Data Mining Techniques for the Life Sciences

1. Front Matter

   Pages i-xiii

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2. Databases

   1. Front Matter

      Pages 1-1

      PDF

   2. Update on Genomic Databases and Resources at the National Center for Biotechnology Information

      • Tatiana Tatusova

      Pages 3-30

   3. Protein Structure Databases

      • Roman A. Laskowski

      Pages 31-53

   4. The MIntAct Project and Molecular Interaction Databases

      • Luana Licata, Sandra Orchard

      Pages 55-69

   5. Applications of Protein Thermodynamic Database for Understanding Protein Mutant Stability and Designing Stable Mutants

      • M. Michael Gromiha, P. Anoosha, Liang-Tsung Huang

      Pages 71-89

   6. Classification and Exploration of 3D Protein Domain Interactions Using Kbdock

      • Anisah W. Ghoorah, Marie-Dominique Devignes, Malika Smaïl-Tabbone, David W. Ritchie

      Pages 91-105

   7. Data Mining of Macromolecular Structures

      • Bart van Beusekom, Anastassis Perrakis, Robbie P. Joosten

      Pages 107-138

   8. Criteria to Extract High-Quality Protein Data Bank Subsets for Structure Users

      • Oliviero Carugo, Kristina Djinović-Carugo

      Pages 139-152

   9. Homology-Based Annotation of Large Protein Datasets

      • Marco Punta, Jaina Mistry

      Pages 153-176

3. Computational Techniques

   1. Front Matter

      Pages 177-177

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   2. Identification and Correction of Erroneous Protein Sequences in Public Databases

      • László Patthy

      Pages 179-192

   3. Improving the Accuracy of Fitted Atomic Models in Cryo-EM Density Maps of Protein Assemblies Using Evolutionary Information from Aligned Homologous Proteins

      • Ramachandran Rakesh, Narayanaswamy Srinivasan

      Pages 193-209

   4. Systematic Exploration of an Efficient Amino Acid Substitution Matrix: MIQS

      • Kentaro Tomii, Kazunori Yamada

      Pages 211-223

   5. Promises and Pitfalls of High-Throughput Biological Assays

      • Greg Finak, Raphael Gottardo

      Pages 225-243

   6. Optimizing RNA-Seq Mapping with STAR

      • Alexander Dobin, Thomas R. Gingeras

      Pages 245-262

4. Prediction Methods

   1. Front Matter

      Pages 263-263

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   2. Predicting Conformational Disorder

      • Philippe Lieutaud, François Ferron, Sonia Longhi

      Pages 265-299

   3. Classification of Protein Kinases Influenced by Conservation of Substrate Binding Residues

      • Chintalapati Janaki, Narayanaswamy Srinivasan, Malini Manoharan

      Pages 301-313

   4. Spectral–Statistical Approach for Revealing Latent Regular Structures in DNA Sequence

      • Maria Chaley, Vladimir Kutyrkin

      Pages 315-340

This volume details several important databases and data mining tools. Data Mining Techniques for the Life Sciences, Second Edition guides readers through archives of macromolecular three-dimensional structures, databases of protein-protein interactions, thermodynamics information on protein and mutant stability, “Kbdock” protein domain structure database, PDB_REDO databank, erroneous sequences, substitution matrices, tools to align RNA sequences, interesting procedures for kinase family/subfamily classifications, new tools to predict protein crystallizability, metabolomics data, drug-target interaction predictions, and a recipe for protein-sequence-based function prediction and its implementation in the latest version of the ANNOTATOR software suite. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.

Authoritative and cutting-edge, Data Mining Techniques for the Life Sciences, Second Edition aims to ensure successful results in the further study of this vital field.

• protein-protein interactions
• align RNA sequences
• thermodynamics
• “Kbdock” protein domain structure database
• PDB_REDO databank
• protein crystallizability

“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)

• Max F. Perutz Laboratories GmbH, Universität Wien, Wien, Austria

  Oliviero Carugo

• Technology and Research (A*STAR), Agency for Science, Singapore, Singapore

  Frank Eisenhaber

Policies and ethics