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检索条件"任意字段=IEEE Computational Systems Bioinformatics Conference"

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ABS: Sequence Alignment By Scanning

ABS: Sequence Alignment By Scanning

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Annual International conference of the ieee Engineering in Medicine and Biology Society

作者： Talal Bonny Khaled N. Salama Electrical Engineering Program King Abdullah University of Science and Technology (KAUST)

ISBN: (纸本)9781424441211

Sequence alignment is an essential tool in almost any computational biology research. It processes large database sequences and considered to be high consumers of computation time. Heuristic algorithms are used to get approximate but fast results. We introduce fast alignment algorithm, called 'Alignment By Scanning' (ABS), to provide an approximate alignment of two DNA sequences. We compare our algorithm with the well-known alignment algorithms, the 'FASTA' (which is heuristic) and the 'Needleman-Wunsch' (which is optimal). The proposed algorithm achieves up to 76% enhancement in alignment score when it is compared with the FASTA Algorithm. The evaluations are conducted using different lengths of DNA sequences.

关键词： Sequence Alignment DDX41 gene Antilock Braking systems ABS resins Alignment computational Biology bioinformatics Approximate scanning Heuristics algorithms DNA Sequence

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Inferring domain-domain interactions using an extended parsimony model

Inferring domain-domain interactions using an extended parsi...

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ieee International conference on systems Biology

作者： Chen Chen Jun-Fei Zhao Qiang Huang Wang, Rui-Sheng Zhang, Xiang-Sun National Center for Mathematics and Interdisciplinary Sciences Institute of Applied Mathematics Academy of Mathematics and Systems Science CAS Beijing 100190 China

ISBN: (纸本)9781457716614

High-throughput technologies have produced a large number of protein-protein interactions (PPIs) for different species. As protein domains are functional and structural units of proteins, many computational efforts have been made to identify domain-domain interactions (DDIs) from PPIs. Parsimony assumption is widely used in computational biology as the evolution of the nature is considered as a continuous optimization process. In the context of identifying DDIs, parsimony methods try to find a minimal set of DDIs that can explain the observed PPIs. This category of methods are promising since they can be formulated and solved easily. Besides, researches have shown that they could detect specific DDIs, which is often hard for many probabilistic methods. In this paper, we revisit the parsimony model by presenting two important extensions. First, ‘complex networks’as an emerging concept is incorporated as prior knowledge into the parsimony model. With this improvement, the prediction accuracy increases, which to some extent enhances the biological meaning of the common property of complex networks. Second, two randomization tests are designed to show the parsimony nature of the DDIs in mediating PPIs, which corroborates the model validation.

关键词： Clustering Coefficient Complex Networks Domain-Domain Interaction Parsimony Assumption Protein-Protein Interaction complex networks Protein-Protein Interaction Model checking Minimal Set Common property resources protein domain computational Biology bioinformatics Optimization Procedure

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Sequencing and disease variation detection tools and techniques

Sequencing and disease variation detection tools and techniq...

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ACS/ieee International conference on Computer systems and Applications

作者： Adam P. DeLuca Alex H. Wagner Kyle R. Taylor Ben Faga David Thole Val C. Sheffield Edwin M. Stone Thomas L. Casavant Todd E. Scheetz Terry A. Braun Center of Bioinformatics and Computational Biology University of Iowa Iowa IA USA Howard Hughes Medical Institute Iowa IA USA

Next-generation sequencing technology provides greater sequencing capacity to identify disease-causing variations. Currently there are many alignment tools and variation detection techniques, multiple SNP data sets used to filter out benign polymorphisms with the intent of enriching for disease-causing variations, and many tools and websites for annotating variations and performing pathogenicity prediction of variations. There is no consensus or standard with regards to which tools and corresponding parameter settings for each tool is appropriate for the different application of next-generation sequencing technologies for disease-causing variation identification. We have implemented an annotation pipeline that can easily use the output from different alignment tools (BLAT, BWA, BFAST, Bowtie) typically used to align sequence from next-generation sequencing and Sanger sequencing experiments. The Automated Sequence Analysis Pipeline (ASAP) reports variations using the HGVS standardized nomenclature[1] to facilitate comparison across tools and publications. To date, we have annotated the sequence from 13 exomes in an effort to identify disease-causing mutations.

关键词： bioinformatics Genomics Humans Pipelines Diseases Next generation networking

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A Structure-Based computational Mutagenesis Elucidates the Spectrum of Stability-Activity Relationships in Proteins

A Structure-Based Computational Mutagenesis Elucidates the S...

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Annual International conference of the ieee Engineering in Medicine and Biology Society

作者： Majid Masso Iosif I. Vaisman Laboratory for Structural Bioinformatics School of Systems Biology George Mason University

ISBN: (纸本)9781424441211

Protein engineering experiments involving single amino acid substitutions are routinely implemented for the analysis of protein structure, stability, and function. The resulting change in just one of these characteristics relative to the native protein constitutes the focus of any single study, as is the case with predictive computational models developed for the same purpose. Other than investigations into stability-activity trade-offs specifically resulting from active site residue replacements in a few enzymes, a literature survey fails to reveal a comprehensive analysis of stability-activity relationships in proteins upon mutation. Here, we employ a computational mutagenesis for quantifying overall protein structural change upon mutation, which is applied to a dataset of 938 single residue replacements distributed at positions throughout twenty diverse proteins. These mutants are selected based on the availability of both experimental stability and activity change data, and their structural change data are used to characterize the full range of stability-activity relationships.

关键词： Amino Acid Substitution Mutagenesis computational modeling literature survey Structural change Surgical Replantation comprehensive analysis BASES(STRUCTURES) FULL-SCALE Dataset Stability analysis

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Incorporating estimated motion in real-time background subtraction

Incorporating estimated motion in real-time background subtr...

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ieee International conference on Image Processing

作者： Minglun Gong Li Cheng Memorial University of Newfoundland Canada Bioinformatics Institute Agency for Science Technology and Research Singapore

Many existing background subtraction approaches model background color only and detect foreground as outliers, and hence may confuse background changes or noises with true foreground. We present a novel algorithm that utilizes motion cues computed from an optical flow algorithm. The additional motion information allows aligning moving foreground objects over time so that models can be built for foreground as well. It also facilities background (and foreground) modeling since both color and motion cues can be utilized. In practice, our GPU implementation is able to process QVGA-sized video sequences at 39.3 FPS on a laptop. Quantitative evaluation on standard testbeds demonstrate the competitive performance of our approach.

关键词： computational modeling Image color analysis Color conferences Real time systems Graphics processing unit

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Theoretical assessment of immunogenicity variation on the HA protein of H2N2 influenza virus by using fuzzy integral and SVM classifier

Theoretical assessment of immunogenicity variation on the HA...

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2011 International conference on Machine Learning and Cybernetics, ICMLC 2011

作者： Chen, Po-Fon Hsiao, Ya-Li Liu, Hsiang-Chuan Chang, Pei-Chun Department of Bioinformatics Asia University Wufeng Taichung 41354 Taiwan

ISBN: (纸本)9781457703065

Hemagglutinin (HA) is the surface protein of influenza viruses, which is known to play important role in the infection process. It is the antigen that inducing immune responses and currently be used as the influenza vaccine potency marker. Epitope are some segments in the antigen which could be recognized by the immune system specifically and induce immune response. The T-cell epitopes of protein antigens are some peptides that presented on the cell surface by MHC molecules via the MHC class I pathway or the MHC class II pathway. The antigen presentation mechanisms are different in these two pathways. The MHC class I pathway is used to present endogeneous antigens to cytotoxic T cell, while the MHC class II pathway is used to present the extracellular antigens to helper T cell. The epitope with strong immune response is good target for vaccine design. Recently, the type of H2N2 influenza has a tendency towards popular again. To understand the immunogenicity variation among the HA proteins of H2N2 influenza for the past decade is important for deciphering the infection tendency. It is also a clue to design effective vaccine in advance. Fuzzy measure considers a series of special classes of measures and defined by a special property, respectively. The concept of fuzzy measure theory was introduced by Choquet in 1953 and independently defined by Sugeno in 1974 in the context of fuzzy integrals. The Choquet integral is a fuzzy integral based on any fuzzy measure that provides a computational scheme for information aggregation. In this study, we proposed a novel algorithm with high accuracy in immunogenicity prediction based on fuzzy measure and SVM classifier. Accordingly, we applied this prediction method to assess the immunogenicity variation on the HA protein of H2N2 influenza virus for the past three decades. The results show that the immunogenicity strength decreased for MHC class II response that implied the increasing tendency of influenza outbreak by H2N2 virus.

关键词： T-cells

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Workshop: Inferring viral population from ultra-deep sequencing data

Workshop: Inferring viral population from ultra-deep sequenc...

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ieee International conference on computational Advances in Bio and Medical Sciences (ICCABS)

作者： Irina Astrovskaya Department of Computer Science Georgia State University Atlanta GA USA

Since existing high-throughput sequencing systems are originally designed for a single genome assembly, they cannot distinguish and simultaneously assemble multiple closely related sequences as well as estimate their relative abundances. This paper presents a novel approach in ViSpA software for quasispecies spectrum reconstruction. On simulated data, ViSpA accurately reconstructs up to 29 (out of 44) quasispecies in absence of genotyping errors. The ViSpA was also applied to real read data derived from blood sample of HCV-infected patient processed by Roche 454 Life Science machine. The sequenced region is half-genome long. The method reconstructed 10 most frequent sequences each of which represents a viable protein. The most frequent sequence has been within 1% from the actual ORF obtained by cloning the quasispecies. ShoRAH was able to reconstruct only one sequence that represents a viable protein. This sequence has 99.94% similarity with the fourth most frequent assemblies. Both methods returned similar frequency estimations for this sequence: 0.017% (ShoRAH) and 0.019% (ViSpA). The remaining top 9 quasispecies reconstructed by ShoRAH contain multiple stop codons in their corresponding amino-acid sequences which is an indication of unfixed systematic erroneous indels introduced by 454 Life Sciences machines. Additional experiments on 90% of read data shows that the ten most frequent assembled quasispecies are robustly reproduced by the sequencing process in ViSpA.

关键词： bioinformatics Genomics Software Assembly Frequency estimation Estimation Human immunodeficiency virus

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Structure-Based Prediction of Protein Activity Changes: Assessing the Impact of Single Residue Replacements

Structure-Based Prediction of Protein Activity Changes: Asse...

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Annual International conference of the ieee Engineering in Medicine and Biology Society

作者： Majid Masso Iosif I. Vaisman Laboratory for Structural Bioinformatics School of Systems Biology George Mason University

ISBN: (纸本)9781424441211

A computational mutagenesis methodology founded upon a structure-dependent and knowledge-based four-body statistical potential is utilized in generating feature vectors that characterize over 8500 individual amino acid substitutions occurring in seven proteins, each mutant having been experimentally ascertained for its relative effect on native protein activity. The proteins are diverse with respect to host organism (viral, bacterial, human) and function (enzymatic, nucleic acid binding, signaling), the structures span all four major SCOP classifications, and the mutations occur at positions well distributed throughout the seven structures. Implementation of the random forest algorithm, for classifying mutant activity as either unaffected or affected relative to the native protein, yields 84% accuracy based on tenfold cross-validation. A freely available online server for obtaining predictions with the trained model, which also displays 84% accuracy on an independent test set of mutants, is available at .

关键词： protein structure function Mutants BASES(STRUCTURES) Surgical Replantation Nucleic Acid Binding

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Discriminative random field approach to prediction of protein residue contacts

Discriminative random field approach to prediction of protei...

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ieee International conference on systems Biology

作者： Mayumi Kamada Morihiro Hayashida Jiangning Song Tatsuya Akutsu Bioinformatics Center Institute for Chemical Research Kyoto University Uji Kyoto Japan Department of Biochemistry and Molecular Biology Monash University Clayton VIC Australia Tianjin Institute of Industrial Biotechnology Chinese Academy of Sciences (CAS) Tianjin China

Understanding of interactions of proteins is important to reveal networks and functions of molecules. Many investigations have been conducted to analyze interactions and contacts between residues. It is supported that residues at interacting sites have co-evolved with those at the corresponding residues in the partner protein to keep the interactions between the proteins. Therefore, mutual information (MI) between residues calculated from multiple sequence alignments of homologous proteins is considered to be useful for identifying contact residues in interacting proteins. In our previous work, we proposed a prediction method for protein-protein interactions using mutual information and conditional random fields (CRFs), and confirmed its usefulness. The discriminative random field (DRF) is a special type of CRFs, and can recognize some specific characteristic regions in an image. Since the matrix consisted of mutual information between residues in two interacting proteins can be regarded as an image, we propose a prediction method for protein residue contacts using DRF models with mutual information. To validate our method, we perform computational experiments for several interactions between Pfam domains. The results suggest that the proposed DRF-based method with MI is useful for predicting protein residue contacts compared with that using the corresponding Markov random field (MRF) model.

关键词： Proteins Mutual information Amino acids Chemicals Zirconium Training Biological system modeling

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OntoHealth: A System to Process Ontologies Applied to Health Pervasive Environment

OntoHealth: A System to Process Ontologies Applied to Health...

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ieee International conference on Ubi-Media Computing

作者： Giovani R. Librelotto Leandro O. Freitas Andre Fiorin Bruno A. Mozzaquatro Leandro Pasetto Ricardo G. Martini Renato P. de Azevedo Rafael T. Pereira PPGI/DELC-Technology Center Federal University of Santa Maria Santa Maria Rio Grande do Sul Brazil Department of Bioinformatics University of Minho Braga Portugal

In the last years ontologies are being used in the development of pervasive computing applications. It is habitual their use for facilitating the interoperability among context-aware applications and the entities that may enter in the context at any time. This paper presents OntoHealth: a system to process ontologies applied to health pervasive environment. The main idea is that a hospital could be seen as this pervasive environment, where someone, through ubiquitous computing, engages a range of computational devices and systems simultaneously, in the course of ordinary activities, and may not necessarily even be aware that they are doing so. With the proposed ontology and the tool for its processing, the medical tasks can be shared by all components of this pervasive environment.

关键词： Ontologies Hospitals Context Pervasive computing Semantics Cognition

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