Functional census of mutation sequence spaces: the example of p53 cancer rescue mutants.
about
Computational identification of a transiently open L1/S3 pocket for reactivation of mutant p53Predicting transcriptional activity of multiple site p53 mutants based on hybrid propertiesHeterogeneous biomedical database integration using a hybrid strategy: a p53 cancer research database.Predicting positive p53 cancer rescue regions using Most Informative Positive (MIP) active learning.Structure-based predictions broadly link transcription factor mutations to gene expression changes in cancers.Prediction of P53 mutants (multiple sites) transcriptional activity based on structural (2D&3D) properties.Compensated pathogenic deviations.Choosing where to look next in a mutation sequence space: Active Learning of informative p53 cancer rescue mutants.Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science.
P2860
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P2860
Functional census of mutation sequence spaces: the example of p53 cancer rescue mutants.
description
2006 nî lūn-bûn
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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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2006年论文
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2006年论文
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name
Functional census of mutation sequence spaces: the example of p53 cancer rescue mutants.
@en
type
label
Functional census of mutation sequence spaces: the example of p53 cancer rescue mutants.
@en
prefLabel
Functional census of mutation sequence spaces: the example of p53 cancer rescue mutants.
@en
P2093
P2860
P356
P1476
Functional census of mutation sequence spaces: the example of p53 cancer rescue mutants
@en
P2093
Hiroto Saigo
Jianlin Cheng
Jonathan H Chen
Lawrence R Dearth
Pierre Baldi
Rainer K Brachmann
Richard H Lathrop
Samuel A Danziger
P2860
P304
P356
10.1109/TCBB.2006.22
P577
2006-04-01T00:00:00Z