Pushing the annotation of cellular activities to a higher resolution: Predicting functions at the isoform level
Wenyuan Li1, Chun-Chi Liu2, Shuli Kang1
1Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA.
Abstract:
In past decades, the experimental determination of protein functions was expensive and time-consuming, so numerous computational methods were developed to speed up and guide the process. However, most of these methods predict protein functions at the gene level and do not consider the fact that protein isoforms (translated from alternatively spliced transcripts), not genes, are the actual function carriers. Now, high-throughput RNA-seq technology is providing unprecedented opportunities to unravel protein functions at the isoform level. In this article, we review recent progress in the high-resolution functional annotations of protein isoforms, focusing on two methods developed by the authors. Both methods can integrate multiple RNA-seq datasets for comprehensively characterizing functions of protein isoforms.
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