Bioinformatics Database Systems

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A01=Jason T. L. Wang
A01=Katherine G. Herbert
A01=Kevin Byron
advanced biological data mining techniques
Author_Jason T. L. Wang
Author_Katherine G. Herbert
Author_Kevin Byron
bank
Bioinformatics Databases
biological
biological data integration
Case Study
Category=PS
Category=UN
Category=UNF
Cloud Computing
Cloud Service
Cloud Service Providers
cloud-based bioinformatics
computational genomics
Data Cleaning
Data Sets
databases
dna
EMBL Nucleotide Sequence Database
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_science
Gene Expression Datasets
gene regulatory modelling
GRN
information
japan
MapReduce
NDB
Network Inference
Non-coding RNA
omics data analysis
Ordinary Differential Equations
phylogenetic
Phylogenetic Trees
protein
Query Tree
Random Forests Classifier
Reference Genome
resource
RF Algorithm
RNA Junction
RNA Pseudoknot
Semi-supervised Methods
sequence alignment methods
tree
Unlabeled Examples
VM

Product details

  • ISBN 9780367574062
  • Weight: 462g
  • Dimensions: 156 x 234mm
  • Publication Date: 30 Jun 2020
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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Modern biological databases comprise not only data, but also sophisticated query facilities and bioinformatics data analysis tools. This book provides an exploration through the world of Bioinformatics Database Systems.

The book summarizes the popular and innovative bioinformatics repositories currently available, including popular primary genetic and protein sequence databases, phylogenetic databases, structure and pathway databases, microarray databases and boutique databases. It also explores the data quality and information integration issues currently involved with managing bioinformatics databases, including data quality issues that have been observed, and efforts in the data cleaning field.

Biological data integration issues are also covered in-depth, and the book demonstrates how data integration can create new repositories to address the needs of the biological communities. It also presents typical data integration architectures employed in current bioinformatics databases.

The latter part of the book covers biological data mining and biological data processing approaches using cloud-based technologies. General data mining approaches are discussed, as well as specific data mining methodologies that have been successfully deployed in biological data mining applications. Two biological data mining case studies are also included to illustrate how data, query, and analysis methods are integrated into user-friendly systems.

Aimed at researchers and developers of bioinformatics database systems, the book is also useful as a supplementary textbook for a one-semester upper-level undergraduate course, or an introductory graduate bioinformatics course.

Kevin Byron is a PhD candidate in the Department of Computer Science at the New Jersey Institute of Technology.

Katherine G. Herbert is Associate Professor of Computer Science at Montclair State University.

Jason T.L. Wang is Professor of Bioinformatics and Computer Science at the New Jersey Institute of Technology.

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