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Feature Selection Based on Physicochemical Properties of Redefined N-term Region and C-term Regions for Predicting Disorder

Feature Selection Based on Physicochemical Properties of Red...

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ieee symposium on computational intelligence and bioinformatics and computational biology (CIBCB)

作者： K. Shimizu Y. Muraoka S. Hirose T. Noguchi Department of Computer Science Graduate school of Waseda University Tokyo Japan PharmaDesign Inc. Tokyo Japan National Institute for Advanced Industrial Science and Technology Tokyo Japan

The prediction of intrinsic disorder from amino acid sequence has been gaining increasing attention because these have come to be known as important regions for protein functions. The most common way of predicting disorder is based on binary classification with machine learning. Since amino acid composition has different propensities in the N-term, C-term, and internal regions, the accuracy of prediction increases by dividing training data into these three regions and predicting them separately. However, previous work has lacked discussion about a concrete definition of the N-term and C-term regions, and has only used the heuristic length from the terminal. Other previous work has shown that general physicochemical properties rather than specific amino acids are important factors contributing to disorder, and a reduced amino acid alphabet can maintain excellent precision in predicting disorder. In this paper, we redefine a suitable length and position for the N-term and C-term regions for predicting disorder. Moreover, we show that each region has different physicochemical properties, which are important factors contributing to disorder. We also suggest a region-specific-reduced set of amino acid and modified PSSM based on that for predicting disorder. We implemented our method and (1) compare it with the conventional division method, (2) compare our feature selection with all physicochemical features, on casp6 benchmark, PDB dataset, and DisProt. The result supports that the method of new data separation is effective, and indicates each region has different physicochemical properties that are important factors for predicting protein disorders.

关键词： Proteins Amino acids Sequences Computer science Educational institutions Machine learning Training data computational biology Accuracy Concrete

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VIZ - A graphical open-source architecture for use in structural bioinformatics

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Brazilian symposium on bioinformatics - Advances in bioinformatics and computational biology

作者： Czekster, Ricardo M. De Souza, Osmar Norberte Laboratorio de Bioinformatica Modelagem e Simulacao de Biossistemas - LABIO PPGCC - FACIN PUCRS 6681. Predio 16 - Sala 106 90619-900 Porto Alegre RS Brazil

ISBN: (纸本)3540280081

Protein structure visualization is crucial for understanding its function inside the cell. Each year, laboratories around the world deposit protein structures on a central database for further analysis and research. The result is a large amount of structures being deposited (approximately 31,000 in may 2005). Visualization is a very powerful tool to help in the analysis, aiding data understanding and interpretation. The present work suggests an architecture to help the rapid construction of visual biomolecular software, specifically designed to be simple, modular and scalable. The architecture, called VIZ, employs high quality open-source libraries offering simple data structures and customizable options. The architecture can be used to start a new visual software project to visualize and represent individual protein structures, as well as multiple conformations from molecular dynamics simulation trajectories. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Proteins

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Fast and accurate structural RNA alignment by progressive lagrangian optimization

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1st International symposium on computational Life Sciences, CompLife 2005

作者： Bauer, Markus Klau, Gunnar W. Reinert, Knut Algorithmic Bioinformatics Group Institute of Computer Science Free University of Berlin Germany International Max Planck Research School on Computational Biology and Scientific Computing Germany Mathematics in Life Sciences Group Institute of Mathematics Free University of Berlin Germany

ISBN: (纸本)3540291040

During the last few years new functionalities of RNA have been discovered, renewing the need for computational tools for their analysis. To this respect, multiple sequence alignment is an essential step in finding structurally conserved regions in related RNA sequences. In contrast to proteins, many classes of functionally related RNA molecules show a rather weak sequence conservation but instead a fairly well conserved secondary structure. Hence, any method that relates RNA sequences in form of multiple alignments should take structural features into account, which has been verified in recent studies. Progress has been made in developing new structural alignment algorithms, however, current methods are computationally costly or do not have the desired accuracy to make them an everyday tool. In this paper we present a fast, practical, and accurate method for computing multiple, structural RNA alignments. The method is based on combining a new pairwise structural alignment method with the popular program T-Coffee. Our pairwise method is based on an integer linear programming (ILP) formulation resulting from a graph-theoretic reformulation of the structural alignment problem. We find provably optimal or near-optimal solutions of the ILP with a Lagrangian approach. Tests on a recently published benchmark set show that our Lagrangian approach outper-forms current programs in quality and in the length of the sequences it can align. © Springer-Verlag Berlin Heidelberg 2005.

关键词： RNA

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MAPPIS: Multiple 3D alignment of protein-protein interfaces

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1st International symposium on computational Life Sciences, CompLife 2005

作者： Shulman-Peleg, Alexandra Shatsky, Maxim Nussinov, Ruth Wolfson, Haim J. School of Computer Science Raymond and Beverly Sackler Faculty of Exact Sciences Tel Aviv University Tel Aviv 69978 Israel Sackler Inst. of Molecular Medicine Sackler Faculty of Medicine Tel Aviv University Tel Aviv 69978 Israel Basic Research Program SAIC-Frederick Inc. Lab. of Experimental and Computational Biology Frederick MD 21702 United States

ISBN: (纸本)3540291040

A protein-protein interface (PPI) is defined by a pair of regions of two interacting protein molecules that are linked by non-covalent bonds. Recognition of conserved 3D patterns of physico-chemical interactions may suggest their importance for the function as well as for the stability and formation of the protein-protein complex. It may assist in discovery of new drug leads that target these interactions. We present a novel method, MAPPIS, for multiple structural alignment of PPIs which allows recognition of a set of common physico-chemical properties and their interactions without the need to assume similarity of sequential patterns or backbone patterns. We show its application to several biological examples, such as alignment of interfaces of G proteins with their effectors and regulators, as well as previously created clusters of interfaces. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Proteins

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On learning performance evaluation for some psycho-learning experimental work versus an optimal swarm intelligent system

On learning performance evaluation for some psycho-learning ...

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5th ieee International symposium on Signal Processing and Information Technology

作者： Hassan, HM Educ Tech Dept Fac Specif Educ Banha Egypt

ISBN: (纸本)0780393139

Some models closely related to animal psycho-learning, and a swarm intelligent system, are comparatively presented. More specifically, three introduced models are inspired by creatures' behavioral learning phenomenon, observed in nature. Two of presented models based on Pavlov's and Thorndike's excremental work. Pavlov's dog learns how to associate two inputs sensory stimuli (audible, and visual signals). Thorndike's cat behavioral learning that to get out from a cage for obtaining food. Each of behavioral learning models improves its performance by minimizing response time period. Additionally, other third model motivated by ant colony system ACS. optimized performance. That model simulates a swarm (ant) intelligent system used for solving optimally traveling sales man problem TSP. That by bringing food from different food sources to store (in cycles) at ant's nest. Moreover, three other learning models based on pulsed neurons criterion, parallel genetic algorithmic programming, and modified Hebbian learning paradigm (Oja's rule). Interestingly, those models shown to behave analogously to previously suggested;Pavlov's, Thorndike's and ACS models.

关键词： artificial neural network modeling swarm intelligence ant colony system traveling salesman problem and computational biology

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Stochastic model of protease-ligand reactions

Stochastic model of protease-ligand reactions

引用

ieee symposium on bioinformatics and Bioengineering (BIBE)

作者： P. Anderson D. Raiford D. Sweeney T. Doom M. Raymer Department of Computer Science and Engineering Wright State University Dayton OH USA

Prediction of protein tertiary structure based on amino acid sequence is one of the most challenging open questions in computational molecular biology. The two most common experimental methods for determining protein structure, X-ray crystallography and nuclear magnetic resonance (NMR) are both relatively expensive and time consuming processes. Further, some proteins (such as largely hydrophobic membrane integral proteins) are resistant to crystallization. Thus, computational approaches for determination of protein conformation are an attractive alternative to experimental procedures. While many such algorithms exist, none can yet achieve the same accuracy and reliability as experimental structure determination techniques. The objective of this research is to combine experimental evidence with computational modeling for high-confidence structure prediction. Limited proteolysis and chemical modification data is used to drive the modeling process towards physically realizable structures. Here we present a stochastic simulation of a limited proteolysis experiment that models the behavior of a protease-ligand reaction at an abstracted molecular level. The results of this simulation will be used to validate rate constant prediction methods that will then be used for the selection and refinement of candidate models for computational structure determination.

关键词： Stochastic processes Proteins computational modeling biology computing Nuclear magnetic resonance Predictive models Biological system modeling Amino acids Sequences computational biology

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A methodology to enhance the semantics of links between PubMed publications and markers in the human genome

A methodology to enhance the semantics of links between PubM...

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ieee symposium on bioinformatics and Bioengineering (BIBE)

作者： A. Lash Woei-Jyh Lee L. Raschid Computational Biology Center Memorial Sloan Kettering Cancer Center New York NY USA Institute for Advanced Computer Studies University of Maryland College Park MD USA

Links in life science sources capture important biological knowledge. However, current simple physical link implementations do not explicitly represent this knowledge so that it can be easily shared among scientists. We develop a methodology for link extraction and generation, and link labeling to produce an enhanced e-link. The e-link associates each existing link with a link label that captures semantics of the link. We develop a machine assisted tool for curators to produce e-links and we develop a search interface for biologists to discover interesting e-links.

关键词： Humans Genomics bioinformatics Labeling Data mining Filtering Cancer computational biology biology computing Educational institutions

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Quartet-based phylogenetic inference: a grid approach

引用

2nd International symposium on Parallel and Distributed Processing and Applications, ISPA 2004

作者： Wang, Chen Zhou, Bing Bing Zomaya, Albert Y. School of Information Technologies University of Sydney NSW2006 Australia

ISBN: (纸本)9783540241287

The accuracy of quartet-puzzling method, which is widely used in molecular phylogenetic analysis depends heavily on the number of intermediate trees searched and the order of molecular sequences selected to generate these trees. Because the quality of intermediate trees cannot be guaranteed, the consensus results can easily be trapped into local optima. In this paper we present a new approach to guide the intermediate tree selection. Our experimental results show that the accuracy of reconstructed trees can be improved significantly. Using our method, the task can easily be partitioned into independent subtasks of different sizes. Therefore, it can effectively be implemented and run in the heterogeneous and dynamic environment of the computational grid. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Artificial intelligence

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Design issues of a novel toolkit for parallel application performance monitoring and analysis in cluster and grid environments

Design issues of a novel toolkit for parallel application pe...

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8th International symposium on Parallel Architectures, Algorithms and Networks, I-SPAN 2005

作者： Li, Kuan-Ching Wang, Hsiao-Hsi Chen, Chiou-Nan Liu, Chun-Chieh Chang, Chia-Fu Hsu, Chia-Wen Hung, Sheng-Shiang Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Shalu Taichung 43301 Taiwan Laboratory of Bioinformatics and Computational Biology Department of Computer Science National Tsing Hua University Hsinchu 30013 Taiwan

ISBN: (纸本)0769525091

The low-cost and availability of network of workstations have made them attractive solution for high performance computing. Striking progress of network technology is enabling high-performance global computing, with the utilization of cluster and grid technologies, in which computational and data resources in a local or wide area network are transparently employed to solve large-scale problems. In this paper, we present implementation and design rationale of Visuel* toolkit for performance measurement and analysis of parallel applications in cluster and grid environments. Most of performance visualization tools available today for high-performance platforms show solely system performance data (e.g., CPU load, memory usage, network bandwidth, server average load), and thus, being suitable for visualization of computing platform system activities. The Visuel toolkit is web-based interface designed to show performance, activities of all computing nodes of a cluster or grid computing platform involved in the execution of a parallel application, such as CPU load level and memory usage of each computing node. In addition, this toolkit is able to display comparative performance data visualizations generated from a number of executions of an application under investigation, analyzing the performance of different implementations. Evaluations using this toolkit show that it outperforms in easing the process of investigation and implementation of parallel applications, in effective way. © 2005 ieee.

关键词： Computer workstations

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GNARE: an environment for grid-based high-throughput genome analysis 05

GNARE: an environment for grid-based high-throughput genome ...

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ieee/ACM International symposium on Cluster Computing and the Grid (CCGRID)

作者： D. Sulakhe A. Rodriguez M. D'Souza M. Wilde V. Nefedova I. Foster N. Maltsev Mathematics and Computer Science Division Argonne National Laboratory Argonne IL USA Department of Computer Science University of Chicago Chicago IL USA

ISBN: (纸本)9780780390744

Recent progress in genomics and experimental biology has brought exponential growth of the biological information available for computational analysis in public genomics databases. However, applying the potentially enormous scientific value of this information to the understanding of biological systems requires computing and data storage technology of an unprecedented scale. The grid, with its aggregated and distributed computational and storage infrastructure, offers an ideal platform for high-throughput bioinformatics analysis. To leverage this we have developed the Genome Analysis Research Environment (GNARE) - a scalable computational system for the high-throughput analysis of genomes, which provides an integrated database and computational backend for data-driven bioinformatics applications. GNARE efficiently automates the major steps of genome analysis including acquisition of data from multiple genomic databases; data analysis by a diverse set of bioinformatics tools; and storage of results and annotations. High-throughput computations in GNARE are performed using distributed heterogeneous grid computing resources such as Grid2003, TeraGrid, and the DOE science grid. Multi-step genome analysis workflows involving massive data processing, the use of application-specific toots and algorithms and updating of an integrated database to provide interactive Web access to results are all expressed and controlled by a "virtual data" model which transparently maps computational workflows to distributed grid resources. This paper describes how Grid technologies such as Globus, Condor, and the Gryphyn virtual data system were applied in the development of GNARE. It focuses on our approach to Grid resource allocation and to the use of GNARE as a computational framework for the development of bioinformatics applications.

关键词： Genomics bioinformatics Grid computing biology computing Databases Distributed computing computational biology Information analysis Biological systems Memory

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