分子生物学中适用于计算方法的重大挑战概述。

R M Glaeser
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引用次数: 0

摘要

现代细胞和分子生物学理论方法的发展存在许多具有挑战性但重要的机会。包含大量信息的数据库的创建已被证明是一个意想不到的重要因素,它使建立在数据库本身之上的理论工作获得接受和尊重,例如涉及已知蛋白质结构分析的理论工作,或开发更强大的同源性搜索。其他尚未被广泛接受的机会包括研究复杂的网络(代谢、遗传、免疫和神经网络),以及研究“事物如何运作的物理学”。美国能源部国家实验室系统代表了一个理想的机构,它将非常适合作为现代生物学理论和计算学科创建的“孵化器”。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Overview of significant challenges in molecular biology amenable to computational methods.

Many challenging but significant opportunities exist for the development of theoretical approaches in modern Cell and Molecular Biology. The creation of data bases which contain extremely large amounts of information has proven to be an unexpectedly important facto-tin gaining acceptance and respectability for theoretical work that builds on nothing more than what is in the data base itself, such as theoretical work involving the analysis of known protein structures, or the development of more powerful homology searches. Other opportunities, not yet accepted by a broad community, involve work on complex networks (metabolic, genetic, immunologic and neural networks) and work on the "physics of how things work." The DOE National Laboratory System represents the ideal institution that would be well suited to the role of being an "incubator" for the creation of a theoretical and computational discipline within modern biology.

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