题目内容
（请给出正确答案）
A.生物信息学
B.基因组学
C.蛋白质组学
D.表观遗传学
参考答案
简答题官方参考答案
（由简答题聘请的专业题库老师提供的解答）
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更多“Bioinformatics的含义是（）。”相关的问题
A.biocomp
B.bioinformatics
C.bioinformatique
D.bio-informatics
E.biocompute
Bioinformatics is a new computer software technology that makes research findings on genetic engineering publicly available to the public.
A．正确
B．错误
Scientists in California and Virginia will try to decode
genetic makeup of two plant-destroying microbes, including 【M1】______
one blaming for killing tens of thousands of oak trees along the 【M2】______
West Coast.
Backed by ＄4 million in federal grants, the scientists hope
to sequence the genomes of the two species of Phytophthora.
The most notorious of the pair is P. ramorum, that causes sudden【M3】______
oak death syndrome.
With the genomes in hand, scientists expect to develop
the mean to track, detect and, eventually, treat both diseases.【M4】______
P. ramorum has killed tens of thousands of black oak,
coast live oak and tan oak trees in northern California and
southern Oregon as it first appeared in 1995. This year, 【M5】______
scientists invented coast redwoods and Douglas fir also 【M6】______
are susceptible, as is at least 14 other plant species. 【M7】______
At the same time, scientists at the Walnut Creek laboratory
and at the Virginia Bioinformatics Institute in Blacksburg will
sequence the genome of P. sojae, a related microbe
responsible soy rot, which is estimated to cause ＄1 billion in 【M8】______
damages to soy Bean crops worldwide. Both sequences will be
free available on the Internet once completed. 【M9】______
The two species of funguslike organisms are closely
related to algae. Among their relatives is P. infestans, the microbe
responsible for the failure of potato crops in Ireland in the
19th century and the resulting famine. The name
Phytophthora means "plant devourer" in Greece. 【M10】______
【M1】
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？
A．A shortage of research funds.
B．A reluctance to acquire advanced mathematical skills.
C．An insufficient knowledge of computer languages.
D．An unwillingness to work cooperatively with mathematicians.
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