Junbai Wang

发表

A new framework for identifying combinatorial regulation of transcription factors: A case study of the yeast cell cycle

Junbai Wang, Junbai Wang, 2007, J. Biomed. Informatics.

M-CGH: Analysing microarray-based CGH experiments

Junbai Wang, Leonardo A. Meza-Zepeda, Stine H. Kresse, 2004, BMC Bioinformatics.

Integrated study to infer dynamic protein-gene interactions in human p53 regulatory networks

Tianhai Tian, Junbai Wang, Qianqian Wu, 2015, 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

New probabilistic graphical models for genetic regulatory networks studies

Junbai Wang, Leo Wang-Kit Cheung, Jan Delabie, 2005, J. Biomed. Informatics.

MArray: analysing single, replicated or reversed microarray experiments

Eivind Hovig, Junbai Wang, Ola Myklebost, 2002, Bioinform..

Quality versus accuracy: result of a reanalysis of protein-binding microarrays from the DREAM5 challenge by using BayesPI2 including dinucleotide interdependence

Junbai Wang, Junbai Wang, 2014, BMC Bioinformatics.

Quantitative model for inferring dynamic regulation of the tumour suppressor gene p53

Tianhai Tian, Junbai Wang, T. Tian, 2010, BMC Bioinformatics.

An integrated approach to infer dynamic protein-gene interactions - A case study of the human P53 protein.

Tianhai Tian, Xiaohua Tony Hu, Junbai Wang, 2016, Methods.

HMST-Seq-Analyzer: A new python tool for differential methylation and hydroxymethylation analysis in various DNA methylation sequencing data

Torbjørn Rognes, Junbai Wang, Magnar Bjørås, 2020, Computational and structural biotechnology journal.

The effect of prior assumptions over the weights in BayesPI with application to study protein-DNA interactions from ChIP-based high-throughput data

Junbai Wang, 2009, BMC Bioinformatics.

Systems Biology Studies of Gene Network and Cell Signaling Pathway in Cancer Research

Tianhai Tian, Junbai Wang, Ben Davidson, 2013 .

BayesPI - a new model to study protein-DNA interactions: a case study of condition-specific protein binding parameters for Yeast transcription factors

Morigen, Junbai Wang, Junbai Wang, 2009, BMC Bioinformatics.

Clustering of the SOM easily reveals distinct gene expression patterns: results of a reanalysis of lymphoma study

Junbai Wang, Ola Myklebost, Jan Delabie, 2002, BMC Bioinformatics.

Tumor classification and marker gene prediction by feature selection and fuzzy c-means clustering using microarray data

Eivind Hovig, Inge Jonassen, Junbai Wang, 2003, BMC Bioinformatics.

MGraph: graphical models for microarray data analysis

Eivind Hovig, Junbai Wang, Ola Myklebost, 2003, Bioinform..

Computational biology of genome expression and regulation--a review of microarray bioinformatics.

Junbai Wang, Junbai Wang, 2008, Journal of environmental pathology, toxicology and oncology : official organ of the International Society for Environmental Toxicology and Cancer.

Biomedical Informatics and Computational Biology for High-Throughput Data Analysis

Bairong Shen, Junbai Wang, Jian Ma, 2014, TheScientificWorldJournal.

Computational study of associations between histone modification and protein-DNA binding in yeast genome by integrating diverse information

Junbai Wang, Junbai Wang, 2011, BMC Genomics.

Effective non-linear methods for inferring genetic regulation from time-series microarray gene expression data.

Tianhai Tian, Junbai Wang, T. Tian, 2012, Methods in molecular biology.

Genome-wide analysis uncovers high frequency, strong differential chromosomal interactions and their associated epigenetic patterns in E2-mediated gene regulation

Junbai Wang, Victor X Jin, Kun Huang, 2013, BMC Genomics.