Bioinformatics and Functional Genomics, 3rd Edition

Bioinformatics and Functional Genomics, 3rd Edition pdf epub mobi txt 电子书 下载 2026

出版者:Wiley-Blackwell
作者:Jonathan Pevsner
出品人:
页数:1160
译者:
出版时间:2015-10-26
价格:129.95
装帧:Hardcover
isbn号码:9781118581780
丛书系列:
图书标签:
  • 生物信息学
  • 生物学
  • bioinformatics
  • 美国
  • 专业
  • 2018
  • 生物信息学
  • 功能基因组学
  • 基因组学
  • 生物技术
  • 计算生物学
  • 分子生物学
  • 遗传学
  • 数据分析
  • 生物统计学
  • 测序技术
想要找书就要到 小哈图书下载中心
立刻按 ctrl+D收藏本页
你会得到大惊喜!!

具体描述

https://www.amazon.com/Bioinformatics-Functional-Genomics-Jonathan-Pevsner/dp/1118581784/ref=dp_ob_title_bk

From the Back Cover

The bestselling introduction to bioinformatics and genomics – now in its third edition

Widely received in its previous editions, Bioinformatics and Functional Genomics offers the most broad-based introduction to this explosive new discipline. Now in a thoroughly updated and expanded third edition, it continues to be the go-to source for students and professionals involved in biomedical research.

This book provides up-to-the-minute coverage of the fields of bioinformatics and genomics. Features new to this edition include:

Extensive revisions and a slight reorder of chapters for a more effective organization

A brand new chapter on next-generation sequencing

An expanded companion website, also updated as and when new information becomes available

Greater emphasis on a computational approach, with clear guidance of how software tools work and introductions to the use of command-line tools such as software for next-generation sequence analysis, the R programming language, and NCBI search utilities

The book is complemented by lavish illustrations and more than 500 figures and tables - many newly-created for the third edition to enhance clarity and understanding. Each chapter includes learning objectives, a problem set, pitfalls section, boxes explaining key techniques and mathematics/statistics principles, a summary, recommended reading, and a list of freely available software. Readers may visit a related Web page for supplemental information such as PowerPoints and audiovisual files of lectures, and videocasts of how to perform many basic operations: www.wiley.com/go/pevsnerbioinformatics.

Bioinformatics and Functional Genomics, Third Edition serves as an excellent single-source textbook for advanced undergraduate and beginning graduate-level courses in the biological sciences and computer sciences. It is also an indispensable resource for biologists in a broad variety of disciplines who use the tools of bioinformatics and genomics to study particular research problems; bioinformaticists and computer scientists who develop computer algorithms and databases; and medical researchers and clinicians who want to understand the genomic basis of viral, bacterial, parasitic, or other diseases.

作者简介

Jonathan Pevsner, PhD, is a Professor in the Department of Neurology at Kennedy Krieger Institute, an internationally recognized institution dedicated to improving the lives of children with neurodevelopmental disorders. He holds a primary faculty appointment as Professor in the Department of Psychiatry and Behavioral Sciences (Johns Hopkins University School of Medicine). He holds joint or secondary appointments in the Department of Neuroscience, the Institute of Genetic Medicine, and the Division of Health Sciences Informatics (Johns Hopkins School of Medicine), and the Department of Molecular Microbiology and Immunology (Johns Hopkins Bloomberg School of Public Health). He has taught bioinformatics courses since 2000 at the Johns Hopkins School of Medicine, and was awarded Teacher of the Year honors by the Graduate Student Association in both 2001 and 2006, the Professors’ Award for Excellence in Teaching awarded by the medical faculty (2003), Teacher of the Year (Advanced Academic Programs, 2009), and Teaching Excellence Award in the Johns Hopkins Bloomberg School of Public Health (2011). In 2013 his lab used whole genome sequencing and reported a mutation that causes a rare disease, Sturge-Weber syndrome, as well as a commonly occurring port-wine stain birthmark.

目录信息

Part I Analyzing DNA RNA and Protein Sequences
1 Introduction 3
2 Access to Sequence Data and Related Information 19
3 Pairwise Sequence Alignment 69
4 Basic Local Alignment Search Tool (BLAST) 121
5 Advanced Database Searching 167
6 Multiple Sequence Alignment 205
7 Molecular Phylogeny and Evolution 245
Part II Genomewide Analysis of DNA RNA and Protein
8 DNA: The Eukaryotic Chromosome 307
9 Analysis of Next-Generation Sequence Data 377
10 Bioinformatic Approaches to Ribonucleic Acid (RNA) 433
11 Gene Expression: Microarray and RNA-seq Data Analysis 479
12 Protein Analysis and Proteomics 539
13 Protein Structure 589
14 Functional Genomics 635
Part III Genome Analysis
15 Genomes Across the Tree of Life 699
16 Completed Genomes: Viruses 755
17 Completed Genomes: Bacteria and Archaea 797
18 Eukaryotic Genomes: Fungi 847
19 Eukaryotic Genomes: From Parasites to Primates 887
20 Human Genome 957
21 Human Disease 1011
GLOSSARY 1075
Self-Test Quiz: Solutions 1103
Author Index 1105
Subject Index 1109
· · · · · · (收起)

读后感

评分

评分

评分

评分

评分

用户评价

评分

这本书的价值在于其对“整合”概念的深刻阐述。在功能基因组学领域,孤立地看待基因表达或蛋白质互作都是片面的,真正有价值的发现往往来自于多组学数据的整合分析。本书用数个章节专门讲解了如何将表观遗传学数据(如ChIP-seq, ATAC-seq)与基因表达数据进行关联分析,试图勾勒出基因调控的完整图景。作者详细介绍了不同的整合策略,从简单的通路富集分析到复杂的网络构建模型,每一步的原理和局限性都讲解得非常透彻,避免了新手在数据融合时常见的“拉低档次”的错误。阅读这本书的过程,就像是跟着一位经验丰富的导师进行了一次漫长的项目规划。它教导我们,每一个实验设计、每一步分析选择,都必须有明确的生物学目标作为导向,而不是盲目地应用最新潮的工具。对于那些希望从纯粹的生物实验转向数据驱动研究的学者而言,这本书是不可或缺的桥梁,它为你提供了跨越深渊所需的稳固基石和清晰的路径图。

评分

这本《生物信息学与功能基因组学》(第三版)简直是我近期阅读体验中的一股清流。作者在开篇就构建了一个宏大而又精密的知识体系框架,初学者可能会被那些复杂的术语和庞大的图谱吓到,但耐心深入下去,你会发现作者的叙述逻辑简直是教科书级别的严谨。尤其值得称赞的是,书中对于数据处理流程的描述,并非停留在理论层面,而是紧密结合了当前业界主流的软件和算法,例如在处理高通量测序数据时的质量控制、比对策略的权衡,讲得细致入微,仿佛作者就在我旁边手把手指导操作一般。我尤其欣赏它对统计学基础在生物学应用中的强调,很多时候我们只看到结果,却忽略了背后的显著性检验和模型假设,这本书有效地填补了这一知识盲点,让生物信息分析的结果更有说服力。当然,对于一些前沿热点,比如单细胞测序数据的批次效应校正,虽然有所提及,但可能在深度上还略显不足,需要结合最新的期刊文献来补充,但这对于一本综合性的教材来说,已经是相当出色的平衡了。整体而言,这本书是搭建坚实基础的绝佳工具书,它教会你“如何思考”数据,而不仅仅是“如何运行”代码。

评分

说实话,刚翻开这本第三版时,我有点担心它会不会是那种陈旧的、只是修修补补的旧酒装新瓶。然而,事实证明我的担忧是多余的。这次的修订明显注入了新的活力,特别是关于非编码RNA功能研究那几个章节,简直是信息量爆炸。它不仅梳理了miRNA、lncRNA的经典调控网络,更深入探讨了环状RNA(circRNA)的生物学意义及其在疾病中的潜在应用,这部分内容的更新速度跟得上最新的科研进展。作者的文笔非常具有引导性,不是那种干巴巴的罗列事实,而是用大量的案例研究来串联知识点。比如,在讲解转录组组装时,它对比了De Novo组装和参考基因组映射的不同适用场景,并用一个实际的植物基因组案例作为对比,清晰地展示了每种方法的优缺点和计算资源需求。这种教学方法极大地提升了读者的实战能力。我个人觉得,对于已经有一定基础的研究生来说,这本书更像是提升“策略制定”能力的参考手册,能帮助你从一个“操作员”晋升为能独立设计实验流程的“架构师”。唯一的小遗憾是,关于空间转录组学的介绍还比较初步,这块的快速发展未来应该会得到更详尽的阐述。

评分

这本书给我的整体感觉是“厚重而务实”。它成功地跨越了生物学与计算科学之间的鸿沟,让原本看似晦涩难懂的算法原理,通过生物学的实际问题得到了完美的诠释。比如,在介绍聚类分析时,作者没有直接抛出K-means或层次聚类公式,而是先从“我们如何将表现相似的细胞或基因归为一类”这个生物学问题出发,自然而然地引出了降维和聚类的必要性。这种“问题驱动”的叙事方式,极大地降低了入门的心理门槛。此外,书中对数据可视化工具的介绍也相当到位,从基础的箱线图、散点图,到高级的火山图、热图,作者都给出了R语言或Python的代码示例,并且强调了“好的图表胜过千言万语”的原则,教会我们如何用图形讲好数据故事。对于初入实验室的本科生来说,这本书可能是他们接触到的第一本真正意义上的“工具书”,它提供的不仅仅是知识,更是一种严谨的科研规范。如果你期待的是那种轻薄易读、侧重于炒作概念的读物,那这本书可能不太适合你,因为它需要你投入时间和精力去消化这些硬核内容。

评分

阅读体验上,这本第三版在排版和图示的清晰度上做得非常出色,对于一本涉及大量流程图和分子结构图的专业书籍来说,这一点至关重要。相较于市面上一些版本陈旧的教材,它对计算复杂性和时间效率的讨论也更加与时俱进。它没有回避NGS(新一代测序)数据分析中常见的“大数据”挑战,而是着重讲解了如何利用云计算平台和并行计算框架来加速分析,这在当前科研环境下几乎是必备技能。我特别欣赏它在伦理和数据共享部分所花费的笔墨。在生物信息学日益与个人隐私数据深度绑定的今天,作者对数据匿名化、数据所有权和开放科学原则的探讨,体现了高度的社会责任感。这使得本书不仅仅是一本技术手册,更是一本引导未来科学家树立正确科研价值观的指南。虽然一些更偏向于机器学习在生物学中应用的章节,比如深度学习在蛋白质结构预测方面的进展,内容略显精简,但作为一本侧重于基因组学和转录组学基础的教材,它的平衡点把握得相当精准,内容足够支撑大部分生命科学研究的起步阶段。

评分

评分

评分

评分

评分

本站所有内容均为互联网搜索引擎提供的公开搜索信息,本站不存储任何数据与内容,任何内容与数据均与本站无关,如有需要请联系相关搜索引擎包括但不限于百度google,bing,sogou

© 2026 qciss.net All Rights Reserved. 小哈图书下载中心 版权所有