Data Mining Techniques for the Life Sciences

Author:   Oliviero Carugo ,  Frank Eisenhaber
Publisher:   Humana Press Inc.
Edition:   2nd ed. 2016
Volume:   1415
ISBN:  

9781493935703


Pages:   552
Publication Date:   27 April 2016
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Data Mining Techniques for the Life Sciences


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Full Product Details

Author:   Oliviero Carugo ,  Frank Eisenhaber
Publisher:   Humana Press Inc.
Imprint:   Humana Press Inc.
Edition:   2nd ed. 2016
Volume:   1415
Dimensions:   Width: 17.80cm , Height: 3.20cm , Length: 25.40cm
Weight:   1.671kg
ISBN:  

9781493935703


ISBN 10:   1493935704
Pages:   552
Publication Date:   27 April 2016
Audience:   Professional and scholarly ,  Professional and scholarly ,  Professional & Vocational ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Update on Genomic Databases and Resources at the National Center for Biotechnology Information.- Protein Structure Databases.- The MIntAct Project and Molecular Interaction Databases.- Applications of Protein Thermodynamic Database for Understanding Protein Mutant Stability and Designing Stable Mutants.- Classification and Exploration of 3D Protein Domain Interactions using Kbdock.- Data Mining of Macromolecular Structures.- Criteria to Extract High Quality Protein Data Bank Subsets for Structure Users.- Homology-based Annotation of Large Protein Datasets.- Identification and Correction Of Erroneous Protein Sequences in Public Databases.- Improving the Accuracy of Fitted Atomic Models in Cryo-EM Density Maps Of Protein Assemblies Using Evolutionary Information From Aligned Homologous Proteins.- Systematic Exploration of an Efficient Amino Acid Substitution Matrix, MIQS.- Promises and Pitfalls of High Throughput Biological Assays.- Optimizing RNA-seq Mapping with STAR.- Predicting Conformational Disorder.- Classification of Protein Kinases Influenced By Conservation of Substrate Binding Residues.- Spectral-Statistical Approach for Revealing Latent Regular Structures in DNA Sequence.- Protein Crystallizability.- Analysis and Visualization of ChIP-Seq and RNA-Seq Sequence Alignments using ngs.plot.- Data Mining with ontologies.- Functional Analysis of Metabolomics Data.- Bacterial Genomics Data Analysis in the Next-Generation Sequencing Era.- A Broad Overview of Computational Methods for Predicting the Pathophysiological Effects of Non-Synonymous Variants.- Recommendation Techniques for Drug-Target Interaction Prediction and Drug-Repositioning.- Protein Residue Contacts and Prediction Methods.- The Recipe for Protein Sequence-Based Function Prediction and its Implementation in the Annotator Software Environment.- Big Data, Evolution, and Metagenomes: Predicting Disease from Gut Microbiota Codon Usage Profiles.- Big Data in Plant Science: Resources and Data Mining Tools for Plant Genomics and Proteomics.  

Reviews

The style of the book and the assortment of topics which are presented make it accessible to a wide range of audiences, from undergraduates to established researchers, and from a variety of backgrounds, biologists, chemists, bioinformaticians. This collection of articles highlighting the state of the art for protein analyses, can also be used as a brief yet thorough starting point for post-graduate projects. (Irina Ioana Mohorianu, zbMATH 1353.92002, 2017)


“The style of the book and the assortment of topics which are presented make it accessible to a wide range of audiences, from undergraduates to established researchers, and from a variety of backgrounds, biologists, chemists, bioinformaticians. This collection of articles highlighting the state of the art for protein analyses, can also be used as a brief yet thorough starting point for post-graduate projects.” (Irina Ioana Mohorianu, zbMATH 1353.92002, 2017)


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