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Computer Science - Bioinformatics | Pattern Recognition in Bioinformatics - 9th IAPR International Conference, PRIB 2014, Stockholm,

Pattern Recognition in Bioinformatics

9th IAPR International Conference, PRIB 2014, Stockholm, Sweden, August 21-23, 2014. Proceedings

Comin, M., Käll, L., Marchiori, E., Ngom, A., Rajapakse, J.C. (Eds.)

2014, XII, 135 p. 29 illus.

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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.

Content Level » Research

Keywords » Bioinformatics - Computational biology - Pattern Matching - Pattern recognition - Protein-Protein Interaction Prediction - classification - computational proteomics - data mining - graph theory - information theory - support vector machines

Related subjects » Artificial Intelligence - Bioinformatics - Database Management & Information Retrieval - Image Processing - Public Health - Theoretical Computer Science

Table of contents 

FULL PAPERS.- 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.- SHORT ABSTRACTS.- Analysis of miRNA expression profiles in breast cancer using biclustering.- Gram-positive and Gram-negative Subcellular Localization Using Rotation Forest and Physicochemical-based Features.- Data Driven Feature Selection for RNA-Seq Differential Expression Analysis.- Intramuscular fat percentage estimation through ultrasound images.- An integrated approach of gene expression and DNA-methylation profiles of WNT signaling genes uncovers novel prognostic markers in Acute Myeloid Leukemia.- Improving performance of the eXtasy model by hierarchical sampling.- Popovic et al.Ensemble Neural Networks Scoring Functions for Accurate Binding Affinity.- Prediction of Protein-Ligand Complexes.- Integration of Gene Expression and DNA-methylation Profiles Improves Molecular Subtype Classification in Acute Myeloid Leukemia.- The Relative Vertex-to-Vertex Clustering Value- A New Criterion for the Fast Detection of Functional Modules in Protein Interaction Networks.

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