A machine learning strategy to identify candidate binding sites in human protein-coding sequence
about
Resolving the structural features of genomic islands: a machine learning approachA search for conserved sequences in coding regions reveals that the let-7 microRNA targets Dicer within its coding sequenceExploiting residue-level and profile-level interface propensities for usage in binding sites prediction of proteins.Genomic mid-range inhomogeneity correlates with an abundance of RNA secondary structuresThe Alternative Splicing Mutation Database: a hub for investigations of alternative splicing using mutational evidenceCalculation of splicing potential from the Alternative Splicing Mutation DatabaseAutomatic detection of exonic splicing enhancers (ESEs) using SVMsCodingMotif: exact determination of overrepresented nucleotide motifs in coding sequencesCOMIT: identification of noncoding motifs under selection in coding sequences.Locating protein-coding sequences under selection for additional, overlapping functions in 29 mammalian genomes.
P2860
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P2860
A machine learning strategy to identify candidate binding sites in human protein-coding sequence
description
2006 nî lūn-bûn
@nan
2006 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած
@hyw
2006 թվականի սեպտեմբերին հրատարակված գիտական հոդված
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2006年の論文
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2006年論文
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2006年論文
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2006年論文
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2006年論文
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2006年論文
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2006年论文
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name
A machine learning strategy to ...... human protein-coding sequence
@ast
A machine learning strategy to ...... human protein-coding sequence
@en
type
label
A machine learning strategy to ...... human protein-coding sequence
@ast
A machine learning strategy to ...... human protein-coding sequence
@en
prefLabel
A machine learning strategy to ...... human protein-coding sequence
@ast
A machine learning strategy to ...... human protein-coding sequence
@en
P2860
P356
P1433
P1476
A machine learning strategy to ...... human protein-coding sequence
@en
P2093
Bernard Leong
Thomas Down
P2860
P2888
P356
10.1186/1471-2105-7-419
P50
P577
2006-09-26T00:00:00Z
P5875
P6179
1026359512