Text mining improves prediction of protein functional sites.
We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts f...
Main Authors: | Karin M Verspoor, Judith D Cohn, Komandur E Ravikumar, Michael E Wall |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2012-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC3290545?pdf=render |
Similar Items
-
Literature mining of protein-residue associations with graph rules learned through distant supervision
by: Ravikumar KE, et al.
Published: (2012-10-01) -
Integrating protein-protein interactions and text mining for protein function prediction
by: Leser Ulf, et al.
Published: (2008-07-01) -
Genome majority vote improves gene predictions.
by: Michael E Wall, et al.
Published: (2011-11-01) -
Text Mining for Protein Docking.
by: Varsha D Badal, et al.
Published: (2015-12-01) -
Evolution of Protein Functional Annotation: Text Mining Study
by: Ekaterina V. Ilgisonis, et al.
Published: (2022-03-01)