Computational Biology and Bioinformatics: Gene Regulation

ISBN-13: 9780367782979 / Angielski / Miękka / 2021 / 438 str.

Wong, Ka-Chun

Opis

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.

Spis treści

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.

O autorze

Ka-Chun Wong