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检索条件"任意字段=6th IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2011"

共 31 条记录，以下是1-10 订阅

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pattern recognition in bioinformatics - 6th iapr international conference, prib 2011, Proceedings

Pattern Recognition in Bioinformatics - 6th IAPR Internation...

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6th iapr international conference on pattern recognition in bioinformatics, prib 2011

ISBN: (纸本)9783642248542

the proceedings contain 29 papers. the topics discussed include: a new framework for co-clustering of gene expression data;biclustering of expression microarray data using affinity propagation;a two-way Bayesianmixture model for clustering in metagenomics;new gene subset selection approaches based on linear separating genes and gene-pairs;identification of biomarkers for prostate cancer prognosis using a novel two-step cluster analysis;renal cancer cell classification using generative embeddings and information theoretic kernels;integration of epigenetic data in Bayesian network modeling of gene regulatory network;metabolic pathway inference from time series data: a non iterative approach;highlighting metabolic strategies using network analysis over strain optimization results;and wrapper- and ensemble-based feature subset selection methods for biomarker discovery in targeted metabolomics.

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6th international conference on pattern recognition and Machine Intelligence, PReMI 2015

6th International Conference on Pattern Recognition and Mach...

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6th international conference on pattern recognition and Machine Intelligence, PReMI 2015

the proceedings contain 55 papers. the special focus in this conference is on pattern recognition and Machine Intelligence. the topics include: Recent Advances in Recommender Systems and Future Directions;On the Number of Rules and Conditions in Mining Data with Attribute-Concept Values and "Do Not Care" Conditions;Simplifying Contextual Structures;Towards a Robust Scale Invariant Feature Correspondence;Hierarchical Agglomerative Method for Improving NPS;A New Linear Discriminant Analysis Method to Address the Over-Reducing Problem;Procedural Generation of Adjustable Terrain for Application in Computer Games Using 2D Maps;Fixed Point Learning Based 3D Conversion of 2D Videos;Fast and Accurate Foreground Background Separation for Video Surveillance;Enumeration of Shortest Isothetic Paths Inside a Digital Object;Modified Exemplar-Based Image Inpainting via Primal-Dual Optimization;A Novel Approach for Image Super Resolution Using Kernel Methods;Generation of Random Triangular Digital Curves Using Combinatorial Techniques;Tackling Curse of Dimensionality for Efficient Content Based Image Retrieval;Face Profile View Retrieval Using Time of Flight Camera Image Analysis;Context-Based Semantic Tagging of Multimedia Data;Improved Simulation of Holography Based on Stereoscopy and Face Tracking;Head Pose Tracking from RGBD Sensor Based on Direct Motion Estimation;A Novel Hybrid CNN-AIS Visual pattern recognition Engine;Modified Orthogonal Neighborhood Preserving Projection for Face recognition;An Optimal Greedy Approximate Nearest Neighbor Method in Statistical pattern recognition.

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pattern recognition in bioinformatics 2012

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丛书名： Lecture Notes in Computer Science

2012年

作者： Tetsuo Shibuya Hisashi Kashima Jun Sese Shandar Ahmad

ISBN: (数字)9783642341236

ISBN: (纸本)9783642341229

this book constitutes the refereed proceedings of the 7th international conference on pattern recognition in bioinformatics, prib 2012, held in Tokyo, Japan, in November 2012. the 24 revised full papers presented were carefully reviewed and selected from 33 submissions. their topics are widely ranging from fundamental techniques, sequence analysis to biological network analysis. the papers are organized in topical sections on generic methods, visualization, image analysis, and platforms, applications of pattern recognition techniques, protein structure and docking, complex data analysis, and sequence analysis.

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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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Improving the Portability and Performance of *** - A Dynamic RNA Visualization Software

Improving the Portability and Performance of *** - A Dynamic...

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

作者： Shabash, Boris Wiese, Kay Glen, Edward Simon Fraser Univ Sch Comp Sci Burnaby BC V5A 1S6 Canada

ISBN: (纸本)9783642341236

In this paper, four methods were explored for improving the performance of ***'s structure drawing algorithm when dealing with large sequences;First, the approximation based Barnes-Hut algorithm was explored. Second, the effects of using multithreading were measured. additionally, dynamic C libraries, which integrate C code into the Java (TM) environment, were investigated. Finally, a technique termed structure recall was examined. the results demonstrated that the use of the Barnes-Hut algorithm produced the most drastic improvements in run-time, but distorts the structure if too crude of an approximation is used. Multithreading and integration of C code proved to be favorable approaches since these improved the speed at which calculations are done, without distorting the structures.

关键词： RNA

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pattern recognition for Subfamily Level Classification of GPCRs Using Motif Distillation and Distinguishing Power Evaluation

Pattern Recognition for Subfamily Level Classification of GP...

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

作者： Yavuz, Ahmet Sinan Ozer, Bugra Sezerman, Osman Ugur Sabanci Univ Fac Engn & Nat Sci Istanbul Turkey

ISBN: (纸本)9783642341236

G protein coupled receptors (GPCRs) are one of the most prominent and abundant family of membrane proteins in the human genome. Since they are main targets of many drugs, GPCR research has grown significantly in recent years. However the fact that only few structures of GPCRs are known still remains as an important challenge. therefore, the classification of GPCRs is a significant problem provoked from increasing gap between orphan GPCR sequences and a small amount of annotated ones. this work employs motif distillation using defined parameters, distinguishing power evaluation method and general weighted set cover problem in order to determine the minimum set of motifs which can cover a particular GPCR subfamily. Our results indicate that in Family A Peptide subfamily, 91% of all proteins listed in GPCRdb can be covered by using only 691 different motifs, which can be employed later as an invaluable source for developing a third level GPCR classification tool.

关键词： g-protein coupled receptors data mining pattern recognition

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Aligning Discovered patterns from Protein Family Sequences

Aligning Discovered Patterns from Protein Family Sequences

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

作者： Lee, En-Shiun Annie Zhuang, Dennis Wong, Andrew K. C. Univ Waterloo Ctr Pattern Anal & Machine Intelligence Waterloo ON N2L 3G1 Canada

ISBN: (纸本)9783642341236

A basic task in protein analysis is to discover a set of sequence patterns that characterizes the function of a protein family. To address this task, we introduce a synthesized pattern representation called Aligned pattern (AP) Cluster to discover potential functional segments in protein sequences. We apply our algorithm to identify and display the binding segments for the Cytochrome C. and Ubiquitin protein families. the resulting AP Clusters correspond to protein binding segments that surround the binding residues. When compared to the results from the protein annotation databases, PROSITE and pFam, ours are more efficient in computation and comprehensive in quality. the significance of the AP Cluster is that it is able to capture subtle variations of the binding segments in protein families. It thus could help to reduce time-consuming simulations and experimentation in the protein analysis.

关键词： Protein Analysis Protein Function Identification pattern Discovery pattern Clustering Hierarchical Clustering Motif Finding Local Alignment Approximate String Matching

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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： Marco Loog Marcel J. T. Reinders Dick Ridder Lodewyk Wessels

ISBN: (数字)9783642248559

ISBN: (纸本)9783642248542

this book constitutes the refereed proceedings of the 6th international conference on pattern recognition in bioinformatics, prib 2011, held in Delft, the Netherlands, in November 2011. the 29 revised full papers presented were carefully reviewed and selected from 35 submissions. the papers cover the wide range of possible applications of bioinformatics in pattern recognition: novel algorithms to handle traditional pattern recognition problems such as (bi)clustering, classification and feature selection; applications of (novel) pattern recognition techniques to infer and analyze biological networks and studies on specific problems such as biological image analysis and the relation between sequence and structure. they are organized in the following topical sections: clustering, biomarker selection and classification, network inference and analysis, image analysis, and sequence, structure, and interactions.

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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pattern recognition: 6th Mexican conference, MCPR 2014 Cancun, Mexico, June 25-28, 2014 Proceedings 6th

Pattern Recognition: 6th Mexican Conference, MCPR 2014 Cancu...

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6th Mexican conference on pattern recognition, MCPR 2014

作者： Martínez-Trinidad, José Francisco Carrasco-Ochoa, Jesús Ariel Olvera-López, José Arturo Salas-Rodríguez, Joaquín Suen, Ching Y. Sta. Maria Tonantzintla Mexico Puebla Mexico Querétaro Mexico Concordia University MontrealQC Canada

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Fast computation of entropic profiles for the detection of conservation in genomes

Fast computation of entropic profiles for the detection of c...

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

作者： Comin, Matteo Antonello, Morris Department of Information Engineering University of Padova Via Gradenigo 6/A Padova Italy

ISBN: (纸本)9783642391583

the information theory has been used for quite some time in the area of computational biology. In this paper we discuss and improve the function Entropic Profile, introduced by Vinga and Almeida in [23]. the Entropic Profiler is a function of the genomic location that captures the importance of that region with respect to the whole genome. We provide a linear time linear space algorithm called Fast Entropic Profile, as opposed to the original quadratic implementation. Moreover we propose an alternative normalization that can be also efficiently implemented. We show that Fast EP is suitable for large genomes and for the discovery of motifs with unbounded length. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Information theory

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