Progress in bioinformatics and the importance of being earnest.

T K Attwood, C J Miller
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引用次数: 13

Abstract

In silico biology has gathered momentum as, worldwide, scientists have united in a common quest to sequence, store and analyse complete genomes. This year, a pivotal achievement of this cooperative endeavour was realised in the release of a public draft of the human genome, and with it the promises to improve our understanding of diverse aspects of biology and to yield a healthier future with safe personalized medicines. Key to these goals will be the need to elucidate and characterise the genes and gene products encoded not just in the human genome, but in many genomes. These tasks are underpinned by the concepts and processes of genome and gene/protein evolution, regulation of gene expression, mechanisms of protein folding, the manifestation of protein function, and so on, all of which must be understood in the context of complex, dynamic biological systems. Our use of computers to model such concepts and systems must be placed in the context of the current limits of our understanding of them:- it is important to recognise, for example, that we don't have a common understanding either of what constitutes a gene or a protein function; we can't invariably say that a particular sequence or fold has arisen via divergent or convergent evolution; and we don't fully understand the rules of protein folding. Accepting what we can't do in silico is essential in appreciating what we can do. Without this understanding, it is easy to be misled, as notions of what particular computational approaches can achieve are sometimes rather optimistic. There are valuable lessons to be learned here from the field of Artificial Intelligence, principal among which is the realisation that capturing and representing complex knowledge is time consuming, expensive and hard. Thus, we argue here that if bioinformatics is to tackle biological complexity in earnest, it would be wise to absorb the experience distilled from decades of artificial intelligence research, and to approach the road ahead with caution, rigour and pragmatism.

生物信息学的进展和认真的重要性。
随着世界各地的科学家们为了对完整基因组进行测序、存储和分析的共同追求而团结起来,硅生物学的发展势头正在增强。今年,这一合作努力的一项关键成就是公布了一份人类基因组的公开草案,并有望提高我们对生物学各个方面的理解,并通过安全的个性化药物创造更健康的未来。实现这些目标的关键将是需要阐明和描述不仅在人类基因组中,而且在许多基因组中编码的基因和基因产物。这些任务的基础是基因组和基因/蛋白质进化的概念和过程,基因表达的调控,蛋白质折叠的机制,蛋白质功能的表现,等等,所有这些都必须在复杂的背景下理解,动态的生物系统。我们使用计算机来模拟这些概念和系统,必须放在我们目前对它们的理解有限的背景下:-重要的是要认识到,例如,我们对基因或蛋白质功能的构成都没有共同的理解;我们不能总是说一个特定的序列或褶皱是通过发散或趋同进化产生的;我们还没有完全理解蛋白质折叠的规则。接受我们在电脑上不能做的事情,是欣赏我们能做的事情的关键。如果没有这种理解,就很容易被误导,因为特定计算方法可以实现的概念有时相当乐观。我们可以从人工智能领域吸取宝贵的经验教训,其中最主要的是认识到捕获和表示复杂的知识是耗时、昂贵和困难的。因此,我们在此认为,如果生物信息学要认真解决生物复杂性问题,那么吸取几十年来人工智能研究的经验,谨慎、严谨和务实地走在前面的道路上,将是明智的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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