Machine learning for discovering missing or wrong protein function annotations
Abstract Background A massive amount of proteomic data is generated on a daily basis, nonetheless annotating all sequences is costly and often unfeasible. As a countermeasure, machine learning methods have been used to automatically annotate new protein functions. More specifically, many studies hav...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2019-09-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12859-019-3060-6 |