Document Detail


Machine learning methods for prediction of CDK-inhibitors.
MedLine Citation:
PMID:  20967128     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Progression through the cell cycle involves the coordinated activities of a suite of cyclin/cyclin-dependent kinase (CDK) complexes. The activities of the complexes are regulated by CDK inhibitors (CDKIs). Apart from its role as cell cycle regulators, CDKIs are involved in apoptosis, transcriptional regulation, cell fate determination, cell migration and cytoskeletal dynamics. As the complexes perform crucial and diverse functions, these are important drug targets for tumour and stem cell therapeutic interventions. However, CDKIs are represented by proteins with considerable sequence heterogeneity and may fail to be identified by simple similarity search methods. In this work we have evaluated and developed machine learning methods for identification of CDKIs. We used different compositional features and evolutionary information in the form of PSSMs, from CDKIs and non-CDKIs for generating SVM and ANN classifiers. In the first stage, both the ANN and SVM models were evaluated using Leave-One-Out Cross-Validation and in the second stage these were tested on independent data sets. The PSSM-based SVM model emerged as the best classifier in both the stages and is publicly available through a user-friendly web interface at http://bioinfo.icgeb.res.in/cdkipred.
Authors:
Jayashree Ramana; Dinesh Gupta
Related Documents :
20725088 - Primate-specific rfpl1 gene controls cell-cycle progression through cyclin b1/cdc2 degr...
9276628 - Inhibition of cdk2 kinase activity by methylselenocysteine in synchronized mouse mammar...
12059028 - Effects of nfkappab decoy oligonucleotides released from biodegradable polymer micropar...
9154838 - A ubiquitin-conjugating enzyme in fission yeast that is essential for the onset of anap...
9162268 - Ultrastructure of interactions between activated murine natural killer cells and melano...
23524488 - Emerging roles for chromatin as a signal integration and storage platform.
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't; Validation Studies     Date:  2010-10-13
Journal Detail:
Title:  PloS one     Volume:  5     ISSN:  1932-6203     ISO Abbreviation:  PLoS ONE     Publication Date:  2010  
Date Detail:
Created Date:  2010-10-22     Completed Date:  2011-03-07     Revised Date:  2013-07-03    
Medline Journal Info:
Nlm Unique ID:  101285081     Medline TA:  PLoS One     Country:  United States    
Other Details:
Languages:  eng     Pagination:  e13357     Citation Subset:  IM    
Affiliation:
Structural and Computational Biology Group, International Centre for Genetic Engineering and Biotechnology, New Delhi, India.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:
Artificial Intelligence*
Cyclin-Dependent Kinases / antagonists & inhibitors*
Internet
Protein Kinase Inhibitors / pharmacology*
ROC Curve
Chemical
Reg. No./Substance:
0/Protein Kinase Inhibitors; EC 2.7.11.22/Cyclin-Dependent Kinases
Comments/Corrections

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  Progranulin is neurotrophic in vivo and protects against a mutant TDP-43 induced axonopathy.
Next Document:  Platelet serotonin level predicts survival in amyotrophic lateral sclerosis.