Prediction of active sites of enzymes by maximum relevance minimum redundancy (mRMR) feature selection.
about
ADMET evaluation in drug discovery: 15. Accurate prediction of rat oral acute toxicity using relevance vector machine and consensus modelingPINGU: PredIction of eNzyme catalytic residues usinG seqUence informationAn ensemble prognostic model for colorectal cancer.Classification of non-small cell lung cancer based on copy number alterationsSequence-Based Prediction of RNA-Binding Proteins Using Random Forest with Minimum Redundancy Maximum Relevance Feature SelectionDNABP: Identification of DNA-Binding Proteins Based on Feature Selection Using a Random Forest and Predicting Binding Residues.Prediction and analysis of retinoblastoma related genes through gene ontology and KEGG.Prediction of aptamer-target interacting pairs with pseudo-amino acid composition.Ensemble Architecture for Prediction of Enzyme-ligand Binding Residues Using Evolutionary Information.Identifying subcellular localizations of mammalian protein complexes based on graph theory with a random forest algorithm.Exploring the potential of 3D Zernike descriptors and SVM for protein-protein interface prediction.iCataly-PseAAC: Identification of Enzymes Catalytic Sites Using Sequence Evolution Information with Grey Model GM (2,1).Predicting DNA-binding sites of proteins based on sequential and 3D structural information.
P2860
Q27902316-A2C422CB-2A80-46E7-A40A-4CE8E2ABE006Q28547146-9725D12F-2967-4355-AC16-A5EDDFF2D11BQ34713253-41EED229-4B47-4528-AE25-57B894A10CC4Q35088670-B4130DDF-FFBD-4594-A87C-1CC302AD2C99Q36205724-2502742E-4BA9-4C82-9C8A-3A6F09E1DB22Q36210279-9F3599F1-F7EC-49F1-8A90-DF59A5FA9854Q37127244-4F068E99-D3D1-46F8-9BDD-647745F42852Q41886193-BADEF96A-8BB1-451C-AA0A-E0A604BA67CEQ45947040-8ACFAA73-41B2-41D2-B182-24E958484FE1Q46929781-937ED9B0-0A6C-4E3D-ACA8-4A0120F7D11DQ48096578-6C7F8498-DA09-4F1A-9AA2-64FAF39EE381Q50898596-C19A00EB-5A6F-43EB-9874-F225BB0E062CQ51121458-EDE80F41-59A6-4A5C-91FD-B833D12E434C
P2860
Prediction of active sites of enzymes by maximum relevance minimum redundancy (mRMR) feature selection.
description
2012 nî lūn-bûn
@nan
2012年の論文
@ja
2012年学术文章
@wuu
2012年学术文章
@zh
2012年学术文章
@zh-cn
2012年学术文章
@zh-hans
2012年学术文章
@zh-my
2012年学术文章
@zh-sg
2012年學術文章
@yue
2012年學術文章
@zh-hant
name
Prediction of active sites of ...... ancy (mRMR) feature selection.
@en
Prediction of active sites of enzymes by maximum relevance minimum redundancy
@nl
type
label
Prediction of active sites of ...... ancy (mRMR) feature selection.
@en
Prediction of active sites of enzymes by maximum relevance minimum redundancy
@nl
prefLabel
Prediction of active sites of ...... ancy (mRMR) feature selection.
@en
Prediction of active sites of enzymes by maximum relevance minimum redundancy
@nl
P2093
P2860
P356
P1433
P1476
Prediction of active sites of ...... ancy (mRMR) feature selection.
@en
P2093
Bi-Qing Li
Kai-Yan Feng
Yang Jiang
Yu-Fei Gao
Zhan-Dong Li
P2860
P356
10.1039/C2MB25327E
P50
P577
2012-11-02T00:00:00Z