作者
Christof Angermueller, Tanel Pärnamaa, Leopold Parts, Oliver Stegle
发表日期
2016/7
来源
Molecular systems biology
卷号
12
期号
7
页码范围
878
简介
Technological advances in genomics and imaging have led to an explosion of molecular and cellular profiling data from large numbers of samples. This rapid increase in biological data dimension and acquisition rate is challenging conventional analysis strategies. Modern machine learning methods, such as deep learning, promise to leverage very large data sets for finding hidden structure within them, and for making accurate predictions. In this review, we discuss applications of this new breed of analysis approaches in regulatory genomics and cellular imaging. We provide background of what deep learning is, and the settings in which it can be successfully applied to derive biological insights. In addition to presenting specific applications and providing tips for practical use, we also highlight possible pitfalls and limitations to guide computational biologists when and how to make the most use of this new …
引用总数
201620172018201920202021202220232024148718727626422919419073
学术搜索中的文章
C Angermueller, T Pärnamaa, L Parts, O Stegle - Molecular systems biology, 2016