题目内容
There are some differences, of Course. The genetic code has four elements (known as bases or letters), while a computer's binary code has only two. And the bases of genetic code are grouped together in threes rather than in the eight-bit bytes of computing. But the similarities are so striking that biology is suddenly undergoing a serious amount of computerization. At the same time, there has been rapid progress in the machines that supply the raw material for the computer - the sequences of genetic bases to be analyzed. A single gene-sequencing machine can now read hundreds of thousands of bases per day; and newer technologies, such as "gene chips", should produce even more data to be stored and annotated for subsequent study.
The result is a mind-boggling amount of information. A genetics laboratory can easily produce 100 gigabytes of data a day--that is about 20,000 times the volume of data in the complete works of Shakespeare or J. S. Bach. The analysis of such data poses problems beyond mere volume control. Computer programs must analyze what constitutes a biologically meaningful relationship between a newly discovered sequence of DNA and existing sequences stored in a central database. Programming a computer for such tasks requires both extensive knowledge of computing theory and a keen biological intuition.
And there's the rub. The real problem about the growing quantification of biology is not the change in the subject but the lack of change in its practitioners. For a sudden in pouring of data is not unique to biology .Astronomers must now deal with squillions of bits of data from automatic sky surveys; particle physicists would not have the first idea of what was going on in their machines if the results of their experiments were not processed automatically. Yet neither of these fields seems to be suffering unduly from information overload because the physical sciences are founded on number crunching. Many biologists, however, avoided the fields of astronomy or particle physics because they have, in the delicately chosen words of Sylvia Spengler of the Center for Bioinformatics and Computational Genomics in California, "some problem with mathematics." The result is that there is a desperate shortage of specialists capable of developing the tools that biologists need. What is required is genuinely new kind of scientist who is trained both in computer science and biology. It used to be said that the physicists got all the research money. Now, however, it is the biologists' budgets that are growing. But there is a price. As biology becomes numerically rigorous, its practitioners have no choice but to do the same.
According to the author, what is the central problem facing biological researchers today？
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