. Despite these deficits, presenting pictorial information at encoding allowed schizophrenic subjects to suppress false recognition to a similar degree as the comparison group, implying the intact use of a high-level cognitive strategy in this population.

Segmentation and Recognition of Continuous Human Activity

DTIC Science & Technology

2001-01-01

This paper presents a methodology for automatic segmentation and recognition of continuous human activity . We segment a continuous human activity into...commencement or termination. We use single action sequences for the training data set. The test sequences, on the other hand, are continuous sequences of human ... activity that consist of three or more actions in succession. The system has been tested on continuous activity sequences containing actions such as

RNA editing of microRNA prevents RNA-induced silencing complex recognition of target mRNA.

PubMed

Cui, Yalei; Huang, Tianzhi; Zhang, Xiaobo

2015-12-01

MicroRNAs (miRNAs) integrate with Argonaut (Ago) to create the RNA-induced silencing complex, and regulate gene expression by silencing target mRNAs. RNA editing of miRNA may affect miRNA processing, assembly of the Ago complex and target mRNA binding. However, the function of edited miRNA, assembled within the Ago complex, has not been extensively investigated. In this study, sequence analysis of the Ago complex of Marsupenaeus japonicus shrimp infected with white spot syndrome virus (WSSV) revealed that host ADAR (adenosine deaminase acting on RNA) catalysed A-to-I RNA editing of a viral miRNA (WSSV-miR-N12) at the +16 site. This editing of the non-seed sequence did not affect association of the edited miRNA with the Ago protein, but inhibited interaction between the miRNA and its target gene (wsv399). The WSSV early gene wsv399 inhibited WSSV infection. As a result, the RNA editing of miRNA caused virus latency. Our results highlight a novel example of miRNA editing in the miRNA-induced silencing complex. © 2015 The Authors.

Targeted exome sequencing for the identification of a protective variant against Internet gaming disorder at rs2229910 of neurotrophic tyrosine kinase receptor, type 3 (NTRK3): A pilot study

PubMed Central

Kim, Jeong-Yu; Jeong, Jo-Eun; Rhee, Je-Keun; Cho, Hyun; Chun, Ji-Won; Kim, Tae-Min; Choi, Sam-Wook; Choi, Jung-Seok; Kim, Dai-Jin

2016-01-01

Background and aims Internet gaming disorder (IGD) has gained recognition as a potential new diagnosis in the fifth revision of the Diagnostic and Statistical Manual of Mental Disorders, but genetic evidence supporting this disorder remains scarce. Methods In this study, targeted exome sequencing was conducted in 30 IGD patients and 30 control subjects with a focus on genes linked to various neurotransmitters associated with substance and non-substance addictions, depression, and attention deficit hyperactivity disorder. Results rs2229910 of neurotrophic tyrosine kinase receptor, type 3 (NTRK3) was the only single nucleotide polymorphism (SNP) that exhibited a significantly different minor allele frequency in IGD subjects compared to controls (p = .01932), suggesting that this SNP has a protective effect against IGD (odds ratio = 0.1541). The presence of this potentially protective allele was also associated with less time spent on Internet gaming and lower scores on the Young’s Internet Addiction Test and Korean Internet Addiction Proneness Scale for Adults. Conclusions The results of this first targeted exome sequencing study of IGD subjects indicate that rs2229910 of NTRK3 is a genetic variant that is significantly related to IGD. These findings may have significant implications for future research investigating the genetics of IGD and other behavioral addictions. PMID:27826991

Proliferating cell nuclear antigen (Pcna) as a direct downstream target gene of Hoxc8

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

Min, Hyehyun; Lee, Ji-Yeon; Bok, Jinwoong

2010-02-19

Hoxc8 is a member of Hox family transcription factors that play crucial roles in spatiotemporal body patterning during embryogenesis. Hox proteins contain a conserved 61 amino acid homeodomain, which is responsible for recognition and binding of the proteins onto Hox-specific DNA binding motifs and regulates expression of their target genes. Previously, using proteome analysis, we identified Proliferating cell nuclear antigen (Pcna) as one of the putative target genes of Hoxc8. Here, we asked whether Hoxc8 regulates Pcna expression by directly binding to the regulatory sequence of Pcna. In mouse embryos at embryonic day 11.5, the expression pattern of Pcna wasmore » similar to that of Hoxc8 along the anteroposterior body axis. Moreover, Pcna transcript levels as well as cell proliferation rate were increased by overexpression of Hoxc8 in C3H10T1/2 mouse embryonic fibroblast cells. Characterization of 2.3 kb genomic sequence upstream of Pcna coding region revealed that the upstream sequence contains several Hox core binding sequences and one Hox-Pbx binding sequence. Direct binding of Hoxc8 proteins to the Pcna regulatory sequence was verified by chromatin immunoprecipitation assay. Taken together, our data suggest that Pcna is a direct downstream target of Hoxc8.« less

Targeted next generation sequencing for the detection of ciprofloxacin resistance markers using molecular inversion probes

DTIC Science & Technology

2016-07-06

1 Targeted next-generation sequencing for the detection of ciprofloxacin resistance markers using molecular inversion probes Christopher P...development and evaluation of a panel of 44 single-stranded molecular inversion probes (MIPs) coupled to next-generation sequencing (NGS) for the...padlock and molecular inversion probes as upfront enrichment steps for use with NGS showed the specificity and multiplexability of these techniques

Social appraisal influences recognition of emotions.

PubMed

Mumenthaler, Christian; Sander, David

2012-06-01

The notion of social appraisal emphasizes the importance of a social dimension in appraisal theories of emotion by proposing that the way an individual appraises an event is influenced by the way other individuals appraise and feel about the same event. This study directly tested this proposal by asking participants to recognize dynamic facial expressions of emotion (fear, happiness, or anger in Experiment 1; fear, happiness, anger, or neutral in Experiment 2) in a target face presented at the center of a screen while a contextual face, which appeared simultaneously in the periphery of the screen, expressed an emotion (fear, happiness, anger) or not (neutral) and either looked at the target face or not. We manipulated gaze direction to be able to distinguish between a mere contextual effect (gaze away from both the target face and the participant) and a specific social appraisal effect (gaze toward the target face). Results of both experiments provided evidence for a social appraisal effect in emotion recognition, which differed from the mere effect of contextual information: Whereas facial expressions were identical in both conditions, the direction of the gaze of the contextual face influenced emotion recognition. Social appraisal facilitated the recognition of anger, happiness, and fear when the contextual face expressed the same emotion. This facilitation was stronger than the mere contextual effect. Social appraisal also allowed better recognition of fear when the contextual face expressed anger and better recognition of anger when the contextual face expressed fear. 2012 APA, all rights reserved

SOVEREIGN: An autonomous neural system for incrementally learning planned action sequences to navigate towards a rewarded goal.

PubMed

Gnadt, William; Grossberg, Stephen

2008-06-01

How do reactive and planned behaviors interact in real time? How are sequences of such behaviors released at appropriate times during autonomous navigation to realize valued goals? Controllers for both animals and mobile robots, or animats, need reactive mechanisms for exploration, and learned plans to reach goal objects once an environment becomes familiar. The SOVEREIGN (Self-Organizing, Vision, Expectation, Recognition, Emotion, Intelligent, Goal-oriented Navigation) animat model embodies these capabilities, and is tested in a 3D virtual reality environment. SOVEREIGN includes several interacting subsystems which model complementary properties of cortical What and Where processing streams and which clarify similarities between mechanisms for navigation and arm movement control. As the animat explores an environment, visual inputs are processed by networks that are sensitive to visual form and motion in the What and Where streams, respectively. Position-invariant and size-invariant recognition categories are learned by real-time incremental learning in the What stream. Estimates of target position relative to the animat are computed in the Where stream, and can activate approach movements toward the target. Motion cues from animat locomotion can elicit head-orienting movements to bring a new target into view. Approach and orienting movements are alternately performed during animat navigation. Cumulative estimates of each movement are derived from interacting proprioceptive and visual cues. Movement sequences are stored within a motor working memory. Sequences of visual categories are stored in a sensory working memory. These working memories trigger learning of sensory and motor sequence categories, or plans, which together control planned movements. Predictively effective chunk combinations are selectively enhanced via reinforcement learning when the animat is rewarded. Selected planning chunks effect a gradual transition from variable reactive exploratory

Plastoglobule-Targeting Competence of a Putative Transit Peptide Sequence from Rice Phytoene Synthase 2 in Plastids.

PubMed

You, Min Kyoung; Kim, Jin Hwa; Lee, Yeo Jin; Jeong, Ye Sol; Ha, Sun-Hwa

2016-12-22

Plastoglobules (PGs) are thylakoid membrane microdomains within plastids that are known as specialized locations of carotenogenesis. Three rice phytoene synthase proteins (OsPSYs) involved in carotenoid biosynthesis have been identified. Here, the N-terminal 80-amino-acid portion of OsPSY2 (PTp) was demonstrated to be a chloroplast-targeting peptide by displaying cytosolic localization of OsPSY2(ΔPTp):mCherry in rice protoplast, in contrast to chloroplast localization of OsPSY2:mCherry in a punctate pattern. The peptide sequence of a PTp was predicted to harbor two transmembrane domains eligible for a putative PG-targeting signal. To assess and enhance the PG-targeting ability of PTp, the original PTp DNA sequence ( PTp ) was modified to a synthetic DNA sequence ( stPTp ), which had 84.4% similarity to the original sequence. The motivation of this modification was to reduce the GC ratio from 75% to 65% and to disentangle the hairpin loop structures of PTp . These two DNA sequences were fused to the sequence of the synthetic green fluorescent protein (sGFP) and drove GFP expression with different efficiencies. In particular, the RNA and protein levels of stPTp-sGFP were slightly improved to 1.4-fold and 1.3-fold more than those of sGFP, respectively. The green fluorescent signals of their mature proteins were all observed as speckle-like patterns with slightly blurred stromal signals in chloroplasts. These discrete green speckles of PTp - sGFP and stPTp - sGFP corresponded exactly to the red fluorescent signal displayed by OsPSY2:mCherry in both etiolated and greening protoplasts and it is presumed to correspond to distinct PGs. In conclusion, we identified PTp as a transit peptide sequence facilitating preferential translocation of foreign proteins to PGs, and developed an improved PTp sequence, a s tPTp , which is expected to be very useful for applications in plant biotechnologies requiring precise micro-compartmental localization in plastids.

Conserved sequence-specific lincRNA-steroid receptor interactions drive transcriptional repression and direct cell fate

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

Hudson, William H.; Pickard, Mark R.; de Vera, Ian Mitchelle S.

2014-12-23

The majority of the eukaryotic genome is transcribed, generating a significant number of long intergenic noncoding RNAs (lincRNAs). Although lincRNAs represent the most poorly understood product of transcription, recent work has shown lincRNAs fulfill important cellular functions. In addition to low sequence conservation, poor understanding of structural mechanisms driving lincRNA biology hinders systematic prediction of their function. Here we report the molecular requirements for the recognition of steroid receptors (SRs) by the lincRNA growth arrest-specific 5 (Gas5), which regulates steroid-mediated transcriptional regulation, growth arrest and apoptosis. We identify the functional Gas5-SR interface and generate point mutations that ablate the SR-Gas5more » lincRNA interaction, altering Gas5-driven apoptosis in cancer cell lines. Further, we find that the Gas5 SR-recognition sequence is conserved among haplorhines, with its evolutionary origin as a splice acceptor site. This study demonstrates that lincRNAs can recognize protein targets in a conserved, sequence-specific manner in order to affect critical cell functions.« less

Sequence-controlled methacrylic multiblock copolymers via sulfur-free RAFT emulsion polymerization

NASA Astrophysics Data System (ADS)

Engelis, Nikolaos G.; Anastasaki, Athina; Nurumbetov, Gabit; Truong, Nghia P.; Nikolaou, Vasiliki; Shegiwal, Ataulla; Whittaker, Michael R.; Davis, Thomas P.; Haddleton, David M.

2017-02-01

Translating the precise monomer sequence control achieved in nature over macromolecular structure (for example, DNA) to whole synthetic systems has been limited due to the lack of efficient synthetic methodologies. So far, chemists have only been able to synthesize monomer sequence-controlled macromolecules by means of complex, time-consuming and iterative chemical strategies such as solid-state Merrifield-type approaches or molecularly dissolved solution-phase systems. Here, we report a rapid and quantitative synthesis of sequence-controlled multiblock polymers in discrete stable nanoscale compartments via an emulsion polymerization approach in which a vinyl-terminated macromolecule is used as an efficient chain-transfer agent. This approach is environmentally friendly, fully translatable to industry and thus represents a significant advance in the development of complex macromolecule synthesis, where a high level of molecular precision or monomer sequence control confers potential for molecular targeting, recognition and biocatalysis, as well as molecular information storage.

Identification of the RNA recognition element of the RBPMS family of RNA-binding proteins and their transcriptome-wide mRNA targets

PubMed Central

Farazi, Thalia A.; Leonhardt, Carl S.; Mukherjee, Neelanjan; Mihailovic, Aleksandra; Li, Song; Max, Klaas E.A.; Meyer, Cindy; Yamaji, Masashi; Cekan, Pavol; Jacobs, Nicholas C.; Gerstberger, Stefanie; Bognanni, Claudia; Larsson, Erik; Ohler, Uwe; Tuschl, Thomas

2014-01-01

Recent studies implicated the RNA-binding protein with multiple splicing (RBPMS) family of proteins in oocyte, retinal ganglion cell, heart, and gastrointestinal smooth muscle development. These RNA-binding proteins contain a single RNA recognition motif (RRM), and their targets and molecular function have not yet been identified. We defined transcriptome-wide RNA targets using photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation (PAR-CLIP) in HEK293 cells, revealing exonic mature and intronic pre-mRNA binding sites, in agreement with the nuclear and cytoplasmic localization of the proteins. Computational and biochemical approaches defined the RNA recognition element (RRE) as a tandem CAC trinucleotide motif separated by a variable spacer region. Similar to other mRNA-binding proteins, RBPMS family of proteins relocalized to cytoplasmic stress granules under oxidative stress conditions suggestive of a support function for mRNA localization in large and/or multinucleated cells where it is preferentially expressed. PMID:24860013

Domain Regeneration for Cross-Database Micro-Expression Recognition

NASA Astrophysics Data System (ADS)

Zong, Yuan; Zheng, Wenming; Huang, Xiaohua; Shi, Jingang; Cui, Zhen; Zhao, Guoying

2018-05-01

In this paper, we investigate the cross-database micro-expression recognition problem, where the training and testing samples are from two different micro-expression databases. Under this setting, the training and testing samples would have different feature distributions and hence the performance of most existing micro-expression recognition methods may decrease greatly. To solve this problem, we propose a simple yet effective method called Target Sample Re-Generator (TSRG) in this paper. By using TSRG, we are able to re-generate the samples from target micro-expression database and the re-generated target samples would share same or similar feature distributions with the original source samples. For this reason, we can then use the classifier learned based on the labeled source samples to accurately predict the micro-expression categories of the unlabeled target samples. To evaluate the performance of the proposed TSRG method, extensive cross-database micro-expression recognition experiments designed based on SMIC and CASME II databases are conducted. Compared with recent state-of-the-art cross-database emotion recognition methods, the proposed TSRG achieves more promising results.

Phage-mediated Delivery of Targeted sRNA Constructs to Knock Down Gene Expression in E. coli.

PubMed

Bernheim, Aude G; Libis, Vincent K; Lindner, Ariel B; Wintermute, Edwin H

2016-03-20

RNA-mediated knockdowns are widely used to control gene expression. This versatile family of techniques makes use of short RNA (sRNA) that can be synthesized with any sequence and designed to complement any gene targeted for silencing. Because sRNA constructs can be introduced to many cell types directly or using a variety of vectors, gene expression can be repressed in living cells without laborious genetic modification. The most common RNA knockdown technology, RNA interference (RNAi), makes use of the endogenous RNA-induced silencing complex (RISC) to mediate sequence recognition and cleavage of the target mRNA. Applications of this technique are therefore limited to RISC-expressing organisms, primarily eukaryotes. Recently, a new generation of RNA biotechnologists have developed alternative mechanisms for controlling gene expression through RNA, and so made possible RNA-mediated gene knockdowns in bacteria. Here we describe a method for silencing gene expression in E. coli that functionally resembles RNAi. In this system a synthetic phagemid is designed to express sRNA, which may designed to target any sequence. The expression construct is delivered to a population of E. coli cells with non-lytic M13 phage, after which it is able to stably replicate as a plasmid. Antisense recognition and silencing of the target mRNA is mediated by the Hfq protein, endogenous to E. coli. This protocol includes methods for designing the antisense sRNA, constructing the phagemid vector, packaging the phagemid into M13 bacteriophage, preparing a live cell population for infection, and performing the infection itself. The fluorescent protein mKate2 and the antibiotic resistance gene chloramphenicol acetyltransferase (CAT) are targeted to generate representative data and to quantify knockdown effectiveness.

Road sign recognition with fuzzy adaptive pre-processing models.

PubMed

Lin, Chien-Chuan; Wang, Ming-Shi

2012-01-01

A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance.

Road Sign Recognition with Fuzzy Adaptive Pre-Processing Models

PubMed Central

Lin, Chien-Chuan; Wang, Ming-Shi

2012-01-01

A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance. PMID:22778650

User acceptance of intelligent avionics: A study of automatic-aided target recognition

NASA Technical Reports Server (NTRS)

Becker, Curtis A.; Hayes, Brian C.; Gorman, Patrick C.

1991-01-01

User acceptance of new support systems typically was evaluated after the systems were specified, designed, and built. The current study attempts to assess user acceptance of an Automatic-Aided Target Recognition (ATR) system using an emulation of such a proposed system. The detection accuracy and false alarm level of the ATR system were varied systematically, and subjects rated the tactical value of systems exhibiting different performance levels. Both detection accuracy and false alarm level affected the subjects' ratings. The data from two experiments suggest a cut-off point in ATR performance below which the subjects saw little tactical value in the system. An ATR system seems to have obvious tactical value only if it functions at a correct detection rate of 0.7 or better with a false alarm level of 0.167 false alarms per square degree or fewer.

Comparison of Methods of Detection of Exceptional Sequences in Prokaryotic Genomes.

PubMed

Rusinov, I S; Ershova, A S; Karyagina, A S; Spirin, S A; Alexeevski, A V

2018-02-01

Many proteins need recognition of specific DNA sequences for functioning. The number of recognition sites and their distribution along the DNA might be of biological importance. For example, the number of restriction sites is often reduced in prokaryotic and phage genomes to decrease the probability of DNA cleavage by restriction endonucleases. We call a sequence an exceptional one if its frequency in a genome significantly differs from one predicted by some mathematical model. An exceptional sequence could be either under- or over-represented, depending on its frequency in comparison with the predicted one. Exceptional sequences could be considered biologically meaningful, for example, as targets of DNA-binding proteins or as parts of abundant repetitive elements. Several methods to predict frequency of a short sequence in a genome, based on actual frequencies of certain its subsequences, are used. The most popular are methods based on Markov chain models. But any rigorous comparison of the methods has not previously been performed. We compared three methods for the prediction of short sequence frequencies: the maximum-order Markov chain model-based method, the method that uses geometric mean of extended Markovian estimates, and the method that utilizes frequencies of all subsequences including discontiguous ones. We applied them to restriction sites in complete genomes of 2500 prokaryotic species and demonstrated that the results depend greatly on the method used: lists of 5% of the most under-represented sites differed by up to 50%. The method designed by Burge and coauthors in 1992, which utilizes all subsequences of the sequence, showed a higher precision than the other two methods both on prokaryotic genomes and randomly generated sequences after computational imitation of selective pressure. We propose this method as the first choice for detection of exceptional sequences in prokaryotic genomes.

Investigation of DNA sequence recognition by a streptomycete MarR family transcriptional regulator through surface plasmon resonance and X-ray crystallography

PubMed Central

Stevenson, Clare E. M.; Assaad, Aoun; Chandra, Govind; Le, Tung B. K.; Greive, Sandra J.; Bibb, Mervyn J.; Lawson, David M.

2013-01-01

Consistent with their complex lifestyles and rich secondary metabolite profiles, the genomes of streptomycetes encode a plethora of transcription factors, the vast majority of which are uncharacterized. Herein, we use Surface Plasmon Resonance (SPR) to identify and delineate putative operator sites for SCO3205, a MarR family transcriptional regulator from Streptomyces coelicolor that is well represented in sequenced actinomycete genomes. In particular, we use a novel SPR footprinting approach that exploits indirect ligand capture to vastly extend the lifetime of a standard streptavidin SPR chip. We define two operator sites upstream of sco3205 and a pseudopalindromic consensus sequence derived from these enables further potential operator sites to be identified in the S. coelicolor genome. We evaluate each of these through SPR and test the importance of the conserved bases within the consensus sequence. Informed by these results, we determine the crystal structure of a SCO3205-DNA complex at 2.8 Å resolution, enabling molecular level rationalization of the SPR data. Taken together, our observations support a DNA recognition mechanism involving both direct and indirect sequence readout. PMID:23748564

Massively Parallel Sequencing of Patients with Intellectual Disability, Congenital Anomalies and/or Autism Spectrum Disorders with a Targeted Gene Panel

PubMed Central

Brett, Maggie; McPherson, John; Zang, Zhi Jiang; Lai, Angeline; Tan, Ee-Shien; Ng, Ivy; Ong, Lai-Choo; Cham, Breana; Tan, Patrick; Rozen, Steve; Tan, Ene-Choo

2014-01-01

Developmental delay and/or intellectual disability (DD/ID) affects 1–3% of all children. At least half of these are thought to have a genetic etiology. Recent studies have shown that massively parallel sequencing (MPS) using a targeted gene panel is particularly suited for diagnostic testing for genetically heterogeneous conditions. We report on our experiences with using massively parallel sequencing of a targeted gene panel of 355 genes for investigating the genetic etiology of eight patients with a wide range of phenotypes including DD/ID, congenital anomalies and/or autism spectrum disorder. Targeted sequence enrichment was performed using the Agilent SureSelect Target Enrichment Kit and sequenced on the Illumina HiSeq2000 using paired-end reads. For all eight patients, 81–84% of the targeted regions achieved read depths of at least 20×, with average read depths overlapping targets ranging from 322× to 798×. Causative variants were successfully identified in two of the eight patients: a nonsense mutation in the ATRX gene and a canonical splice site mutation in the L1CAM gene. In a third patient, a canonical splice site variant in the USP9X gene could likely explain all or some of her clinical phenotypes. These results confirm the value of targeted MPS for investigating DD/ID in children for diagnostic purposes. However, targeted gene MPS was less likely to provide a genetic diagnosis for children whose phenotype includes autism. PMID:24690944

Substrate-Driven Mapping of the Degradome by Comparison of Sequence Logos

PubMed Central

Fuchs, Julian E.; von Grafenstein, Susanne; Huber, Roland G.; Kramer, Christian; Liedl, Klaus R.

2013-01-01

Sequence logos are frequently used to illustrate substrate preferences and specificity of proteases. Here, we employed the compiled substrates of the MEROPS database to introduce a novel metric for comparison of protease substrate preferences. The constructed similarity matrix of 62 proteases can be used to intuitively visualize similarities in protease substrate readout via principal component analysis and construction of protease specificity trees. Since our new metric is solely based on substrate data, we can engraft the protease tree including proteolytic enzymes of different evolutionary origin. Thereby, our analyses confirm pronounced overlaps in substrate recognition not only between proteases closely related on sequence basis but also between proteolytic enzymes of different evolutionary origin and catalytic type. To illustrate the applicability of our approach we analyze the distribution of targets of small molecules from the ChEMBL database in our substrate-based protease specificity trees. We observe a striking clustering of annotated targets in tree branches even though these grouped targets do not necessarily share similarity on protein sequence level. This highlights the value and applicability of knowledge acquired from peptide substrates in drug design of small molecules, e.g., for the prediction of off-target effects or drug repurposing. Consequently, our similarity metric allows to map the degradome and its associated drug target network via comparison of known substrate peptides. The substrate-driven view of protein-protein interfaces is not limited to the field of proteases but can be applied to any target class where a sufficient amount of known substrate data is available. PMID:24244149

Serial position effects in recognition memory for odors: a reexamination.

PubMed

Miles, Christopher; Hodder, Kathryn

2005-10-01

Seven experiments examined recognition memory for sequentially presented odors. Following Reed (2000), participants were presented with a sequence of odors and then required to identify an odor from the sequence in a test probe comprising 2 odors. The pattern of results obtained by Reed (2000, although statistically marginal) demonstrated enhanced recognition for odors presented at the start (primacy) and end (recency) of the sequence: a result that we failed to replicate in any of the experiments reported here. Experiments 1 and 3 were designed to replicate Reed (2000), employing five-item and seven-item sequences, respectively, and each demonstrated significant recency, with evidence of primacy in Experiment 3 only. Experiment 2 replicated Experiment 1, with reduced interstimulus intervals, and produced a null effect of serial position. The ease with which the odors could be verbally labeled was manipulated in Experiments 4 and 5. Nameable odors produced a null effect of serial position (Experiment 4), and hard-to-name odors produced a pronounced recency effect (Experiment 5); nevertheless, overall rates of recognition were remarkably similar for the two experiments at around 70%. Articulatory suppression reduced recognition accuracy (Experiment 6), but recency was again present in the absence of primacy. Odor recognition performance was immune to the effects of an interleaved odor (Experiment 7), and, again, both primacy and recency effects were absent. There was no evidence of olfactory fatigue: Recognition accuracy improved across trials (Experiment 1). It is argued that the results of the experiments reported here are generally consistent with that body of work employing hard-to-name visual stimuli, where recency is obtained in the absence of primacy when the retention interval is short.

Structural basis of DNA target recognition by the B3 domain of Arabidopsis epigenome reader VAL1

PubMed Central

Sasnauskas, Giedrius; Kauneckaitė, Kotryna; Siksnys, Virginijus

2018-01-01

Abstract Arabidopsis thaliana requires a prolonged period of cold exposure during winter to initiate flowering in a process termed vernalization. Exposure to cold induces epigenetic silencing of the FLOWERING LOCUS C (FLC) gene by Polycomb group (PcG) proteins. A key role in this epigenetic switch is played by transcriptional repressors VAL1 and VAL2, which specifically recognize Sph/RY DNA sequences within FLC via B3 DNA binding domains, and mediate recruitment of PcG silencing machinery. To understand the structural mechanism of site-specific DNA recognition by VAL1, we have solved the crystal structure of VAL1 B3 domain (VAL1-B3) bound to a 12 bp oligoduplex containing the canonical Sph/RY DNA sequence 5′-CATGCA-3′/5′-TGCATG-3′. We find that VAL1-B3 makes H-bonds and van der Waals contacts to DNA bases of all six positions of the canonical Sph/RY element. In agreement with the structure, in vitro DNA binding studies show that VAL1-B3 does not tolerate substitutions at any position of the 5′-TGCATG-3′ sequence. The VAL1-B3–DNA structure presented here provides a structural model for understanding the specificity of plant B3 domains interacting with the Sph/RY and other DNA sequences. PMID:29660015

Atypical case of Wolfram syndrome revealed through targeted exome sequencing in a patient with suspected mitochondrial disease

PubMed Central

2012-01-01

Background Mitochondrial diseases comprise a diverse set of clinical disorders that affect multiple organ systems with varying severity and age of onset. Due to their clinical and genetic heterogeneity, these diseases are difficult to diagnose. We have developed a targeted exome sequencing approach to improve our ability to properly diagnose mitochondrial diseases and apply it here to an individual patient. Our method targets mitochondrial DNA (mtDNA) and the exons of 1,600 nuclear genes involved in mitochondrial biology or Mendelian disorders with multi-system phenotypes, thereby allowing for simultaneous evaluation of multiple disease loci. Case Presentation Targeted exome sequencing was performed on a patient initially suspected to have a mitochondrial disorder. The patient presented with diabetes mellitus, diffuse brain atrophy, autonomic neuropathy, optic nerve atrophy, and a severe amnestic syndrome. Further work-up revealed multiple heteroplasmic mtDNA deletions as well as profound thiamine deficiency without a clear nutritional cause. Targeted exome sequencing revealed a homozygous c.1672C > T (p.R558C) missense mutation in exon 8 of WFS1 that has previously been reported in a patient with Wolfram syndrome. Conclusion This case demonstrates how clinical application of next-generation sequencing technology can enhance the diagnosis of patients suspected to have rare genetic disorders. Furthermore, the finding of unexplained thiamine deficiency in a patient with Wolfram syndrome suggests a potential link between WFS1 biology and thiamine metabolism that has implications for the clinical management of Wolfram syndrome patients. PMID:22226368

Multimodal emotional state recognition using sequence-dependent deep hierarchical features.

PubMed

Barros, Pablo; Jirak, Doreen; Weber, Cornelius; Wermter, Stefan

2015-12-01

Emotional state recognition has become an important topic for human-robot interaction in the past years. By determining emotion expressions, robots can identify important variables of human behavior and use these to communicate in a more human-like fashion and thereby extend the interaction possibilities. Human emotions are multimodal and spontaneous, which makes them hard to be recognized by robots. Each modality has its own restrictions and constraints which, together with the non-structured behavior of spontaneous expressions, create several difficulties for the approaches present in the literature, which are based on several explicit feature extraction techniques and manual modality fusion. Our model uses a hierarchical feature representation to deal with spontaneous emotions, and learns how to integrate multiple modalities for non-verbal emotion recognition, making it suitable to be used in an HRI scenario. Our experiments show that a significant improvement of recognition accuracy is achieved when we use hierarchical features and multimodal information, and our model improves the accuracy of state-of-the-art approaches from 82.5% reported in the literature to 91.3% for a benchmark dataset on spontaneous emotion expressions. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Performance Comparison of Bench-Top Next Generation Sequencers Using Microdroplet PCR-Based Enrichment for Targeted Sequencing in Patients with Autism Spectrum Disorder

PubMed Central

Okamoto, Nobuhiko; Nakashima, Mitsuko; Tsurusaki, Yoshinori; Miyake, Noriko; Saitsu, Hirotomo; Matsumoto, Naomichi

2013-01-01

Next-generation sequencing (NGS) combined with enrichment of target genes enables highly efficient and low-cost sequencing of multiple genes for genetic diseases. The aim of this study was to validate the accuracy and sensitivity of our method for comprehensive mutation detection in autism spectrum disorder (ASD). We assessed the performance of the bench-top Ion Torrent PGM and Illumina MiSeq platforms as optimized solutions for mutation detection, using microdroplet PCR-based enrichment of 62 ASD associated genes. Ten patients with known mutations were sequenced using NGS to validate the sensitivity of our method. The overall read quality was better with MiSeq, largely because of the increased indel-related error associated with PGM. The sensitivity of SNV detection was similar between the two platforms, suggesting they are both suitable for SNV detection in the human genome. Next, we used these methods to analyze 28 patients with ASD, and identified 22 novel variants in genes associated with ASD, with one mutation detected by MiSeq only. Thus, our results support the combination of target gene enrichment and NGS as a valuable molecular method for investigating rare variants in ASD. PMID:24066114

Cas9 specifies functional viral targets during CRISPR-Cas adaptation.

PubMed

Heler, Robert; Samai, Poulami; Modell, Joshua W; Weiner, Catherine; Goldberg, Gregory W; Bikard, David; Marraffini, Luciano A

2015-03-12

Clustered regularly interspaced short palindromic repeat (CRISPR) loci and their associated (Cas) proteins provide adaptive immunity against viral infection in prokaryotes. Upon infection, short phage sequences known as spacers integrate between CRISPR repeats and are transcribed into small RNA molecules that guide the Cas9 nuclease to the viral targets (protospacers). Streptococcus pyogenes Cas9 cleavage of the viral genome requires the presence of a 5'-NGG-3' protospacer adjacent motif (PAM) sequence immediately downstream of the viral target. It is not known whether and how viral sequences flanked by the correct PAM are chosen as new spacers. Here we show that Cas9 selects functional spacers by recognizing their PAM during spacer acquisition. The replacement of cas9 with alleles that lack the PAM recognition motif or recognize an NGGNG PAM eliminated or changed PAM specificity during spacer acquisition, respectively. Cas9 associates with other proteins of the acquisition machinery (Cas1, Cas2 and Csn2), presumably to provide PAM-specificity to this process. These results establish a new function for Cas9 in the genesis of prokaryotic immunological memory.

Rapid molecular diagnostics of severe primary immunodeficiency determined by using targeted next-generation sequencing.

PubMed

Yu, Hui; Zhang, Victor Wei; Stray-Pedersen, Asbjørg; Hanson, Imelda Celine; Forbes, Lisa R; de la Morena, M Teresa; Chinn, Ivan K; Gorman, Elizabeth; Mendelsohn, Nancy J; Pozos, Tamara; Wiszniewski, Wojciech; Nicholas, Sarah K; Yates, Anne B; Moore, Lindsey E; Berge, Knut Erik; Sorte, Hanne; Bayer, Diana K; ALZahrani, Daifulah; Geha, Raif S; Feng, Yanming; Wang, Guoli; Orange, Jordan S; Lupski, James R; Wang, Jing; Wong, Lee-Jun

2016-10-01

Primary immunodeficiency diseases (PIDDs) are inherited disorders of the immune system. The most severe form, severe combined immunodeficiency (SCID), presents with profound deficiencies of T cells, B cells, or both at birth. If not treated promptly, affected patients usually do not live beyond infancy because of infections. Genetic heterogeneity of SCID frequently delays the diagnosis; a specific diagnosis is crucial for life-saving treatment and optimal management. We developed a next-generation sequencing (NGS)-based multigene-targeted panel for SCID and other severe PIDDs requiring rapid therapeutic actions in a clinical laboratory setting. The target gene capture/NGS assay provides an average read depth of approximately 1000×. The deep coverage facilitates simultaneous detection of single nucleotide variants and exonic copy number variants in one comprehensive assessment. Exons with insufficient coverage (<20× read depth) or high sequence homology (pseudogenes) are complemented by amplicon-based sequencing with specific primers to ensure 100% coverage of all targeted regions. Analysis of 20 patient samples with low T-cell receptor excision circle numbers on newborn screening or a positive family history or clinical suspicion of SCID or other severe PIDD identified deleterious mutations in 14 of them. Identified pathogenic variants included both single nucleotide variants and exonic copy number variants, such as hemizygous nonsense, frameshift, and missense changes in IL2RG; compound heterozygous changes in ATM, RAG1, and CIITA; homozygous changes in DCLRE1C and IL7R; and a heterozygous nonsense mutation in CHD7. High-throughput deep sequencing analysis with complete clinical validation greatly increases the diagnostic yield of severe primary immunodeficiency. Establishing a molecular diagnosis enables early immune reconstitution through prompt therapeutic intervention and guides management for improved long-term quality of life. Copyright © 2016 American

The effect of letter string length and report condition on letter recognition accuracy.

PubMed

Raghunandan, Avesh; Karmazinaite, Berta; Rossow, Andrea S

Letter sequence recognition accuracy has been postulated to be limited primarily by low-level visual factors. The influence of high level factors such as visual memory (load and decay) has been largely overlooked. This study provides insight into the role of these factors by investigating the interaction between letter sequence recognition accuracy, letter string length and report condition. Letter sequence recognition accuracy for trigrams and pentagrams were measured in 10 adult subjects for two report conditions. In the complete report condition subjects reported all 3 or all 5 letters comprising trigrams and pentagrams, respectively. In the partial report condition, subjects reported only a single letter in the trigram or pentagram. Letters were presented for 100ms and rendered in high contrast, using black lowercase Courier font that subtended 0.4° at the fixation distance of 0.57m. Letter sequence recognition accuracy was consistently higher for trigrams compared to pentagrams especially for letter positions away from fixation. While partial report increased recognition accuracy in both string length conditions, the effect was larger for pentagrams, and most evident for the final letter positions within trigrams and pentagrams. The effect of partial report on recognition accuracy for the final letter positions increased as eccentricity increased away from fixation, and was independent of the inner/outer position of a letter. Higher-level visual memory functions (memory load and decay) play a role in letter sequence recognition accuracy. There is also suggestion of additional delays imposed on memory encoding by crowded letter elements. Copyright © 2016 Spanish General Council of Optometry. Published by Elsevier España, S.L.U. All rights reserved.

Rational Design of Small Molecules Targeting Oncogenic Noncoding RNAs from Sequence.

PubMed

Disney, Matthew D; Angelbello, Alicia J

2016-12-20

The discovery of RNA catalysis in the 1980s and the dissemination of the human genome sequence at the start of this century inspired investigations of the regulatory roles of noncoding RNAs in biology. In fact, the Encyclopedia of DNA Elements (ENCODE) project has shown that only 1-2% of the human genome encodes protein, yet 75% is transcribed into RNA. Functional studies both preceding and following the ENCODE project have shown that these noncoding RNAs have important roles in regulating gene expression, developmental timing, and other critical functions. RNA's diverse roles are often a consequence of the various folds that it adopts. The single-stranded nature of the biopolymer enables it to adopt intramolecular folds with noncanonical pairings to lower its free energy. These folds can be scaffolds to bind proteins or to form frameworks to interact with other RNAs. Not surprisingly, dysregulation of certain noncoding RNAs has been shown to be causative of disease. Given this as the background, it is easy to see why it would be useful to develop methods that target RNA and manipulate its biology in rational and predictable ways. The antisense approach has afforded strategies to target RNAs via Watson-Crick base pairing and has typically focused on targeting partially unstructured regions of RNA. Small molecule strategies to target RNA would be desirable not only because compounds could be lead optimized via medicinal chemistry but also because structured regions within an RNA of interest could be targeted to directly interfere with RNA folds that contribute to disease. Additionally, small molecules have historically been the most successful drug candidates. Until recently, the ability to design small molecules that target non-ribosomal RNAs has been elusive, creating the perception that they are "undruggable". In this Account, approaches to demystify targeting RNA with small molecules are described. Rather than bulk screening for compounds that bind to singular

Evaluation of Nine Somatic Variant Callers for Detection of Somatic Mutations in Exome and Targeted Deep Sequencing Data.

PubMed

Krøigård, Anne Bruun; Thomassen, Mads; Lænkholm, Anne-Vibeke; Kruse, Torben A; Larsen, Martin Jakob

2016-01-01

Next generation sequencing is extensively applied to catalogue somatic mutations in cancer, in research settings and increasingly in clinical settings for molecular diagnostics, guiding therapy decisions. Somatic variant callers perform paired comparisons of sequencing data from cancer tissue and matched normal tissue in order to detect somatic mutations. The advent of many new somatic variant callers creates a need for comparison and validation of the tools, as no de facto standard for detection of somatic mutations exists and only limited comparisons have been reported. We have performed a comprehensive evaluation using exome sequencing and targeted deep sequencing data of paired tumor-normal samples from five breast cancer patients to evaluate the performance of nine publicly available somatic variant callers: EBCall, Mutect, Seurat, Shimmer, Indelocator, Somatic Sniper, Strelka, VarScan 2 and Virmid for the detection of single nucleotide mutations and small deletions and insertions. We report a large variation in the number of calls from the nine somatic variant callers on the same sequencing data and highly variable agreement. Sequencing depth had markedly diverse impact on individual callers, as for some callers, increased sequencing depth highly improved sensitivity. For SNV calling, we report EBCall, Mutect, Virmid and Strelka to be the most reliable somatic variant callers for both exome sequencing and targeted deep sequencing. For indel calling, EBCall is superior due to high sensitivity and robustness to changes in sequencing depths.

The Coding of Biological Information: From Nucleotide Sequence to Protein Recognition

NASA Astrophysics Data System (ADS)

Štambuk, Nikola

The paper reviews the classic results of Swanson, Dayhoff, Grantham, Blalock and Root-Bernstein, which link genetic code nucleotide patterns to the protein structure, evolution and molecular recognition. Symbolic representation of the binary addresses defining particular nucleotide and amino acid properties is discussed, with consideration of: structure and metric of the code, direct correspondence between amino acid and nucleotide information, and molecular recognition of the interacting protein motifs coded by the complementary DNA and RNA strands.

Cryo-EM Structures Reveal Mechanism and Inhibition of DNA Targeting by a CRISPR-Cas Surveillance Complex.

PubMed

Guo, Tai Wei; Bartesaghi, Alberto; Yang, Hui; Falconieri, Veronica; Rao, Prashant; Merk, Alan; Eng, Edward T; Raczkowski, Ashleigh M; Fox, Tara; Earl, Lesley A; Patel, Dinshaw J; Subramaniam, Sriram

2017-10-05

Prokaryotic cells possess CRISPR-mediated adaptive immune systems that protect them from foreign genetic elements, such as invading viruses. A central element of this immune system is an RNA-guided surveillance complex capable of targeting non-self DNA or RNA for degradation in a sequence- and site-specific manner analogous to RNA interference. Although the complexes display considerable diversity in their composition and architecture, many basic mechanisms underlying target recognition and cleavage are highly conserved. Using cryoelectron microscopy (cryo-EM), we show that the binding of target double-stranded DNA (dsDNA) to a type I-F CRISPR system yersinia (Csy) surveillance complex leads to large quaternary and tertiary structural changes in the complex that are likely necessary in the pathway leading to target dsDNA degradation by a trans-acting helicase-nuclease. Comparison of the structure of the surveillance complex before and after dsDNA binding, or in complex with three virally encoded anti-CRISPR suppressors that inhibit dsDNA binding, reveals mechanistic details underlying target recognition and inhibition. Published by Elsevier Inc.

Silent genetic alterations identified by targeted next-generation sequencing in pheochromocytoma/paraganglioma: A clinicopathological correlations.

PubMed

Pillai, Suja; Gopalan, Vinod; Lo, Chung Y; Liew, Victor; Smith, Robert A; Lam, Alfred King Y

2017-02-01

The goal of this pilot study was to develop a customized, cost-effective amplicon panel (Ampliseq) for target sequencing in a cohort of patients with sporadic phaeochromocytoma/paraganglioma. Phaeochromocytoma/paragangliomas from 25 patients were analysed by targeted next-generation sequencing approach using an Ion Torrent PGM instrument. Primers for 15 target genes (NF1, RET, VHL, SDHA, SDHB, SDHC, SDHD, SDHAF2, TMEM127, MAX, MEN1, KIF1Bβ, EPAS1, CDKN2 & PHD2) were designed using ion ampliseq designer. Ion Reporter software and Ingenuity® Variant Analysis™ software (www.ingenuity.com/variants) from Ingenuity Systems were used to analysis these results. Overall, 713 variants were identified. The variants identified from the Ion Reporter ranged from 64 to 161 per patient. Single nucleotide variants (SNV) were the most common. Further annotation with the help of Ingenuity variant analysis revealed 29 of these 713variants were deletions. Of these, six variants were non-pathogenic and four were likely to be pathogenic. The remaining 19 variants were of uncertain significance. The most frequently altered gene in the cohort was KIF1B followed by NF1. Novel KIF1B pathogenic variant c.3375+1G>A was identified. The mutation was noted in a patient with clinically confirmed neurofibromatosis. Chromosome 1 showed the presence of maximum number of variants. Use of targeted next-generation sequencing is a sensitive method for the detecting genetic changes in patients with phaeochromocytoma/paraganglioma. The precise detection of these genetic changes helps in understanding the pathogenesis of these tumours. Copyright © 2016 Elsevier Inc. All rights reserved.

Hyaluronan functionalizing QDs as turn-on fluorescent probe for targeted recognition CD44 receptor

NASA Astrophysics Data System (ADS)

Zhou, Shang; Huo, Danqun; Hou, Changjun; Yang, Mei; Fa, Huanbao

2017-09-01

The recognition of tumor markers in living cancer cells has attracted increasing interest. In the present study, the turn-on fluorescence probe was designed based on the fluorescence of thiolated chitosan-coated CdTe QDs (CdTe/TCS QDs) quenched by hyaluronan, which could provide the low background signal for sensitive cellular imaging. This system is expected to offer specific recognition of CD44 receptor over other substances owing to the specific affinity of hyaluronan and CD44 receptor ( 8-9 kcal/mol). The probe is stable in aqueous and has little toxicity to living cells; thus, it can be utilized for targeted cancer cell imaging. The living lung cancer cell imaging experiments further demonstrate its value in recognizing cell-surface CD44 receptor with turn-on mode. In addition, the probe can be used to recognize and differentiate the subtypes of lung cancer cells based on the difference of CD44 expression on the surface of lung cancer cells. And, the western blot test further confirmed that the expression level of the CD44 receptor in lung cancer cells is different. Therefore, this probe may be potentially applied in recognizing lung cancer cells with higher contrast and sensitivity and provide new tools for cancer prognosis and therapy. [Figure not available: see fulltext.

Prediction of TF target sites based on atomistic models of protein-DNA complexes

PubMed Central

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

2008-01-01

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

Human target acquisition performance

NASA Astrophysics Data System (ADS)

Teaney, Brian P.; Du Bosq, Todd W.; Reynolds, Joseph P.; Thompson, Roger; Aghera, Sameer; Moyer, Steven K.; Flug, Eric; Espinola, Richard; Hixson, Jonathan

2012-06-01

The battlefield has shifted from armored vehicles to armed insurgents. Target acquisition (identification, recognition, and detection) range performance involving humans as targets is vital for modern warfare. The acquisition and neutralization of armed insurgents while at the same time minimizing fratricide and civilian casualties is a mounting concern. U.S. Army RDECOM CERDEC NVESD has conducted many experiments involving human targets for infrared and reflective band sensors. The target sets include human activities, hand-held objects, uniforms & armament, and other tactically relevant targets. This paper will define a set of standard task difficulty values for identification and recognition associated with human target acquisition performance.

Aptamer Recognition of Multiplexed Small-Molecule-Functionalized Substrates.

PubMed

Nakatsuka, Nako; Cao, Huan H; Deshayes, Stephanie; Melkonian, Arin Lucy; Kasko, Andrea M; Weiss, Paul S; Andrews, Anne M

2018-05-31

Aptamers are chemically synthesized oligonucleotides or peptides with molecular recognition capabilities. We investigated recognition of substrate-tethered small-molecule targets, using neurotransmitters as examples, and fluorescently labeled DNA aptamers. Substrate regions patterned via microfluidic channels with dopamine or L-tryptophan were selectively recognized by previously identified dopamine or L-tryptophan aptamers, respectively. The on-substrate dissociation constant determined for the dopamine aptamer was comparable to, though slightly greater than the previously determined solution dissociation constant. Using pre-functionalized neurotransmitter-conjugated oligo(ethylene glycol) alkanethiols and microfluidics patterning, we produced multiplexed substrates to capture and to sort aptamers. Substrates patterned with L-DOPA, L-DOPS, and L-5-HTP enabled comparison of the selectivity of the dopamine aptamer for different targets via simultaneous determination of in situ binding constants. Thus, beyond our previous demonstrations of recognition by protein binding partners (i.e., antibodies and G-protein-coupled receptors), strategically optimized small-molecule-functionalized substrates show selective recognition of nucleic acid binding partners. These substrates are useful for side-by-side target comparisons, and future identification and characterization of novel aptamers targeting neurotransmitters or other important small-molecules.

Structural Basis for Conserved Regulation and Adaptation of the Signal Recognition Particle Targeting Complex.

PubMed

Wild, Klemens; Bange, Gert; Motiejunas, Domantas; Kribelbauer, Judith; Hendricks, Astrid; Segnitz, Bernd; Wade, Rebecca C; Sinning, Irmgard

2016-07-17

The signal recognition particle (SRP) is a ribonucleoprotein complex with a key role in targeting and insertion of membrane proteins. The two SRP GTPases, SRP54 (Ffh in bacteria) and FtsY (SRα in eukaryotes), form the core of the targeting complex (TC) regulating the SRP cycle. The architecture of the TC and its stimulation by RNA has been described for the bacterial SRP system while this information is lacking for other domains of life. Here, we present the crystal structures of the GTPase heterodimers of archaeal (Sulfolobus solfataricus), eukaryotic (Homo sapiens), and chloroplast (Arabidopsis thaliana) SRP systems. The comprehensive structural comparison combined with Brownian dynamics simulations of TC formation allows for the description of the general blueprint and of specific adaptations of the quasi-symmetric heterodimer. Our work defines conserved external nucleotide-binding sites for SRP GTPase activation by RNA. Structural analyses of the GDP-bound, post-hydrolysis states reveal a conserved, magnesium-sensitive switch within the I-box. Overall, we provide a general model for SRP cycle regulation by RNA. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evaluating allopolyploid origins in strawberries (Fragaria) using haplotypes generated from target capture sequencing.

PubMed

Kamneva, Olga K; Syring, John; Liston, Aaron; Rosenberg, Noah A

2017-08-04

Hybridization is observed in many eukaryotic lineages and can lead to the formation of polyploid species. The study of hybridization and polyploidization faces challenges both in data generation and in accounting for population-level phenomena such as coalescence processes in phylogenetic analysis. Genus Fragaria is one example of a set of plant taxa in which a range of ploidy levels is observed across species, but phylogenetic origins are unknown. Here, using 20 diploid and polyploid Fragaria species, we combine approaches from NGS data analysis and phylogenetics to infer evolutionary origins of polyploid strawberries, taking into account coalescence processes. We generate haplotype sequences for 257 low-copy nuclear markers assembled from Illumina target capture sequence data. We then identify putative hybridization events by analyzing gene tree topologies, and further test predicted hybridizations in a coalescence framework. This approach confirms the allopolyploid ancestry of F. chiloensis and F. virginiana, and provides new allopolyploid ancestry hypotheses for F. iturupensis, F. moschata, and F. orientalis. Evidence of gene flow between diploids F. bucharica and F. vesca is also detected, suggesting that it might be appropriate to consider these groups as conspecifics. This study is one of the first in which target capture sequencing followed by computational deconvolution of individual haplotypes is used for tracing origins of polyploid taxa. The study also provides new perspectives on the evolutionary history of Fragaria.

Challenging ocular image recognition

NASA Astrophysics Data System (ADS)

Pauca, V. Paúl; Forkin, Michael; Xu, Xiao; Plemmons, Robert; Ross, Arun A.

2011-06-01

Ocular recognition is a new area of biometric investigation targeted at overcoming the limitations of iris recognition performance in the presence of non-ideal data. There are several advantages for increasing the area beyond the iris, yet there are also key issues that must be addressed such as size of the ocular region, factors affecting performance, and appropriate corpora to study these factors in isolation. In this paper, we explore and identify some of these issues with the goal of better defining parameters for ocular recognition. An empirical study is performed where iris recognition methods are contrasted with texture and point operators on existing iris and face datasets. The experimental results show a dramatic recognition performance gain when additional features are considered in the presence of poor quality iris data, offering strong evidence for extending interest beyond the iris. The experiments also highlight the need for the direct collection of additional ocular imagery.

Evaluation of Nine Somatic Variant Callers for Detection of Somatic Mutations in Exome and Targeted Deep Sequencing Data

PubMed Central

Krøigård, Anne Bruun; Thomassen, Mads; Lænkholm, Anne-Vibeke; Kruse, Torben A.; Larsen, Martin Jakob

2016-01-01

Next generation sequencing is extensively applied to catalogue somatic mutations in cancer, in research settings and increasingly in clinical settings for molecular diagnostics, guiding therapy decisions. Somatic variant callers perform paired comparisons of sequencing data from cancer tissue and matched normal tissue in order to detect somatic mutations. The advent of many new somatic variant callers creates a need for comparison and validation of the tools, as no de facto standard for detection of somatic mutations exists and only limited comparisons have been reported. We have performed a comprehensive evaluation using exome sequencing and targeted deep sequencing data of paired tumor-normal samples from five breast cancer patients to evaluate the performance of nine publicly available somatic variant callers: EBCall, Mutect, Seurat, Shimmer, Indelocator, Somatic Sniper, Strelka, VarScan 2 and Virmid for the detection of single nucleotide mutations and small deletions and insertions. We report a large variation in the number of calls from the nine somatic variant callers on the same sequencing data and highly variable agreement. Sequencing depth had markedly diverse impact on individual callers, as for some callers, increased sequencing depth highly improved sensitivity. For SNV calling, we report EBCall, Mutect, Virmid and Strelka to be the most reliable somatic variant callers for both exome sequencing and targeted deep sequencing. For indel calling, EBCall is superior due to high sensitivity and robustness to changes in sequencing depths. PMID:27002637

High-fidelity target sequencing of individual molecules identified using barcode sequences: de novo detection and absolute quantitation of mutations in plasma cell-free DNA from cancer patients.

PubMed

Kukita, Yoji; Matoba, Ryo; Uchida, Junji; Hamakawa, Takuya; Doki, Yuichiro; Imamura, Fumio; Kato, Kikuya

2015-08-01

Circulating tumour DNA (ctDNA) is an emerging field of cancer research. However, current ctDNA analysis is usually restricted to one or a few mutation sites due to technical limitations. In the case of massively parallel DNA sequencers, the number of false positives caused by a high read error rate is a major problem. In addition, the final sequence reads do not represent the original DNA population due to the global amplification step during the template preparation. We established a high-fidelity target sequencing system of individual molecules identified in plasma cell-free DNA using barcode sequences; this system consists of the following two steps. (i) A novel target sequencing method that adds barcode sequences by adaptor ligation. This method uses linear amplification to eliminate the errors introduced during the early cycles of polymerase chain reaction. (ii) The monitoring and removal of erroneous barcode tags. This process involves the identification of individual molecules that have been sequenced and for which the number of mutations have been absolute quantitated. Using plasma cell-free DNA from patients with gastric or lung cancer, we demonstrated that the system achieved near complete elimination of false positives and enabled de novo detection and absolute quantitation of mutations in plasma cell-free DNA. © The Author 2015. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

The Drosophila hnRNP F/H Homolog Glorund Uses Two Distinct RNA-Binding Modes to Diversify Target Recognition.

PubMed

Tamayo, Joel V; Teramoto, Takamasa; Chatterjee, Seema; Hall, Traci M Tanaka; Gavis, Elizabeth R

2017-04-04

The Drosophila hnRNP F/H homolog, Glorund (Glo), regulates nanos mRNA translation by interacting with a structured UA-rich motif in the nanos 3' untranslated region. Glo regulates additional RNAs, however, and mammalian homologs bind G-tract sequences to regulate alternative splicing, suggesting that Glo also recognizes G-tract RNA. To gain insight into how Glo recognizes both structured UA-rich and G-tract RNAs, we used mutational analysis guided by crystal structures of Glo's RNA-binding domains and identified two discrete RNA-binding surfaces that allow Glo to recognize both RNA motifs. By engineering Glo variants that favor a single RNA-binding mode, we show that a subset of Glo's functions in vivo is mediated solely by the G-tract binding mode, whereas regulation of nanos requires both recognition modes. Our findings suggest a molecular mechanism for the evolution of dual RNA motif recognition in Glo that may be applied to understanding the functional diversity of other RNA-binding proteins. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

The Drosophila hnRNP F/H homolog glorund uses two distinct RNA-binding modes to diversify target recognition

DOE PAGES

Tamayo, Joel V.; Teramoto, Takamasa; Chatterjee, Seema; ...

2017-04-04

The Drosophila hnRNP F/H homolog, Glorund (Glo), regulates nanos mRNA translation by interacting with a structured UA-rich motif in the nanos 3' untranslated region. Glo regulates additional RNAs, however, and mammalian homologs bind G-tract sequences to regulate alternative splicing, suggesting that Glo also recognizes G-tract RNA. To gain insight into how Glo recognizes both structured UA-rich and G-tract RNAs, we used mutational analysis guided by crystal structures of Glo’s RNA-binding domains and identified two discrete RNA-binding surfaces that allow Glo to recognize both RNA motifs. By engineering Glo variants that favor a single RNA-binding mode, we show that a subsetmore » of Glo’s functions in vivo is mediated solely by the G-tract binding mode, whereas regulation of nanos requires both recognition modes. Lastly, our findings suggest a molecular mechanism for the evolution of dual RNA motif recognition in Glo that may be applied to understanding the functional diversity of other RNA-binding proteins.« less

The Drosophila hnRNP F/H Homolog Glorund Uses Two Distinct RNA-Binding Modes to Diversify Target Recognition

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

Tamayo, Joel V.; Teramoto, Takamasa; Chatterjee, Seema

The Drosophila hnRNP F/H homolog, Glorund (Glo), regulates nanos mRNA translation by interacting with a structured UA-rich motif in the nanos 3' untranslated region. Glo regulates additional RNAs, however, and mammalian homologs bind G-tract sequences to regulate alternative splicing, suggesting that Glo also recognizes G-tract RNA. To gain insight into how Glo recognizes both structured UA-rich and G-tract RNAs, we used mutational analysis guided by crystal structures of Glo’s RNA-binding domains and identified two discrete RNA-binding surfaces that allow Glo to recognize both RNA motifs. By engineering Glo variants that favor a single RNA-binding mode, we show that a subsetmore » of Glo’s functions in vivo is mediated solely by the G-tract binding mode, whereas regulation of nanos requires both recognition modes. Our findings suggest a molecular mechanism for the evolution of dual RNA motif recognition in Glo that may be applied to understanding the functional diversity of other RNA-binding proteins.« less

The Drosophila hnRNP F/H homolog glorund uses two distinct RNA-binding modes to diversify target recognition

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

Tamayo, Joel V.; Teramoto, Takamasa; Chatterjee, Seema

The Drosophila hnRNP F/H homolog, Glorund (Glo), regulates nanos mRNA translation by interacting with a structured UA-rich motif in the nanos 3' untranslated region. Glo regulates additional RNAs, however, and mammalian homologs bind G-tract sequences to regulate alternative splicing, suggesting that Glo also recognizes G-tract RNA. To gain insight into how Glo recognizes both structured UA-rich and G-tract RNAs, we used mutational analysis guided by crystal structures of Glo’s RNA-binding domains and identified two discrete RNA-binding surfaces that allow Glo to recognize both RNA motifs. By engineering Glo variants that favor a single RNA-binding mode, we show that a subsetmore » of Glo’s functions in vivo is mediated solely by the G-tract binding mode, whereas regulation of nanos requires both recognition modes. Lastly, our findings suggest a molecular mechanism for the evolution of dual RNA motif recognition in Glo that may be applied to understanding the functional diversity of other RNA-binding proteins.« less

ROBIN: a platform for evaluating automatic target recognition algorithms: I. Overview of the project and presentation of the SAGEM DS competition

NASA Astrophysics Data System (ADS)

Duclos, D.; Lonnoy, J.; Guillerm, Q.; Jurie, F.; Herbin, S.; D'Angelo, E.

2008-04-01

The last five years have seen a renewal of Automatic Target Recognition applications, mainly because of the latest advances in machine learning techniques. In this context, large collections of image datasets are essential for training algorithms as well as for their evaluation. Indeed, the recent proliferation of recognition algorithms, generally applied to slightly different problems, make their comparisons through clean evaluation campaigns necessary. The ROBIN project tries to fulfil these two needs by putting unclassified datasets, ground truths, competitions and metrics for the evaluation of ATR algorithms at the disposition of the scientific community. The scope of this project includes single and multi-class generic target detection and generic target recognition, in military and security contexts. From our knowledge, it is the first time that a database of this importance (several hundred thousands of visible and infrared hand annotated images) has been publicly released. Funded by the French Ministry of Defence (DGA) and by the French Ministry of Research, ROBIN is one of the ten Techno-vision projects. Techno-vision is a large and ambitious government initiative for building evaluation means for computer vision technologies, for various application contexts. ROBIN's consortium includes major companies and research centres involved in Computer Vision R&D in the field of defence: Bertin Technologies, CNES, ECA, DGA, EADS, INRIA, ONERA, MBDA, SAGEM, THALES. This paper, which first gives an overview of the whole project, is focused on one of ROBIN's key competitions, the SAGEM Defence Security database. This dataset contains more than eight hundred ground and aerial infrared images of six different vehicles in cluttered scenes including distracters. Two different sets of data are available for each target. The first set includes different views of each vehicle at close range in a "simple" background, and can be used to train algorithms. The second set

PAM-Dependent Target DNA Recognition and Cleavage by C2c1 CRISPR-Cas Endonuclease

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

Yang, Hui; Gao, Pu; Rajashankar, Kanagalaghatta R.

C2c1 is a newly identified guide RNA-mediated type V-B CRISPR-Cas endonuclease that site-specifically targets and cleaves both strands of target DNA. We have determined crystal structures of Alicyclobacillus acidoterrestris C2c1 (AacC2c1) bound to sgRNA as a binary complex and to target DNAs as ternary complexes, thereby capturing catalytically competent conformations of AacC2c1 with both target and non-target DNA strands independently positioned within a single RuvC catalytic pocket. Moreover, C2c1-mediated cleavage results in a staggered seven-nucleotide break of target DNA. crRNA adopts a pre-ordered five-nucleotide A-form seed sequence in the binary complex, with release of an inserted tryptophan, facilitating zippering upmore » of 20-bp guide RNA:target DNA heteroduplex on ternary complex formation. Notably, the PAM-interacting cleft adopts a “locked” conformation on ternary complex formation. Structural comparison of C2c1 ternary complexes with their Cas9 and Cpf1 counterparts highlights the diverse mechanisms adopted by these distinct CRISPR-Cas systems, thereby broadening and enhancing their applicability as genome editing tools.« less

psRNATarget: a plant small RNA target analysis server

PubMed Central

Dai, Xinbin; Zhao, Patrick Xuechun

2011-01-01

Plant endogenous non-coding short small RNAs (20–24 nt), including microRNAs (miRNAs) and a subset of small interfering RNAs (ta-siRNAs), play important role in gene expression regulatory networks (GRNs). For example, many transcription factors and development-related genes have been reported as targets of these regulatory small RNAs. Although a number of miRNA target prediction algorithms and programs have been developed, most of them were designed for animal miRNAs which are significantly different from plant miRNAs in the target recognition process. These differences demand the development of separate plant miRNA (and ta-siRNA) target analysis tool(s). We present psRNATarget, a plant small RNA target analysis server, which features two important analysis functions: (i) reverse complementary matching between small RNA and target transcript using a proven scoring schema, and (ii) target-site accessibility evaluation by calculating unpaired energy (UPE) required to ‘open’ secondary structure around small RNA’s target site on mRNA. The psRNATarget incorporates recent discoveries in plant miRNA target recognition, e.g. it distinguishes translational and post-transcriptional inhibition, and it reports the number of small RNA/target site pairs that may affect small RNA binding activity to target transcript. The psRNATarget server is designed for high-throughput analysis of next-generation data with an efficient distributed computing back-end pipeline that runs on a Linux cluster. The server front-end integrates three simplified user-friendly interfaces to accept user-submitted or preloaded small RNAs and transcript sequences; and outputs a comprehensive list of small RNA/target pairs along with the online tools for batch downloading, key word searching and results sorting. The psRNATarget server is freely available at http://plantgrn.noble.org/psRNATarget/. PMID:21622958

Experimental and statistical post-validation of positive example EST sequences carrying peroxisome targeting signals type 1 (PTS1).

PubMed

Lingner, Thomas; Kataya, Amr R A; Reumann, Sigrun

2012-02-01

We recently developed the first algorithms specifically for plants to predict proteins carrying peroxisome targeting signals type 1 (PTS1) from genome sequences. As validated experimentally, the prediction methods are able to correctly predict unknown peroxisomal Arabidopsis proteins and to infer novel PTS1 tripeptides. The high prediction performance is primarily determined by the large number and sequence diversity of the underlying positive example sequences, which mainly derived from EST databases. However, a few constructs remained cytosolic in experimental validation studies, indicating sequencing errors in some ESTs. To identify erroneous sequences, we validated subcellular targeting of additional positive example sequences in the present study. Moreover, we analyzed the distribution of prediction scores separately for each orthologous group of PTS1 proteins, which generally resembled normal distributions with group-specific mean values. The cytosolic sequences commonly represented outliers of low prediction scores and were located at the very tail of a fitted normal distribution. Three statistical methods for identifying outliers were compared in terms of sensitivity and specificity." Their combined application allows elimination of erroneous ESTs from positive example data sets. This new post-validation method will further improve the prediction accuracy of both PTS1 and PTS2 protein prediction models for plants, fungi, and mammals.

Experimental and statistical post-validation of positive example EST sequences carrying peroxisome targeting signals type 1 (PTS1)