A Hybrid Deep Learning Model for Predicting Protein Hydroxylation Sites

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A Hybrid Deep Learning Model for Predicting Protein Hydroxylation Sites

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im September 2018 veröffentlichter wissenschaftlicher Artikel

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wetenschappelijk artikel

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наукова стаття, опублікована у вересні 2018

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A Hybrid Deep Learning Model for Predicting Protein Hydroxylation Sites

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A Hybrid Deep Learning Model for Predicting Protein Hydroxylation Sites

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A Hybrid Deep Learning Model for Predicting Protein Hydroxylation Sites

@en

A Hybrid Deep Learning Model for Predicting Protein Hydroxylation Sites

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A Hybrid Deep Learning Model for Predicting Protein Hydroxylation Sites

@en

A Hybrid Deep Learning Model for Predicting Protein Hydroxylation Sites

@nl

P1476

A Hybrid Deep Learning Model for Predicting Protein Hydroxylation Sites

@en

P2093

Bo Liao

http://www.w3.org/2001/XMLSchema#string

Xingyu Xu

http://www.w3.org/2001/XMLSchema#string

P2860

Prediction and analysis of protein hydroxyproline and hydroxylysine

The meaning and use of the area under a receiver operating characteristic (ROC) curve

Improving the accuracy of PSI-BLAST protein database searches with composition-based statistics and other refinements

iHyd-PseAAC: predicting hydroxyproline and hydroxylysine in proteins by incorporating dipeptide position-specific propensity into pseudo amino acid composition

Predicting human immunodeficiency virus protease cleavage sites in proteins by a discriminant function method.

Prediction of human immunodeficiency virus protease cleavage sites in proteins.

Proteomics-based identification of novel factor inhibiting hypoxia-inducible factor (FIH) substrates indicates widespread asparaginyl hydroxylation of ankyrin repeat domain-containing proteins.

The importance of proline residues in the structure, stability and susceptibility to proteolytic degradation of collagens.

iHyd-PseCp: Identify hydroxyproline and hydroxylysine in proteins by incorporating sequence-coupled effects into general PseAAC.

Some remarks on protein attribute prediction and pseudo amino acid composition.

P304

2817

http://www.w3.org/2001/XMLSchema#string

P31

scholarly article

P356

10.3390/IJMS19092817

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P407

English

P433

http://www.w3.org/2001/XMLSchema#string

P478

http://www.w3.org/2001/XMLSchema#string

P50

Jialiang Yang

Haixia Long

P577

2018-09-18T00:00:00Z

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P698

30231550

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P921

molecular biology

catalysis

P932

6164125

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