University bioinformatics programs on the rise
University bioinformatics programs on the rise
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DOI：
10.1038/85758
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发表时间：
2001-03-01
影响因子：
46.9
通讯作者：
Zauhar, RJ
中科院分区：
文献类型：
--
作者：
Zauhar, RJ
职业自然生物技术·第19卷·2001年3月·http://biotech.大自然。COM 286 Rithms以及如何用C/C++、Java和Perl实现它们，并获得了构建大型数据库的经验。对于那些计算经验仅限于Netscape和PowerPoint的人来说，这可能会令人望而生畏。另一方面，计算机科学家必须进入生物物质和实验不确定性的模糊而复杂的世界，对于习惯于用严格逻辑解决定义明确的问题的人来说，这可能是一个可怕的环境。我们两位崭露头角的生物信息学家都必须学习构成当前实践基础的计算技术，包括BLAST和其他比对算法、基因识别技术和蛋白质表达谱跟踪技术-从神秘的(隐马尔可夫模型)到步行者(用Perl脚本重新格式化文件！)。无论目标是培养独立的研究科学家还是工业团队中的高效参与者，基础教育应该大致相同，就像我们在同一学科比较MS和博士科学家时通常所做的那样。不同之处在于书本学习之后的实践经验的性质。对于博士来说，重点是创新和创造性思维，而对MS级科学家的期望是高度胜任应用知识库，并能够保持该知识库的最新。对于那些对独立研究感兴趣的人来说，显而易见的道路是一个提供博士学位的系，而他们的期望应该是一个相对注重计算、较少关注生物学的课程。
CAREERS nature biotechnology• VOLUME 19• MARCH 2001• http://biotech. nature. com 286 rithms and how to implement them in C/C++, Java, and PERL, and gain experience in constructing big databases. This can be intimidating for someone whose computing experience has been limited to Netscape and PowerPoint. On the other hand, the computer scientist must enter the squishy and complex world of living matter and experimental uncertainty, perhaps a frightening neighborhood for someone accustomed to tackling well-defined problems with rigorous logic. Both of our budding bioinformaticists must learn the computing techniques that form the foundation of current practice, including BLAST and other alignment algorithms, techniques for gene identification, and tracking profiles of protein expression—everything from the arcane (hidden Markov models) to the pedestrian (reformat that file with a PERL script!).Whether the goal is to produce an independent research scientist or an efficient player in an industrial team, the fundamental education should be much the same, as it usually is when we compare MS and PhD scientists in the same discipline. The difference lies in the nature of the practical experience that follows the book learning. For a PhD, the emphasis is on innovation and creative thinking, whereas the expectation for the MS-level scientist is to be highly competent in applying a base of knowledge, and to be able to keep that base of knowledge current. For those interested in a career in independent research, the obvious road is a department that offers a PhD, and the expectation should be for a curriculum that is relatively heavy on computation and light on biology.