The rational design of amino acid sequences by artificial neural networks and simulated molecular evolution: de novo design of an idealized leader peptidase cleavage site.
about
Discovery of substrate for type I signal peptidase SpsB from Staphylococcus aureus.Peptide design by artificial neural networks and computer-based evolutionary search.Efficacy of different protein descriptors in predicting protein functional families.Application of neural networks in structure-activity relationships.Peptide design in machina: development of artificial mitochondrial protein precursor cleavage sites by simulated molecular evolution.Classification of lung cancer tumors based on structural and physicochemical properties of proteins by bioinformatics models.Exploration of sequence space for protein engineering.PROFEAT: a web server for computing structural and physicochemical features of proteins and peptides from amino acid sequence.Update of PROFEAT: a web server for computing structural and physicochemical features of proteins and peptides from amino acid sequenceSPiCE: a web-based tool for sequence-based protein classification and explorationImproved peptide elution time prediction for reversed-phase liquid chromatography-MS by incorporating peptide sequence information.Attractors in Sequence Space: Peptide Morphing by Directed Simulated EvolutionRF-Phos: A Novel General Phosphorylation Site Prediction Tool Based on Random Forest.Prediction of functional class of proteins and peptides irrespective of sequence homology by support vector machines.Optimisation of signal peptide for recombinant protein secretion in bacterial hosts.Sparse Neural Network Models of Antimicrobial Peptide-Activity Relationships.The inverse protein folding question and simulated molecular evolution.Support vector machines for predicting membrane protein types by using functional domain composition.A neural network model for the prediction of membrane-spanning amino acid sequences."Simulated molecular evolution" or computer-generated artifacts?Prediction of lung tumor types based on protein attributes by machine learning algorithms.Computational study on the origin of the cancer immunotherapeutic potential of B and T cell epitope peptides.Bastion6: a bioinformatics approach for accurate prediction of type VI secreted effectors.Organization of the DMSO respiratory operon of Rhodobacter capsulatus and its consequences for homologous expression of DMSOR/TMAOR.
P2860
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P2860
The rational design of amino acid sequences by artificial neural networks and simulated molecular evolution: de novo design of an idealized leader peptidase cleavage site.
description
1994 nî lūn-bûn
@nan
1994年の論文
@ja
1994年学术文章
@wuu
1994年学术文章
@zh-cn
1994年学术文章
@zh-hans
1994年学术文章
@zh-my
1994年学术文章
@zh-sg
1994年學術文章
@yue
1994年學術文章
@zh
1994年學術文章
@zh-hant
name
The rational design of amino a ...... eader peptidase cleavage site.
@en
The rational design of amino a ...... eader peptidase cleavage site.
@nl
type
label
The rational design of amino a ...... eader peptidase cleavage site.
@en
The rational design of amino a ...... eader peptidase cleavage site.
@nl
prefLabel
The rational design of amino a ...... eader peptidase cleavage site.
@en
The rational design of amino a ...... eader peptidase cleavage site.
@nl
P2860
P1433
P1476
The rational design of amino a ...... eader peptidase cleavage site.
@en
P2093
P2860
P304
P356
10.1016/S0006-3495(94)80782-9
P407
P433
P577
1994-02-01T00:00:00Z