Sequence-based prediction of protein crystallization, purification and production propensity.
about
Disorder Prediction Methods, Their Applicability to Different Protein Targets and Their Usefulness for Guiding Experimental StudiesStatistical analysis of crystallization database links protein physico-chemical features with crystallization mechanismsPSIONplus: Accurate Sequence-Based Predictor of Ion Channels and Their TypesBEST: improved prediction of B-cell epitopes from antigen sequencesThe "Sticky Patch" Model of Crystallization and Modification of Proteins for Enhanced Crystallizability.Improving the chances of successful protein structure determination with a random forest classifierCrysalis: an integrated server for computational analysis and design of protein crystallization.Covering complete proteomes with X-ray structures: a current snapshot.Prediction of bioluminescent proteins by using sequence-derived features and lineage-specific scheme.Knowledge-transfer learning for prediction of matrix metalloprotease substrate-cleavage sitesStructural genomics plucks high-hanging membrane proteins.Genome-scale prediction of proteins with long intrinsically disordered regions.An integrative computational framework based on a two-step random forest algorithm improves prediction of zinc-binding sites in proteinsSCMCRYS: predicting protein crystallization using an ensemble scoring card method with estimating propensity scores of P-collocated amino acid pairs.PredPPCrys: accurate prediction of sequence cloning, protein production, purification and crystallization propensity from protein sequences using multi-step heterogeneous feature fusion and selection.Computational crystallization.TSTMP: target selection for structural genomics of human transmembrane proteins.Computational approaches to selecting and optimising targets for structural biology.How disordered is my protein and what is its disorder for? A guide through the "dark side" of the protein universe.Critical evaluation of bioinformatics tools for the prediction of protein crystallization propensity.DRNApred, fast sequence-based method that accurately predicts and discriminates DNA- and RNA-binding residues.TargetCrys: protein crystallization prediction by fusing multi-view features with two-layered SVM.Learning protein multi-view features in complex space.fDETECT webserver: fast predictor of propensity for protein production, purification, and crystallization.Target selection for structural genomics based on combining fold recognition and crystallisation prediction methods: application to the human proteome.Improved prediction of residue flexibility by embedding optimized amino acid grouping into RSA-based linear models.Structural insights and characterization of human Npas4 protein.Functional and structural characterization of osteocytic MLO-Y4 cell proteins encoded by genes differentially expressed in response to mechanical signals in vitro.
P2860
Q26796658-B7950C35-7EBC-4E41-AF66-DDDA202DA879Q28540267-9C3D5F67-3221-4073-8973-596852FF2068Q28551152-98711BC3-E854-4709-A2C5-CBA9D8B256DEQ28727926-5A49A695-8D03-42C5-9FC9-36FFD085EE68Q30252224-B534E51A-A864-4293-B343-0913EDA9F44EQ30359799-46C2ED30-DFEF-469E-8CDC-085954FB0740Q30384803-B7EDECDD-20AE-4D69-9275-FF83741793A2Q30596920-C6EDA0CB-0989-4578-AAEB-749754BEA317Q33767868-6735655B-D5FD-47B6-884F-E1F759358146Q33915991-22A3AE1D-0FEC-4728-80B1-36D7E2F6DFBDQ34276839-C3E26A6E-70FA-4ABD-9393-78BFD8E869F1Q34353364-35961B52-29E0-467D-80B1-8B08AC5C1195Q34482705-2270C560-0ECD-4FFF-842A-796EF38150CEQ34982681-3F44ED76-51EC-444F-8F49-E849504EFE77Q35229942-6DC3626D-22C2-436F-951F-7EB3B22DD610Q37008791-CC77548F-B780-4CC5-939A-AE31938982A8Q37557027-F579A80B-6EE3-43E1-8F5F-EC9DEF54D401Q38332028-BA33EC89-BDD3-42DC-8951-857D0A0FF6A3Q38944980-E7427056-2FB8-4A3C-A6EA-7D7D374806EDQ39196103-2F771A6F-D40D-4F8A-BEED-D625FF6C0D1CQ42237296-51608E4C-BB74-4B4F-BE28-F001294A0C84Q45949782-32B57B6B-BD29-473E-8C52-A5A8B1D71C0BQ45959560-C5038398-0F8F-48AD-BAFA-24756D748D1CQ47204147-844473A1-FB2B-4E20-8063-CE1C7DB84261Q51418712-22A9A192-C900-4786-AF2B-68B7B8BD65FDQ53477774-0A505AD2-379C-4557-AF52-311761B772C7Q55261718-F0D5794C-15EE-4CEA-A724-1C2FAE681EB4Q55311483-4479C339-F0ED-48B9-A813-7435C0B54FF8
P2860
Sequence-based prediction of protein crystallization, purification and production propensity.
description
2011 nî lūn-bûn
@nan
2011 թուականի Յուլիսին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի հուլիսին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
name
Sequence-based prediction of p ...... ion and production propensity.
@ast
Sequence-based prediction of p ...... ion and production propensity.
@en
type
label
Sequence-based prediction of p ...... ion and production propensity.
@ast
Sequence-based prediction of p ...... ion and production propensity.
@en
prefLabel
Sequence-based prediction of p ...... ion and production propensity.
@ast
Sequence-based prediction of p ...... ion and production propensity.
@en
P2860
P356
P1433
P1476
Sequence-based prediction of p ...... ion and production propensity.
@en
P2093
Marcin J Mizianty
P2860
P304
P356
10.1093/BIOINFORMATICS/BTR229
P407
P577
2011-07-01T00:00:00Z