统计机器学习和计算生物学

Michael I. Jordan
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引用次数: 0

摘要

统计机器学习是一个将算法思想与概率论和统计学的基本概念相结合的领域。这种结合使得统计机器学习成为计算生物学的重要工具,部分原因是概率概念是生物学中固有的(例如,通过热力学、重组和种系突变产生),部分原因是大多数生物学数据集的不完整性。我将在蛋白质功能注释、蛋白质结构建模、蛋白质结构预测以及多种群连锁和关联分析等领域介绍统计机器学习应用于生物学问题的几个例子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Statistical Machine Learning and Computational Biology
Statistical machine learning is a field that combines algorithmic ideas with foundational concepts from probability and statistics. This combination makes statistical machine learning an essential tool for computational biology, in part because probabilistic notions are inherent in biology (arising, e.g., via thermodynamics, recombination and germline mutation) and in part because of the incomplete nature of most biological data sets. I will present several examples of applications of statistical machine learning to problems in biology, in the areas of protein functional annotation, protein structural modeling, protein structure prediction and multipopulation linkage and association analysis.
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