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.
| Original language | English |
|---|---|
| Pages (from-to) | 110-118 |
| Number of pages | 9 |
| Journal | Methods: A Companion to Methods in Enzymology |
| Volume | 93 |
| DOIs | |
| State | Published - 15 01 2016 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2015.
Keywords
- Isoform function prediction
- Multiple instance learning
- RNA-seq data
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