Uberbacher E
Computer Science and Mathematics Division, Oak Ridge National Laboratory, TN 37831-6364, USA.
Trends Biotechnol. 1995 Dec;13(12):497-500. doi: 10.1016/S0167-7799(00)89011-3.
The Third International Conference on Intelligent Systems in Molecular Biology was truly an outstanding event. Computational methods in molecular biology have reached a new level of maturity and utility, resulting in many high-impact applications. The success of this meeting bodes well for the rapid and continuing development of computational methods, intelligent systems and information-based approaches for the biosciences. The basic technology, originally most often applied to 'feasibility' problems, is now dealing effectively with the most difficult real-world problems. Significant progress has been made in understanding protein-structure information, structural classification, and how functional information and the relevant features of active-site geometry can be gleaned from structures by automated computational approaches. The value and limits of homology-based methods, and the ability to classify proteins by structure in the absence of homology, have reached a new level of sophistication. New methods for covariation analysis in the folding of large structures such as RNAs have shown remarkably good results, indicating the long-term potential to understand very complicated molecules and multimolecular complexes using computational means. Novel methods, such as HMMs, context-free grammars and the uses of mutual information theory, have taken center stage as highly valuable tools in our quest to represent and characterize biological information. A focus on creative uses of intelligent systems technologies and the trend toward biological application will undoubtedly continue and grow at the 1996 ISMB meeting in St Louis.
第三届国际分子生物学智能系统会议确实是一次卓越的盛会。分子生物学中的计算方法已达到了新的成熟度和实用性水平,催生了许多具有重大影响力的应用。此次会议的成功预示着计算方法、智能系统以及生物科学领域基于信息的方法将快速且持续地发展。最初大多应用于“可行性”问题的基础技术,如今正有效地应对最具挑战性的现实世界问题。在理解蛋白质结构信息、结构分类以及如何通过自动化计算方法从结构中获取功能信息和活性位点几何形状的相关特征方面,已经取得了显著进展。基于同源性方法的价值和局限性,以及在缺乏同源性的情况下按结构对蛋白质进行分类的能力,已达到了新的精细程度。用于诸如RNA等大型结构折叠中共变分析的新方法已显示出非常好的结果,表明利用计算手段理解非常复杂的分子和多分子复合物具有长期潜力。诸如隐马尔可夫模型、上下文无关文法以及互信息理论的应用等新方法,已成为我们在表示和刻画生物信息过程中极具价值的核心工具。在1996年于圣路易斯举行的智能系统分子生物学会议(ISMB)上,对智能系统技术创造性应用的关注以及生物应用的趋势无疑将持续并发展。