Pattern Recognition in Bioinformatics : 9th IAPR International Conference, PRIB 2014, Stockholm, Sweden, August 21-23, 2014. Proceedings / edited by Matteo Comin, Lukas Käll, Elena Marchiori, Alioune Ngom, Jagath Chandana Rajapakse.

Format:

Book

Contributor:

Comin, Matteo, Editor.

Käll, Lukas., Editor.

Marchiori, E., Editor.

Ngom, Alioune., Editor.

Rajapakse, Jagath Chandana, Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

Lecture notes in computer science. Lecture notes in bioinformatics 2366-6331 ; 8626

Lecture Notes in Bioinformatics, 2366-6331 ; 8626

Language:

English

Subjects (All):

Bioinformatics.

Medical informatics.

Pattern recognition systems.

Data mining.

Algorithms.

Artificial intelligence.

Computational and Systems Biology.

Health Informatics.

Automated Pattern Recognition.

Data Mining and Knowledge Discovery.

Artificial Intelligence.

Local Subjects:

Computational and Systems Biology.

Health Informatics.

Automated Pattern Recognition.

Data Mining and Knowledge Discovery.

Algorithms.

Artificial Intelligence.

Physical Description:

1 online resource (XII, 135 pages) : 29 illustrations

Edition:

1st ed. 2014.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2014.

System Details:

text file PDF

Summary:

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.

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 and othersEnsemble 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.

Other Format:

Printed edition:

ISBN:

978-3-319-09192-1

9783319091921

Access Restriction:

Restricted for use by site license.