Principles of Biomedical Informatics

Biomedical informatics (BMI) is an extraordinarily broad discipline. In scale, it spans across genes, cells, tissues, organ systems, individual patients, populations, and the world’s medical ecology. It ranges in methodology fromhardcoremathematicalmodeling to descriptive observations that use “soft”methods such as those of sociology. It studies, models and designs data, processes, policies, organizations, and systems.

The Cambridge Dictionary of Statistics (3rd Edition)

To provide students of statistics, working statisticians and researchers in many disciplines who are users of statistics with relatively concise definitions of statistical terms.

R统计语言手册（中文版）

作者 許湘伶 國立中山大學應用數學研究所 博士生 黃文璋 國立高雄大學應用數學系 教授 羅夢娜 國立中山大學應用數學系 教授

R统计软件导论（中文版）

该文档改自Bill Venables 和David M. Smith (Insightful 公司) 描述 S 和 SPLUS开发环境的讲义，并且扩充了一些材料。 各种评论和校正可以通过电子邮件R-core@R-project.org 联系。对于中文版的各种意见可以通过电子邮件ghding@gmail.com联系译者。

Data Mining With R

To introduce the reader to the use of R as a tool for performing data mining. R is a freely downloadable language and environment for statistical computing and graphics. Its capabilities and the large set of available packages turn this tool into an excellent alternative to the existing (and expensive!) data mining tools.

UCSC genome browser tutorial

The University of California Santa Cruz (UCSC) Genome Bioinformatics website consists of a suite of free, open-source, on-line tools that can be used to browse, analyze, and query genomic data. These tools are available to anyone who has an Internet browser and an interest in genomics. The website provides a quick and easy-to-use visual display of genomic data. It places annotation tracks beneath genome coordinate positions, allowing rapid visual correlation of different types of information. Many of the annotation tracks are submitted by scientists worldwide; the others are computed by the UCSC Genome Bioinformatics group from publicly available sequence data. It also allows users to upload and display their own experimental results or annotation sets by creating a custom track. The suite of tools, downloadable data files, and links to documentation and other information can be found at http://genome.ucsc.edu/.

生物信息学：序列和基因组分析

当前生物信息学研究重点是对基因组序列、蛋白质组学和数组技术所产生的大量数据的计算分析。本书对DNA、RNA和蛋白质数据的计算提供了丰富的演算方法，并指出了在解决生物学问题中这些方法的优缺点及应用策略。. 本书的第一版是在Mount博士讲稿的基础上进行整理出版的，在全球范围内用作教材。第二版对内容进行了全面的修订，由专业教师提供导读，最大程度地适用本科生和研究生教学。.. 本书为高等院校生物信息学专业本科生和研究生提供理想的学习材料。同时，本书也适宜科研人员、信息专家自学使用。 ..