Protein fold recognition using sequence-derived predictions.
about
A novel human apolipoprotein (apoM)Enzymatic reduction of disulfide bonds in lysosomes: characterization of a gamma-interferon-inducible lysosomal thiol reductase (GILT)A novel immunoglobulin superfamily receptor (19A) related to CD2 is expressed on activated lymphocytes and promotes homotypic B-cell adhesionGlucocorticoid-induced leucine zipper inhibits the Raf-extracellular signal-regulated kinase pathway by binding to Raf-1All are not equal: a benchmark of different homology modeling programsCoarse-grained modeling of large RNA molecules with knowledge-based potentials and structural filtersPredicting continuous local structure and the effect of its substitution for secondary structure in fragment-free protein structure predictionStructural requirements of six naturally occurring isoforms of the IL-18 binding protein to inhibit IL-18Homology modeling using parametric alignment ensemble generation with consensus and energy-based model selectionIntegrated web service for improving alignment quality based on segments comparisonA study of quality measures for protein threading modelsStructure of the active core of human stem cell factor and analysis of binding to its receptor KitCrystal structure of the eosinophil major basic protein at 1.8 A. An atypical lectin with a paradigm shift in specificityProposed lipocalin fold for apolipoprotein M based on bioinformatics and site-directed mutagenesisCloning and characterization of IL-1HY2, a novel interleukin-1 family memberHomology modelling and structural analysis of human arylamine N-acetyltransferase NAT1: evidence for the conservation of a cysteine protease catalytic domain and an active-site loopOligomerization properties of ERp29, an endoplasmic reticulum stress proteinApplication of multiple sequence alignment profiles to improve protein secondary structure predictionA structural model for the rolA protein and its interaction with DNA.Protein structure alignment using environmental profiles.Pcons: a neural-network-based consensus predictor that improves fold recognition.Sequence-structure homology recognition by iterative alignment refinement and comparative modeling.The directional atomic solvation energy: an atom-based potential for the assignment of protein sequences to known folds.DSSPcont: Continuous secondary structure assignments for proteins.CooPPS: a system for the cooperative prediction of protein structures.Protein structure prediction by pro-Sp3-TASSER.Sixty-five years of the long march in protein secondary structure prediction: the final stretch?Template-based protein structure modeling using TASSER(VMT.).A proposed architecture for the central domain of the bacterial enhancer-binding proteins based on secondary structure prediction and fold recognition.The protease inhibitor chagasin of Trypanosoma cruzi adopts an immunoglobulin-type fold and may have arisen by horizontal gene transfer.Combining multiple structure and sequence alignments to improve sequence detection and alignment: application to the SH2 domains of Janus kinases.Motif-based fold assignmentEstimating the probability for a protein to have a new fold: A statistical computational model.Application of data mining tools for classification of protein structural class from residue based averaged NMR chemical shiftsThe inositol polyphosphate 5-phosphatases and the apurinic/apyrimidinic base excision repair endonucleases share a common mechanism for catalysis.Mutational analysis of protein substrate presentation in the post-translational attachment of biotin to biotin domains.Fold recognition and accurate query-template alignment by a combination of PSI-BLAST and threading.An optimal structure-discriminative amino acid index for protein fold recognitionFold recognition by combining sequence profiles derived from evolution and from depth-dependent structural alignment of fragments.Amino acids 257 to 288 of mouse p48 control the cooperation of polyomavirus large T antigen, replication protein A, and DNA polymerase alpha-primase to synthesize DNA in vitro.
P2860
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P2860
Protein fold recognition using sequence-derived predictions.
description
1996 nî lūn-bûn
@nan
1996年の論文
@ja
1996年学术文章
@wuu
1996年学术文章
@zh-cn
1996年学术文章
@zh-hans
1996年学术文章
@zh-my
1996年学术文章
@zh-sg
1996年學術文章
@yue
1996年學術文章
@zh
1996年學術文章
@zh-hant
name
Protein fold recognition using sequence-derived predictions.
@ast
Protein fold recognition using sequence-derived predictions.
@en
type
label
Protein fold recognition using sequence-derived predictions.
@ast
Protein fold recognition using sequence-derived predictions.
@en
prefLabel
Protein fold recognition using sequence-derived predictions.
@ast
Protein fold recognition using sequence-derived predictions.
@en
P2860
P356
P1433
P1476
Protein fold recognition using sequence-derived predictions.
@en
P2093
Eisenberg D
P2860
P304
P356
10.1002/PRO.5560050516
P577
1996-05-01T00:00:00Z