How accurate and statistically robust are catalytic site predictions based on closeness centrality?
about
L1pred: a sequence-based prediction tool for catalytic residues in enzymes with the L1-logreg classifierA network pharmacology approach to understanding the mechanisms of action of traditional medicine: Bushenhuoxue formula for treatment of chronic kidney diseaseAllosteric regulation of the Hsp90 dynamics and stability by client recruiter cochaperones: protein structure network modelingSmall world network strategies for studying protein structures and binding.From sequence to enzyme mechanism using multi-label machine learning.Novel feature for catalytic protein residues reflecting interactions with other residuesExploiting a reduced set of weighted average features to improve prediction of DNA-binding residues from 3D structures.Identification of catalytic residues using a novel feature that integrates the microenvironment and geometrical location properties of residues.Accurate prediction of protein catalytic residues by side chain orientation and residue contact density.Automatic prediction of catalytic residues by modeling residue structural neighborhood.Computational prediction of heme-binding residues by exploiting residue interaction networkComputational modeling of allosteric communication reveals organizing principles of mutation-induced signaling in ABL and EGFR kinases.Fast dynamics perturbation analysis for prediction of protein functional sites.SitesIdentify: a protein functional site prediction tool.Predicting protein-ATP binding sites from primary sequence through fusing bi-profile sampling of multi-view features.An integrative computational framework based on a two-step random forest algorithm improves prediction of zinc-binding sites in proteinsRsite2: an efficient computational method to predict the functional sites of noncoding RNAs.CRHunter: integrating multifaceted information to predict catalytic residues in enzymes.Frameworks for understanding long-range intra-protein communication.Cutoff lensing: predicting catalytic sites in enzymes.Graph analysis of β2 adrenergic receptor structures: a "social network" of GPCR residues.Revealing unique properties of the ribosome using a network based analysis.Structural signatures of antibiotic binding sites on the ribosome.Sequence-based enzyme catalytic domain prediction using clustering and aggregated mutual information content.CSmetaPred: a consensus method for prediction of catalytic residues.Accurate sequence-based prediction of catalytic residues.iCataly-PseAAC: Identification of Enzymes Catalytic Sites Using Sequence Evolution Information with Grey Model GM (2,1).A geometry-based generic predictor for catalytic and allosteric sites.
P2860
Q28482793-541A811E-C6AD-41D0-8499-22B3795CA1BBQ28540443-7D82CDA4-CECA-437A-B9A0-C7EA748C2309Q30358343-12E1FF14-8910-4635-8064-8920DE283D13Q30360856-0593EBC2-7000-4B23-A740-2CFAD1745461Q30363113-E0028BED-48D9-49D3-B79C-E943789986DBQ30401557-E8C294F5-8392-4B61-97F5-028730B73478Q30410742-386EE0C8-7143-4B6D-A90E-832A3DE9D891Q30419616-2E9070CD-DA98-44A7-AC48-5873E78DB856Q30422966-9817AD7C-DCE7-4246-BBE5-9E78036962B7Q30978779-05182C9C-3DB6-4F0C-AF10-E2AFA3B092E7Q31032381-56817BF1-A2DB-42DE-A485-DCC775C4704EQ31036423-E4CE4EEA-6FCB-4611-BB2D-0EDA557F0E4CQ33317416-83F3A075-5964-4D41-ADE1-3AEE43CE7011Q33516170-E09D3101-F5E0-4C59-9712-1AE8B91C5C26Q34204567-E20B8482-3AA4-4140-87C1-5FA72037BA22Q34482705-030DDABE-390E-4C27-A4EA-193D69B7F789Q36448795-710F41D9-1F3D-400A-93F9-6806363C7417Q37282016-5C848717-FF31-4845-8F86-E78D763D836DQ37438472-58F221DB-8AF2-4A8C-AE03-2A18423C7B51Q41140874-176A93E5-7E10-473C-8741-224C9369098DQ41692346-AFF1FBD8-BCEC-4AF8-92E8-3862645AB17CQ41727629-7F1CABB4-6CEA-4657-85DF-BE1C9BB0C324Q41897563-3C46866D-F5BE-474D-A848-671A743F75E2Q42619050-9FEC944F-89B7-4B7B-8E71-96BDFF8987D0Q47121849-E55BFE28-4467-46FE-BE12-F587397D4AE7Q48325580-30A56F2F-C542-463C-90A2-CD54312585FFQ50898596-AB58DA24-5CD5-473B-A1BD-DFC5EDC71F21Q53077981-AD4AC487-D18F-4093-B56D-0C2BDD996F88
P2860
How accurate and statistically robust are catalytic site predictions based on closeness centrality?
description
2007 nî lūn-bûn
@nan
2007 թուականի Մայիսին հրատարակուած գիտական յօդուած
@hyw
2007 թվականի մայիսին հրատարակված գիտական հոդված
@hy
2007年の論文
@ja
2007年論文
@yue
2007年論文
@zh-hant
2007年論文
@zh-hk
2007年論文
@zh-mo
2007年論文
@zh-tw
2007年论文
@wuu
name
How accurate and statistically ...... based on closeness centrality?
@ast
How accurate and statistically ...... based on closeness centrality?
@en
type
label
How accurate and statistically ...... based on closeness centrality?
@ast
How accurate and statistically ...... based on closeness centrality?
@en
prefLabel
How accurate and statistically ...... based on closeness centrality?
@ast
How accurate and statistically ...... based on closeness centrality?
@en
P2860
P356
P1433
P1476
How accurate and statistically ...... based on closeness centrality?
@en
P2093
Dennis R Livesay
P2860
P2888
P356
10.1186/1471-2105-8-153
P577
2007-05-11T00:00:00Z
P5875
P6179
1001899258