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pattern recognition in bioinformatics: 9th iapr international conference, prib 2014, Stockholm, Sweden, August 21-23, 2014. Proceedings 1

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丛书名： Lecture Notes in Computer Science 8626 Lecture Notes in bioinformatics

2014年

作者： Matteo Comin, Lukas Käll, Elena Marchiori, Alioune Ngom, Jagath Rajapakse (eds.)

ISBN: (数字)9783319091921

ISBN: (纸本)9783319091914;9783319091921

this book constitutes the refereed proceedings of the 8th iapr international conference on pattern recognition in bioinformatics, prib 2014, held in Stockholm, Sweden in August 2014. the 9 revised full papers and 9 revised short papers presented were carefully reviewed and selected from 29 submissions. the focus of the conference was on the latest Research in pattern recognition and Computational Intelligence-Based Techniques Applied to Problems in bioinformatics and Computational Biology.

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pattern recognition in bioinformatics - 9th iapr international conference, prib 2014, Proceedings

Pattern Recognition in Bioinformatics - 9th IAPR Internation...

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9th iapr international conference on pattern recognition in bioinformatics, prib 2014

ISBN: (纸本)9783319091914

the proceedings contain 11 papers. the topics discussed include: acquiring decision rules for predicting AMES-negative hepatocarcinogens using chemical-chemical interactions;using topology information for protein-protein interaction prediction;biases of drug-target interaction network data;logol: expressive pattern matching in sequences. application to ribosomal frameshift modeling;evolutionary algorithm based on new crossover for the biclustering of gene expression data;SFFS-SW: a feature selection algorithm exploring the small-world properties of GNs;CytomicsDB: a metadata-based storage and retrieval approach for high-throughput screening experiments;CUDAGRN: Parallel Speedup of Inferring Large Gene Regulatory Networks from expression data using random forest;supervised selective kernel fusion for membrane protein prediction;and analysis of miRNA expression profiles in breast cancer using biclustering.

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Guest Editorial: pattern recognition in bioinformatics

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND bioinformatics 2014年第3期11卷 498-499页

作者： Marchiori, Elena Ngom, Alioune Acharya, Raj Radboud Univ Nijmegen Fac Sci Dept Comp Sci NL-6525 AJ Nijmegen Netherlands Univ Windsor Sch Comp Sci Windsor ON N9B 3P4 Canada Penn State Univ Coll Engn Dept Comp Sci & Engn University Pk PA 16802 USA

Development and application of pattern recognition techniques in the field of bioinformatics is of utmost importance for gaining new insights about phenomena in life sciences through the analysis of biological data. In this special section, three research manuscripts in their significantly extended form were selected from the papers presented at the Eighth iapr international conference on pattern recognition in bioinformatics (prib 2013), which was held in Nice, France.

关键词： Special Issues And Sections Meetings bioinformatics Genomics pattern recognition Feature Extraction Semantics Proteins

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SFFS-SW: A Feature Selection Algorithm Exploring the Small-World Properties of GNs

SFFS-SW: A Feature Selection Algorithm Exploring the Small-W...

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9th iapr international conference on pattern recognition in bioinformatics (prib)

作者： da Rocha Vicente, Fabio Fernandes Lopes, Fabricio Martins Fed Univ Technol Curitiba Parana Brazil

ISBN: (纸本)9783319091921;9783319091914

In recent years, several methods for gene networks (GNs) inference from expression data have been developed. Also, models of data integration (as protein-protein and protein-DNA) are nowadays broadly used to face the problem of few amount of expression data. Moreover, it is well known that biological networks conserve some topological properties. the small-world topology is a common arrangement in nature found both in biological and non-biological phenomena. However, in general this information is not used by GNs inference methods. In this work we proposed a new GNs inference algorithm that combines topological features and expression data. the algorithm outperforms the approach that uses only expression data both in accuracy and measures of recovered network.

关键词： small-world gene networks feature selection graph theory pattern recognition bioinformatics

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Logol: Expressive pattern Matching in Sequences. Application to Ribosomal Frameshift Modeling

Logol: Expressive Pattern Matching in Sequences. Application...

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9th iapr international conference on pattern recognition in bioinformatics (prib)

作者： Belleannee, Catherine Sallou, Olivier Nicolas, Jacques Univ Rennes 1 Irisa Inria F-35042 Rennes France

ISBN: (纸本)9783319091921;9783319091914

Most of the current practice of pattern matching tools is oriented towards finding efficient ways to compare sequences. this is useful but insufficient: as the knowledge and understanding of some functional or structural aspects of living systems improve, analysts in molecular biology progressively shift from mere classification tasks to modeling tasks. People need to be able to express global sequence architectures and check various hypotheses on the way their sequences are structured. It appears necessary to offer generic tools for this task, allowing to build more expressive models of biological sequence families, on the basis of their content and structure. this article introduces Logol, a new application designed to achieve pattern matching in possibly large sequences with customized biological patterns. Logol consists in both a language for describing patterns, and the associated parser for effective pattern search in sequences (RNA, DNA or protein) with such patterns. the Logol language, based on an high level grammatical formalism, allows to express flexible patterns (with mispairings and indels) composed of both sequential elements (such as motifs) and structural elements (such as repeats or pseudoknots). Its expressive power is presented through an application using the main components of the language : the identification of -1 programmed ribosomal frameshifting (PRF) events in messenger RNA sequences. Logol allows the design of sophisticated patterns, and their search in large nucleic or amino acid sequences. It is available on the GenOuest bioinformatics platform at http://***. the core application is a command-line application, available for different operating systems. the Logol suite also includes interfaces, e. g. an interface for graphically drawing the pattern.

关键词： Molecular biology

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Diagnose the Premalignant Pancreatic Cancer Using High Dimensional Linear Machine

Diagnose the Premalignant Pancreatic Cancer Using High Dimen...

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7th international-Association-for-pattern-recognition (iapr) international conference on pattern recognition in bioinformatics (prib)

作者： Li, Yifeng Ngom, Alioune Univ Windsor Sch Comp Sci Windsor ON N9B 3P4 Canada

ISBN: (纸本)9783642341236

High throughput mass spectrometry technique has been extensively studied for the diagnosis of cancers. the detection of the pancreatic cancer at a very early stage is important to heal patients, but is very difficult due to biological and computational challenges. this paper proposes a simple classification approach which can be applied to the premalignant pancreatic cancer detection using mass spectrometry technique. Computational experiments show that our method outperforms the benchmark methods in accuracy and sensitivity without resorting to any biomarker selection, and the comparison with previous works shows that our method can obtain competitive performance.

关键词： mass spectrometry pancreatic cancer classification high dimensional linear machine

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pattern recognition in bioinformatics 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Matteo Comin Lukas Käll Elena Marchiori Alioune Ngom Jagath Rajapakse

ISBN: (数字)9783319091921

ISBN: (纸本)9783319091914

关键词： Computational Biology/bioinformatics Health Informatics pattern recognition Data Mining and Knowledge Discovery Algorithm Analysis and Problem Complexity Artificial Intelligence

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A Framework of Gene Subset Selection Using Multiobjective Evolutionary Algorithm

A Framework of Gene Subset Selection Using Multiobjective Ev...

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7th international-Association-for-pattern-recognition (iapr) international conference on pattern recognition in bioinformatics (prib)

作者： Li, Yifeng Ngom, Alioune Rueda, Luis Univ Windsor Sch Comp Sci Windsor ON N9B 3P4 Canada

ISBN: (纸本)9783642341236

Microarray gene expression technique can provide snap shots of gene expression levels of samples. this technique is promising to be used in clinical diagnosis and genomic pathology. However, the curse of dimensionality and other problems have been challenging researchers for a decade. Selecting a few discriminative genes is an important choice. But gene subset selection is a NP hard problem. this paper proposes an effective gene selection framework. this framework integrates gene filtering, sample selection, and multiobjective evolutionary algorithm (MOEA). We use MOEA to optimize four objective functions taking into account of class relevance, feature redundancy, classification performance, and the number of selected genes. Experimental comparison shows that the proposed approach is better than a well-known recursive feature elimination method in terms of classification performance and time complexity.

关键词： gene selection sample selection non-negative matrix factorization multiobjective evolutionary algorithm

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Versatile sparse matrix factorization and its applications in high-dimensional biological data analysis

Versatile sparse matrix factorization and its applications i...

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8th iapr international conference on pattern recognition in bioinformatics, prib 2013

作者： Li, Yifeng Ngom, Alioune School of Computer Science University of Windsor 401 Sunset Avenue Windsor ON N9B 3P4 Canada

ISBN: (纸本)9783642391583

Non-negative matrix factorization and sparse representation models have been successfully applied in high-throughput biological data analysis. In this paper, we propose our versatile sparse matrix factorization (VSMF) model for biological data mining. We show that many well-known sparse models are specific cases of VSMF. through tuning parameters, sparsity, smoothness, and non-negativity can be easily controlled in VSMF. Our computational experiments corroborate the advantages of VSMF. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Non-negative matrix factorization

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Analysis and segmentation of remote-sensing images for land-cover mapping 9th

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9th international conference on Image Analysis and Processing, ICIAP 1997

作者： Smits, P.C. Serpico, S.B. University of Genoa Department of Biophysical and Electronic Engineering Via alrOpera Pia 11A Genova16145 Italy

ISBN: (纸本)3540635084

In the framework of the European Community programme Training and Mobility for Researchers, the project Analysis and Segmentation of Remote-Sensing Images for Land-Cover mapping has been proposed and approved. this article provides some insight in the role of pattern recognition and image processing techniques in the European remote-sensing community and gives and overview of the project's objectives and results to date. © Springer-Verlag Berlin Heidelberg 1997.

关键词： pattern recognition

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