生物信息学入门：Perl编程指南

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"《Perl入门生物信息学指南》( Beginning Perl for Bioinformatics)是一本由James Tisdall编著，由O'Reilly出版社在2001年首次出版的专业书籍，专为那些对编程了解甚少但对生物信息学感兴趣的初学者设计。本书的ISBN号是0-596-00080-4，共384页，它以实用任务为导向，清晰地阐述了如何利用Perl这门语言进行生物数据处理。书中的内容特别适合那些希望提升生物数据分析技能但编程基础薄弱的读者。每一章都专注于解决特定的问题或一类问题，例如解析BLAST和GenBank数据，使读者在阅读过程中逐渐掌握Perl的基础知识，并学会编写一系列实用程序来应对生物信息学领域的挑战。通过学习，读者不仅能学会如何编写简单的脚本，还能培养处理更高级生物信息学编程任务的能力。该书结构清晰，分为两个主要部分：生物学与计算机科学的概述，以及Perl编程入门。在生物学部分，作者介绍了DNA和蛋白质的组织结构，以及计算在生物研究中的应用限制。这部分帮助读者理解生物信息学的核心概念和实际背景。在第二部分，作者引导读者踏上Perl的学习之旅，强调了Perl语言的优势，如易学且功能强大，适用于生物数据处理。书中详细讲述了如何在计算机上安装Perl，运行Perl程序，以及推荐使用文本编辑器以提高编程效率。同时，作者还提供了寻找帮助和解决问题的途径，让学习者能够快速适应并融入Perl编程环境。此外，作者还将讨论编程的本质，探讨不同的编程方法，帮助读者形成个体化的编程思维方式。通过这些内容，本书不仅提供了一门技术工具，也鼓励学习者发展批判性思维和解决问题的能力，这对于生物信息学领域来说至关重要。《Beginning Perl for Bioinformatics》是一本实用且富有启发性的教材，适合任何想要进入生物信息学领域并使用Perl语言进行数据分析的新手，无论是生物学家还是计算机科学家，都能从中受益匪浅。"

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positions at this point. This review is for the benefit of the nonbiologist; if you're a

biologist you can skip the next two sections.

DNA is a polymer composed of four molecules, usually called bases or nucleotides. Their

names and one-letter abbreviations are adenine (A), cytosine (C), guanine (G), and

thymine (T).

[1]

(See Chapter 4 for more about how DNA is represented as computer data.)

The bases joined end to end to form a single strand of DNA.

[1]

These names come from where they were originally found: the glands, the cell, guano, and

the thymus.

In the cell, DNA usually appears in a double-stranded form, with two strands wrapped

around each other in the famous double helix shape. The two strands of the double helix

have matching bases, known as the base pairs. An A on one strand is always opposite a T

on the other strand, and a G is always paired with a C.

There is also an orientation to the strands. One end of a nucleotide is called the 5' (five

prime) end, and the other is called the 3' (three prime) end. When nucleotides join to

make a single strand of DNA, they always connect the 5' end of one to the 3' end of the

other. Furthermore, when the cell uses the DNA, as in translating it to RNA, it does so

base by base from the 5' to the 3' direction. So, when DNA is written, it's done so left to

right on the page, corresponding to the 5' to 3' orientation of the bases. An encoded gene

can appear on either strand, so it's important to look at both strands when searching or

analyzing DNA.

When two strands are joined in a double helix (as in Figure 1-1), the two strands have

opposite orientations. That is, the 5' to 3' orientation of one strand runs in an opposite

direction as the 5' to 3' orientation of the other strand. So at each end of the double helix,

one strand has a 3' end; the other has a 5' end.

Figure 1-1. Two strands of DNA

Because the base pairs are always matched A-T and C-G and the orientation of the

strands are the reverse of each other, the term reverse complement describes the

relationship of the bases of the two strands. It's "reverse" because the orientations are

reversed, and "complement" because the bases always pair to their complementary bases,

A to T and C to G.

Given these facts and a single strand of DNA, it's easy to figure what the matching strand

would be in the double helix. Simply change all bases to their complements: A to T, T to

A, C to G, and G to C. Then, since DNA is written in the 5' to 3' direction, after

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complementing the DNA, write it in reverse.

Genbank, the Genetic Sequence Data Bank (http://www.ncbi.nlm.nih.gov), contains

most known sequence data. We'll take a closer look at GenBank in Chapter 10.

1.2 The Organization of Proteins

Proteins are somewhat similar to DNA. They are also polymers, long strings made up of

a small number of simple molecules. As DNA is composed of four nucleotides, so

proteins are composed of 20 amino acids. These amino acids may occur in any order. See

Table 4-2 for the names and one- and three-letter abbreviations for the amino acids.

Amino acids are composed of an amino group and a carboxyl group. They form a

chemical bond, called a peptide bond, between the amino group and the carboxyl group

of adjacent amino acids. Each of the 20 amino acids has a different sidechain, which

protrudes from the backbone. The chemical properties of the sidechains are important in

determining the properties of the protein.

Proteins usually have a more complex 3D structure than DNA. The peptide bonds have a

great deal of rotational freedom, which allows proteins to form many 3D structures.

Instead of DNA's double helix, proteins tend to fold up in a variety of different shapes

and are composed of one or more strands of amino acids assembled together.

[2]

The

sequence of amino acids along the strand is called the primary structure. The coiling in on

itself into local structures such as helices, beta-strands, and turns, is called the secondary

structure. The final foldings and assemblies are called the tertiary and quaternary

structure of proteins (see Chapter 11).

[2]

I try to avoid most of the potentially confusing biology in this text in order to concentrate

on learning Perl, but I can't help mentioning at this point that DNA also has a more complex

3D structure. It can appear as one-stranded, two-stranded, and three-stranded forms, and it

is also coiled and recoiled into a small space during most of the life of the cell.

There is more primary sequence data available than secondary or higher structural data.

In fact, a great deal of primary protein sequence data is available (since it is relatively

easy to identify primary protein sequence from DNA, of which a great deal has been

sequenced).

The Protein Data Bank (PDB) contains structural information about thousands of proteins,

the accumulated knowledge of decades of work. We'll look at the PDB in Chapter 10,

but you may want to get a headstart by visiting the PDB web site

(http://www.rcsb.org/pdb/) to become familiar with this essential bioinformatics

resource.

1.3 In Silico

Recently, the new term in silico has become a common reference to biological studies

carried out in the computer, joining the traditional terms in vivo and in vitro to describe

the location of experimental studies.

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For nonbiologists, in vitro means "in glass," that is, in the test tube; in vivo means "in

life," that is, in a living organism. The term in silico stems from the fact that most

computer chips are made primarily of silicon. Personally, I prefer a term such as in

algorithmo, since there are plenty of ways to compute that don't involve silicon, such as

the intriguing processes of DNA computing, quantum computing, optical computing, and

more.

The large amount of biological data available online has brought biological research to a

situation somewhat similar to physics and astronomy. Those sciences have found that

experiments in modern equipment produce huge amounts of data, and the computer isn't

only invaluable but necessary for exploring the data. Indeed, it's become possible to

simulate experiments entirely in the computer. For instance, an early use of computer

simulation in physics was in modeling the acoustics of a concert hall and then

experimenting with the results by changing the design of the hall—clearly a much

cheaper way to experiment than by building dozens of concert halls!

A similar trend has been occurring in biology since computers were first invented, but

this trend has sharply accelerated in recent years with the Human Genome Project and the

sequencing of the DNA of many organisms. The experimental data that has to be

collected, searched, and analyzed is often far too large for the unaided biologist, who is

now forced to rely on computers to manage the information.

Beyond the storage and retrieval of biological data, it's now possible to study living

systems through computer simulation. There are standard and accepted studies done

routinely on computers that access the genes of humans and of several other organisms.

When the sequence of some DNA is determined, it can be stored in the computer, and

programs can be written to identify restriction sites, perform restriction digests and create

restriction maps (see Chapter 9). Similarly, gene-finding programs can take sequenced

DNA and identify putative exons and introns. (Not perfectly, as of this writing, and

results differ for different organisms.) Models of cellular processes exist in which it is

possible to study for example, the effect of a change in the regulation of a gene.

Today, microarray technology (incorporating glass slides spotted with thousands of

samples that can be probed, usually with the aid of robotics) can assess the levels of

expression of thousands of genes with one laboratory run. Computers are helping to

unravel the complex interactions between genes. We hope to find, for example, all sets of

genes related by virtue of their protein products as part of a biochemical pathway in the

cell. Microarrays generate a large volume of data. This data needs to be stored, compared

with other experimental data, and analyzed on the computer.

On my first day as a programmer at Bell Labs Research, my boss told me that his

simulations could now be computed so fast—overnight—that it was creating a problem

for him. There wasn't enough time to think about the last simulation! Nevertheless, and

despite all the attendant headaches and pitfalls of computers, their use to simulate

experiments is proving to be beneficial in biology.

1.4 Limits to Computation

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Chapter 2. Getting Started with Perl

Perl is a popular programming language that's extensively used in areas such as

bioinformatics and web programming. Perl has become popular with biologists because

it's so well-suited to several bioinformatics tasks.

Perl is also an application, just like any other application you might install on your

computer. It is available (at no cost) and runs on all the operating systems found in the

average biology lab (Unix and Linux, Macintosh, Windows, VMS, and more).

[1]

The Perl

application on your computer takes a Perl language program (such as one of the programs

you will write in this book), translates it into instructions the computer can understand,

and runs (or "executes") it.

[1]

An operating system manages the running of programs and other basic services that a

computer provides, such as how files are stored.

So, the word Perl refers both to the language in which you will write programs and to the

application on your computer that runs those programs. You can always tell from context

which meaning is being used.

Every computer language such as Perl needs to have a translator application (called an

interpreter or compiler) that can turn programs into instructions the computer can actually

run. So the Perl application is often referred to as the Perl interpreter, and it includes a

Perl compiler as well. You will often see Perl programs referred to as Perl scripts or Perl

code. The terms program, application, script, and executable are somewhat

interchangeable. I refer to them as "programs" in this book.

2.1 A Low and Long Learning Curve

A nice thing about Perl is that you can learn to write programs fairly quickly; in essence,

Perl has a low learning curve. This means you can get started easily, without having

to master a large body of information before writing useful programs.

Perl provides different styles of writing programs. Since these are beyond the scope of

this book, I won't go into details, except to mention the popular style called imperative

programming that you'll learn in this book. The equally popular style called object-

oriented programming is also well-supported in Perl. Other styles of programming

include functional programming and logic programming.

Although you can get started quickly, learning all of Perl will certainly take awhile, if

that's your goal. Most people learn the basics, as presented in this book, and then learn

additional topics as needed.

Let's get a few elementary definitions out of the way:

What is a computer program?

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