Structure-based predictive models for allosteric hot spots.
In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data s...
Main Authors: | Omar N A Demerdash, Michael D Daily, Julie C Mitchell |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2009-10-01
|
Series: | PLoS Computational Biology |
Online Access: | http://europepmc.org/articles/PMC2748687?pdf=render |
Similar Items
-
Hot Spot Data Prediction Model Based on Wavelet Neural Network
by: Ming Zhang, et al.
Published: (2018-01-01) -
Rigorous assessment and integration of the sequence and structure based features to predict hot spots
by: Wang Yong, et al.
Published: (2011-07-01) -
Allosteric communication occurs via networks of tertiary and quaternary motions in proteins.
by: Michael D Daily, et al.
Published: (2009-02-01) -
Prediction of binding hot spot residues by using structural and evolutionary parameters
by: Roberto Hiroshi Higa, et al.
Published: (2009-01-01) -
Extraction of Accidents Prediction Maps Modeling Hot Spots in Geospatial Information System
by: R. Shad, et al.
Published: (2013-10-01)