Computers+Biology=Bioinformatics

[编者的话]

经常有人会问：如何能让自己变成一个生物信息学家。说实话，这样的问题不好回答，因为我自己也常常问自己这样的问题，希望看了这篇文章你和我都有所启发。

by Cynthia Gibas, coauthor of Developing Bioinformatics Computer Skills

Key Skills and Knowledge for Bioinformatics

As professional data analysts in a specialized field, bioinformaticians need to have a solid understanding of both computational analysis methods and the biological questions they're meant to answer. A lack of biological understanding can result in sophisticated computational methods being applied naively and in ways which aren't really helpful to biologists. A lack of analytical sophistication means that interesting features of biological data may go undiscovered.

In 1998, Dr. Russ Altman, now president of the International Society for Computational Biology, published an article called A Curriculum for Bioinformatics: The Time is Ripe, which enumerated some of the many skills that are useful for aspiring bioinformaticians.

Critical knowledge and skills he identified for bioinformaticians include:

·         Established methods for sequence analysis, such as pairwise and multiple sequence alignment and construction of phylogenetic trees, sequence fragment and map assembly, and prediction or extraction of features from sequences.

·         Established methods for molecular structure analysis and simulation, such as geometry analysis, structure modeling, and molecular dynamics.

·         Computational support of laboratory biology, a broad category that could be conceived of as including everything from signal detection and processing to statistical analysis.

·         Design, implementation, and integration of biological databases.

·         Key algorithms and methods of bioinformatics, such as dynamic programming, optimization, classification and cluster analysis, and neural networks.

Even more basic, however, are the key skills pointed out to us by some of our colleagues in the bioinformatics field:

·         Understanding of the scientific method: how experiments are designed and carried out to test hypotheses, and standards for reporting scientific research.

·         Understanding the foundations of molecular biology: how genomic information is transmitted and used in living cells.

·         Facility with computers: everything from the ability to learn to use new software quickly to the ability to work comfortably in a command-line (Unix) environment.

·         Knowledge of a programming language such as C or C++ and a scripting language, such as Perl or Python.

The first two areas are the province of biologists, the latter two of computer scientists. Both sets of knowledge are considered basic to their field and are usually the focus of a good deal of training, generally an entire undergraduate degree. It's rare to find a combination of these skills in one individual. It sometimes seems that in order to retrain for bioinformatics, you'd need an entire new degree. But that's not very practical.

So, How Do I Retrain Myself for Bioinformatics?

The answer to the retraining question depends on how far you want to go on the continuum from programming to scientific research.

If you're going to be a programmer on a bioinformatics project, what you need to learn is enough biology so that you can talk to biological scientists, because they will be asking you to put their ideas into action on the computer. That means knowing on a general level what the important molecules of life are (DNA, RNA, proteins, metabolites), what they're made of, and what kinds of things they do. It's also helpful to understand how the information in the genome is used in living systems by translation into molecules that subsequently interact with each other to carry out life processes.

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Once you know these basics, then you may want to learn about some existing bioinformatics and computational biology methods and how they work. Some universities offer bioinformatics certification programs for computer professionals.

If you see yourself making the transition from programmer to scientist and actually developing new bioinformatics methods, you'll need more than a thin gloss of biology over your computer competence. This is where bioinformatics graduate programs come in. Scientists go through the arduous and life-sucking process of graduate school to do more than just take a few more classes. They're there to learn the rules and process of scientific research from hypothesis to experiment to publication. If this is the road that you choose to take, consider applying to one of the many new graduate programs in bioinformatics and computational biology.