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Junbai Wang

Showing results (11-20 of 66) with videos related to

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Frontiers in Genetics|April 20, 2019
BayesPI-BAR2: A New Python Package for Predicting Functional Non-coding Mutations in Cancer Patient CohortsKirill Batmanov, Jan Delabie, Junbai Wang
Briefings in Bioinformatics|April 27, 2026
BayesPI-FLY: a Bayesian neural network approach for inferring feature weighted TF-DNA interactionGege Liu, Baoyan Bai, Junbai Wang
Bioinformatics (Oxford, England)|November 25, 2003
MGraph: graphical models for microarray data analysisJunbai Wang, Ola Myklebost, Eivind Hovig
Computational and Structural Biotechnology Journal|May 2, 2022
Integrating whole genome sequencing, methylation, gene expression, topological associated domain information in regulatory mutation prediction: A study of follicular lymphomaAmna Farooq, Gunhild Trøen, Jan Delabie, et al.
BMC Genomics|June 21, 2014
Characterizing a collective and dynamic component of chromatin immunoprecipitation enrichment profiles in yeastLucas D Ward, Junbai Wang, Harmen J Bussemaker
Iscience|July 31, 2023
Identifying functional regulatory mutation blocks by integrating genome sequencing and transcriptome dataMingyi Yang, Omer Ali, Magnar Bjørås, et al.
Thescientificworldjournal|April 2, 2014
Biomedical informatics and computational biology for high-throughput data analysisBairong Shen, Jian Ma, Jiajun Wang, et al.
STAR Protocols|July 2, 2026
Protocol for identifying functional regulatory mutation blocks by integrating genome sequencing and transcriptome dataMingyi Yang, Gege Liu, Magnar Bjørås, et al.
Journal of Biomedical Informatics|July 6, 2005
New probabilistic graphical models for genetic regulatory networks studiesJunbai Wang, Leo Wang-Kit Cheung, Jan Delabie
Methods (San Diego, Calif.)|August 13, 2016
An integrated approach to infer dynamic protein-gene interactions - A case study of the human P53 proteinJunbai Wang, Qianqian Wu, Xiaohua Tony Hu, et al.
Pageof 7

Showing results (11-20 of 66) with videos related to

Sort By:
Pageof 7
Frontiers in Genetics|April 20, 2019
BayesPI-BAR2: A New Python Package for Predicting Functional Non-coding Mutations in Cancer Patient CohortsKirill Batmanov, Jan Delabie, Junbai Wang
Briefings in Bioinformatics|April 27, 2026
BayesPI-FLY: a Bayesian neural network approach for inferring feature weighted TF-DNA interactionGege Liu, Baoyan Bai, Junbai Wang
Bioinformatics (Oxford, England)|November 25, 2003
MGraph: graphical models for microarray data analysisJunbai Wang, Ola Myklebost, Eivind Hovig
Computational and Structural Biotechnology Journal|May 2, 2022
Integrating whole genome sequencing, methylation, gene expression, topological associated domain information in regulatory mutation prediction: A study of follicular lymphomaAmna Farooq, Gunhild Trøen, Jan Delabie, et al.
BMC Genomics|June 21, 2014
Characterizing a collective and dynamic component of chromatin immunoprecipitation enrichment profiles in yeastLucas D Ward, Junbai Wang, Harmen J Bussemaker
Iscience|July 31, 2023
Identifying functional regulatory mutation blocks by integrating genome sequencing and transcriptome dataMingyi Yang, Omer Ali, Magnar Bjørås, et al.
Thescientificworldjournal|April 2, 2014
Biomedical informatics and computational biology for high-throughput data analysisBairong Shen, Jian Ma, Jiajun Wang, et al.
STAR Protocols|July 2, 2026
Protocol for identifying functional regulatory mutation blocks by integrating genome sequencing and transcriptome dataMingyi Yang, Gege Liu, Magnar Bjørås, et al.
Journal of Biomedical Informatics|July 6, 2005
New probabilistic graphical models for genetic regulatory networks studiesJunbai Wang, Leo Wang-Kit Cheung, Jan Delabie
Methods (San Diego, Calif.)|August 13, 2016
An integrated approach to infer dynamic protein-gene interactions - A case study of the human P53 proteinJunbai Wang, Qianqian Wu, Xiaohua Tony Hu, et al.
Pageof 7