Computational biology and bioinformatics : gene regulation : gene, RNA, protein, epigenetics
著者
書誌事項
Computational biology and bioinformatics : gene regulation : gene, RNA, protein, epigenetics
(A Science Publishers book)
CRC Press, Taylor & Francis Group, c2016
- : hard
大学図書館所蔵 全4件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
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.
目次
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.
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