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摘要翻译：
在过去的几十年里，计算机使生物科学发生了革命性的变化，以至于几乎所有当代生物科学研究都使用计算机程序。在硬件、软件和算法的基本发展的推动下，计算的进步已经在许多方面出现。这些进展影响，甚至产生了一系列惊人的生物科学领域，包括分子进化和生物信息学；全基因组、蛋白质组、转录组和代谢组的实验研究；结构基因组学；和细胞尺度的分子组装的原子模拟，大到核糖体和完整的病毒。简言之，后基因组生物学的许多部分正日益成为计算生物学的一种形式。设计和编写计算机程序的能力是现代研究人员所能培养的最不可缺少的技能之一。Python已经成为生物科学领域一种流行的编程语言，这主要是因为(i)它直接的语义和干净的语法使它成为一种容易访问的第一语言；㈡它具有表现力，非常适合面向对象编程以及其他现代范式；(iii)许多可用的库和第三方工具包将核心语言的功能扩展到几乎每一个生物领域（序列和结构分析、系统基因组学、工作流管理系统等）。本入门提供了通过Python进行编码的基本介绍，并包括具体的示例和练习来说明该语言的用法和功能；主文以结构生物信息学的最后一个项目而告终。还提供了一套补充章节。从基本概念开始，例如“变量”的概念，章节有条不紊地使读者达到编写图形用户界面来计算两个DNA序列之间的汉明距离的地步。
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英文标题：
《An Introduction to Programming for Bioscientists: A Python-based Primer》
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作者：
Berk Ekmekci, Charles E. McAnany, Cameron Mura
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最新提交年份：
2016
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分类信息：
一级分类：Quantitative Biology 数量生物学
二级分类：Other Quantitative Biology 其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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一级分类：Computer Science 计算机科学
二级分类：Programming Languages 程序设计语言
分类描述：Covers programming language semantics, language features, programming approaches (such as object-oriented programming, functional programming, logic programming). Also includes material on compilers oriented towards programming languages; other material on compilers may be more appropriate in Architecture (AR). Roughly includes material in ACM Subject Classes D.1 and D.3.
涵盖程序设计语言语义，语言特性，程序设计方法（如面向对象程序设计，函数式程序设计，逻辑程序设计）。还包括面向编程语言的编译器的材料；关于编译器的其他材料可能在体系结构(AR)中更合适。大致包括ACM主题课程D.1和D.3中的材料。
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英文摘要：
Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in the biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developments in hardware, software, and algorithms. These advances have influenced, and even engendered, a phenomenal array of bioscience fields, including molecular evolution and bioinformatics; genome-, proteome-, transcriptome- and metabolome-wide experimental studies; structural genomics; and atomistic simulations of cellular-scale molecular assemblies as large as ribosomes and intact viruses. In short, much of post-genomic biology is increasingly becoming a form of computational biology. The ability to design and write computer programs is among the most indispensable skills that a modern researcher can cultivate. Python has become a popular programming language in the biosciences, largely because (i) its straightforward semantics and clean syntax make it a readily accessible first language; (ii) it is expressive and well-suited to object-oriented programming, as well as other modern paradigms; and (iii) the many available libraries and third-party toolkits extend the functionality of the core language into virtually every biological domain (sequence and structure analyses, phylogenomics, workflow management systems, etc.). This primer offers a basic introduction to coding, via Python, and it includes concrete examples and exercises to illustrate the language's usage and capabilities; the main text culminates with a final project in structural bioinformatics. A suite of Supplemental Chapters is also provided. Starting with basic concepts, such as that of a 'variable', the Chapters methodically advance the reader to the point of writing a graphical user interface to compute the Hamming distance between two DNA sequences.
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PDF链接：
https://arxiv.org/pdf/1605.05419
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