List of works - Yaping Fang

A semi-supervised learning based method: Laplacian support vector machine used in diabetes disease diagnosis

scientific article published on 28 May 2009

Diagnostic prediction of complex diseases using phase-only correlation based on virtual sample template

scientific article

Discrimination of soluble and aggregation-prone proteins based on sequence information ⬇️

scientific article published on February 25, 2013

Function Annotation of Hepatic Retinoid x Receptor α Based on Genome-Wide DNA Binding and Transcriptome Profiling ⬇️

scientific article published on November 15, 2012

Genome-wide binding and transcriptome analysis of human farnesoid X receptor in primary human hepatocytes

scientific article

Genomic law guided gene prediction in fungi and metazoans

scientific article published on 21 February 2013

Identification of RNA-binding sites in proteins by integrating various sequence information

scientific article published on 12 June 2010

Identification of properties important to protein aggregation using feature selection

scientific article

In Silico Classification of Proteins from Acidic and Neutral Cytoplasms ⬇️

scientific article published on September 26, 2012

NURBS: a database of experimental and predicted nuclear receptor binding sites of mouse ⬇️

scientific article published on November 29, 2012

PPARβ Regulates Liver Regeneration by Modulating Akt and E2f Signaling ⬇️

scientific article published on June 18, 2013

Predicting DNA-binding proteins: approached from Chou's pseudo amino acid composition and other specific sequence features

scientific article

Predicting residue–residue contacts using random forest models ⬇️

scientific article published on October 20, 2011

Prediction of beta-turn in protein using E-SSpred and support vector machine.

scientific article

Prediction of core cancer genes using multi-task classification framework ⬇️

scientific article published on October 3, 2012

The role of retinoic acid in hepatic lipid homeostasis defined by genomic binding and transcriptome profiling

scientific article

Using multiple linear regression and physicochemical changes of amino acid mutations to predict antigenic variants of influenza A/H3N2 viruses.

scientific article published on January 2014

Using multitask classification methods to investigate the kinase-specific phosphorylation sites ⬇️

scientific article published on June 21, 2012

List of works by Yaping Fang

A semi-supervised learning based method: Laplacian support vector machine used in diabetes disease diagnosis

Diagnostic prediction of complex diseases using phase-only correlation based on virtual sample template

Discrimination of soluble and aggregation-prone proteins based on sequence information ⬇️

Function Annotation of Hepatic Retinoid x Receptor α Based on Genome-Wide DNA Binding and Transcriptome Profiling ⬇️

Genome-wide binding and transcriptome analysis of human farnesoid X receptor in primary human hepatocytes

Genomic law guided gene prediction in fungi and metazoans

Identification of RNA-binding sites in proteins by integrating various sequence information

Identification of properties important to protein aggregation using feature selection

In Silico Classification of Proteins from Acidic and Neutral Cytoplasms ⬇️

NURBS: a database of experimental and predicted nuclear receptor binding sites of mouse ⬇️

PPARβ Regulates Liver Regeneration by Modulating Akt and E2f Signaling ⬇️

Predicting DNA-binding proteins: approached from Chou's pseudo amino acid composition and other specific sequence features

Predicting residue–residue contacts using random forest models ⬇️

Prediction of beta-turn in protein using E-SSpred and support vector machine.

Prediction of core cancer genes using multi-task classification framework ⬇️

The role of retinoic acid in hepatic lipid homeostasis defined by genomic binding and transcriptome profiling

Using multiple linear regression and physicochemical changes of amino acid mutations to predict antigenic variants of influenza A/H3N2 viruses.

Using multitask classification methods to investigate the kinase-specific phosphorylation sites ⬇️