生物学入门Perl编程：解析生物数据分析

perl

生物信息

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"《初识Perl生物信息学》是一本专为生物学家设计的Perl编程入门书籍，旨在帮助没有编程背景的生物学家快速跨越Perl语言障碍。书中将编程视为一种新的实验室技能，通过解决实际生物信息学问题来教授Perl程序和技巧。全书按照由简至繁的顺序组织，每章都围绕一个特定的生物信息学问题或问题类别展开，包括编程练习，通过展示和修改处理各种实际生物学问题的程序进行教学。读者在完成书中的学习后，将掌握Perl基础，拥有用于解析BLAST、GenBank记录等任务的程序，并具备进行更高级生物信息学编程的能力。书中的部分章节深入探讨了特定的生物信息学主题，适合作为课堂教材、自学资料和参考书。" 这本书覆盖了以下几个关键知识点： 1. **编程基础**：介绍编程的基本概念，如何使用Perl进行简单的编程操作。 2. **DNA序列和字符串处理**：讲解如何在Perl中处理生物数据，特别是DNA序列，这是生物信息学的核心内容。 3. **调试代码**：教授如何识别和修复程序中的错误，这对于任何程序员来说都是必不可少的技能。 4. **模拟基因突变**：使用随机数生成器来模拟基因变异，这是理解遗传变化和进化过程的重要工具。 5. **正则表达式**：介绍如何利用Perl的正则表达式功能查找和匹配数据中的模式，这对于解析生物数据至关重要。 6. **数组和哈希**：学习使用Perl的这两种数据结构来组织和操作生物信息学数据。 7. **关系数据库**：介绍如何利用Perl与数据库交互，管理和存储大量生物数据。 8. **解析PDB记录**：教授如何处理蛋白质数据银行（PDB）的记录，这对于结构生物学研究非常有用。 9. **GenBank注释和BLAST输出解析**：学习读取和分析这些常见的生物信息学输出格式，这对于序列比对和基因注释至关重要。通过本书的学习，生物学家不仅能掌握Perl编程，还能将其应用于实际的生物信息学研究中，解决具体的问题，从而提升实验效率和数据分析能力。书中使用的实例和练习旨在强化理论知识，并确保读者能够将所学应用到实践中。

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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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