CRNPRED: highly accurate prediction of one-dimensional protein structures by large-scale critical random networks.
about
Highly accurate sequence-based prediction of half-sphere exposures of amino acid residues in proteinsUniRef: comprehensive and non-redundant UniProt reference clustersSABERTOOTH: protein structural alignment based on a vectorial structure representation.Protein contact order prediction from primary sequences.Capturing Non-Local Interactions by Long Short Term Memory Bidirectional Recurrent Neural Networks for Improving Prediction of Protein Secondary Structure, Backbone Angles, Contact Numbers, and Solvent Accessibility.Protein Data Bank Japan (PDBj): updated user interfaces, resource description framework, analysis tools for large structuresNature of protein family signatures: insights from singular value analysis of position-specific scoring matrices.Protein Data Bank Japan (PDBj): maintaining a structural data archive and resource description framework format.svmPRAT: SVM-based protein residue annotation toolkit.High quality protein sequence alignment by combining structural profile prediction and profile alignment using SABER-TOOTH.Specific non-local interactions are not necessary for recovering native protein dynamics.Comprehensive study of liposome-assisted synthesis of membrane proteins using a reconstituted cell-free translation system.Stochastic reconstruction of protein structures from effective connectivity profiles.Guiding probabilistic search of the protein conformational space with structural profiles.Prediction of One-Dimensional Structural Properties Of Proteins by Integrated Neural Networks
P2860
Q28269843-BDBC2EA8-BA1A-46EA-B346-4AD085CB8BC1Q29614376-6F7E2BFA-279E-413F-A42D-147B0E880FE1Q30365518-268DFA9A-7F1C-4D22-83D4-3CC085552B18Q30369682-9BD997A1-E088-412C-B5C4-2E7496F9B7BAQ30401256-BD445F9A-4D25-465F-833D-5AB4B4A53D05Q31139556-A0FDE7C3-C80D-4FEE-A653-717091B457CFQ33327375-1BEDE5E3-A8C1-43C9-80FB-E269C940DBB5Q33454040-FC48A9FD-E0C0-43A6-97C7-4EC51CC952E2Q33520352-FA0C6B61-122C-4DED-B318-5151AFBC337BQ33578211-E6F87EF4-554E-4184-91BA-31B6067BF3E4Q35119927-3424B982-C840-4FE9-B24B-0659D87FBEA9Q36371029-207263CC-9855-4EC9-9FA2-8D1C84404752Q42061614-80CD5BF4-2104-4667-A22F-43E7669047DEQ51342587-1CF962A4-176B-4375-AE5E-B6A20F3E2E52Q58041627-D06B2ABD-A436-43B8-8636-45A66E7B447C
P2860
CRNPRED: highly accurate prediction of one-dimensional protein structures by large-scale critical random networks.
description
2006 nî lūn-bûn
@nan
2006 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած
@hyw
2006 թվականի սեպտեմբերին հրատարակված գիտական հոդված
@hy
2006年の論文
@ja
2006年論文
@yue
2006年論文
@zh-hant
2006年論文
@zh-hk
2006年論文
@zh-mo
2006年論文
@zh-tw
2006年论文
@wuu
name
CRNPRED: highly accurate predi ...... cale critical random networks.
@ast
CRNPRED: highly accurate predi ...... cale critical random networks.
@en
type
label
CRNPRED: highly accurate predi ...... cale critical random networks.
@ast
CRNPRED: highly accurate predi ...... cale critical random networks.
@en
prefLabel
CRNPRED: highly accurate predi ...... cale critical random networks.
@ast
CRNPRED: highly accurate predi ...... cale critical random networks.
@en
P2860
P356
P1433
P1476
CRNPRED: highly accurate predi ...... cale critical random networks.
@en
P2093
Akira R Kinjo
Ken Nishikawa
P2860
P2888
P356
10.1186/1471-2105-7-401
P577
2006-09-05T00:00:00Z
P5875
P6179
1003896840
P698
P818
q-bio/0604013