Computational Biology and Bioinformatics
Gene Regulation
1st Edition
Published on 31. March 2021
Book
Paperback/Softback
438 pages
978-0-367-78297-9 (ISBN)
Description
The advances in biotechnology such as the next generation sequencing technologies are occurring at breathtaking speed. Advances and breakthroughs give competitive advantages to those who are prepared. However, the driving force behind the positive competition is not only limited to the technological advancement, but also to the companion data analytical skills and computational methods which are collectively called computational biology and bioinformatics. Without them, the biotechnology-output data by itself is raw and perhaps meaningless. To raise such awareness, we have collected the state-of-the-art research works in computational biology and bioinformatics with a thematic focus on gene regulation in this book.
This book is designed to be self-contained and comprehensive, targeting senior undergraduates and junior graduate students in the related disciplines such as bioinformatics, computational biology, biostatistics, genome science, computer science, applied data mining, applied machine learning, life science, biomedical science, and genetics. In addition, we believe that this book will serve as a useful reference for both bioinformaticians and computational biologists in the post-genomic era.
This book is designed to be self-contained and comprehensive, targeting senior undergraduates and junior graduate students in the related disciplines such as bioinformatics, computational biology, biostatistics, genome science, computer science, applied data mining, applied machine learning, life science, biomedical science, and genetics. In addition, we believe that this book will serve as a useful reference for both bioinformaticians and computational biologists in the post-genomic era.
Reviews / Votes
This dense book is a collection of peer-reviewed chapters on the subject of bioinformatics and computational biology in the context of gene regulation. Each chapter was written by a unique set of authors, and the editor compiled the totality to fill a perceived information void. Given the multitude of authors, as well as the challenging subject matter, the readability of each chapter varies. The 17 chapters are organized into six sections covering genes; RNAs; proteins; epigenetics; a case study of gene mutations linked to drug resistance; and advanced topics covering quality assurance, computational trends in sequence alignment, state estimation and process monitoring, next-generation sequencing, metabolic engineering, evolutionary conservation, and protein model ranking. All the chapters are annotated well with references, numerous figures (in color, when necessary), equations, graphs, charts, models, and tables that effectively support the text. Many tables include descriptions, remarks, additional references, and databases with website links. According to the editor, this book is intended to be "self-contained and comprehensive" and geared toward upper-level undergraduates and beginning graduate students in the interdisciplinary areas where biology, computer science, and statistics congregate.--C. L. Iwema, University of Pittsburgh, appeard in February 2017 issues of CHOICE This dense book is a collection of peer-reviewed chapters on the subject of bioinformatics and computational biology in the context of gene regulation. Each chapter was written by a unique set of authors, and the editor compiled the totality to fill a perceived information void. Given the multitude of authors, as well as the challenging subject matter, the readability of each chapter varies. The 17 chapters are organized into six sections covering genes; RNAs; proteins; epigenetics; a case study of gene mutations linked to drug resistance; and advanced topics covering quality assurance, computational trends in sequence alignment, state estimation and process monitoring, next-generation sequencing, metabolic engineering, evolutionary conservation, and protein model ranking. All the chapters are annotated well with references, numerous figures (in color, when necessary), equations, graphs, charts, models, and tables that effectively support the text. Many tables include descriptions, remarks, additional references, and databases with website links. According to the editor, this book is intended to be "self-contained and comprehensive" and geared toward upper-level undergraduates and beginning graduate students in the interdisciplinary areas where biology, computer science, and statistics congregate.
--C. L. Iwema, University of Pittsburgh, appeard in February 2017 issues of CHOICE
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Dimensions
Height: 234 mm
Width: 156 mm
Weight
762 gr
ISBN-13
978-0-367-78297-9 (9780367782979)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Book
approx. 02/2018
1st Edition
CRC Press
approx.
€172.33
Not yet published
Book
05/2016
1st Edition
CRC Press
€267.50
Shipment within 15-20 days
E-Book
04/2016
1st Edition
CRC Press
€67.49
Available for download
Person
Ka-Chun Wong
Content
A Survey on Computational Methods for Enhancer and Enhancer Target Predictions. Cormotif: an R Package for Jointly Detecting Differential Gene Expression in Multiple Studies. Granger Causality for Time Series Gene Expression Data. RNA Sequencing and Gene Expression Regulation. Modern Technologies and Approaches for Decoding Non-coding RNA-mediated Biological Networks in Systems Biology and Their Applications. Annotation of Hypothetical Proteins, a Functional Genomics Approach. Protein-Protein Functional Linkage Predictions: Bringing Regulation to Context. Epigenomic Analysis of Chromatin Organization and DNA Methylation. Gene Body Methylation and Transcriptional Regulation: Statistical Modelling and More. Computational Characterization of Non-small-cell Lung Cancerwith EGFR Gene Mutations and Its Application to Drug Resistance Prediction. Quality Assurance in Genome-Scale Bioinformatics Analyses. Recent Computational Trends in Biological Sequence Alignment. 13. State Estimation and Process Monitoring of Nonlinear Biological Phenomena Modeled by S-systems. Next-Generation Sequencing and Metagenomics. METABOLIC ENGINEERING- Its Dimensions and Applications. Methods to Identify Evolutionary Conserved Regulatory Elements Using Molecular Phylogenetics in Microbes. Improved Protein Model Ranking through Topological Assessment.