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Genomics, Proteomics & Bioinformatics
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December 23, 2018
TELS: A Novel Computational Framework for Identifying Motif Signatures of Transcribed Enhancers
Dimitrios Kleftogiannis, Haitham Ashoor, Vladimir B Bajic
Bioinformatics (Oxford, England)
|
November 30, 2017
DDR: efficient computational method to predict drug-target interactions using graph mining and machine learning approaches
Rawan S Olayan, Haitham Ashoor, Vladimir B Bajic
Bioinformatics (Oxford, England)
|
June 20, 2018
DDR: efficient computational method to predict drug-target interactions using graph mining and machine learning approaches
Rawan S Olayan, Haitham Ashoor, Vladimir B Bajic
Database : the Journal of Biological Databases and Curation
|
September 7, 2015
DENdb: database of integrated human enhancers
Haitham Ashoor, Dimitrios Kleftogiannis, Aleksandar Radovanovic, et al.
Nucleic Acids Research
|
January 6, 2017
HMCan-diff: a method to detect changes in histone modifications in cells with different genetic characteristics
Haitham Ashoor, Caroline Louis-Brennetot, Isabelle Janoueix-Lerosey, et al.
Bioinformatics (Oxford, England)
|
September 12, 2013
HMCan: a method for detecting chromatin modifications in cancer samples using ChIP-seq data
Haitham Ashoor, Aurélie Hérault, Aurélie Kamoun, et al.
Scientific Reports
|
January 12, 2021
epihet for intra-tumoral epigenetic heterogeneity analysis and visualization
Xiaowen Chen, Haitham Ashoor, Ryan Musich, et al.
Nature Communications
|
March 5, 2020
Graph embedding and unsupervised learning predict genomic sub-compartments from HiC chromatin interaction data
Haitham Ashoor, Xiaowen Chen, Wojciech Rosikiewicz, et al.
Ebiomedicine
|
June 28, 2023
Plasma protein biomarkers for early prediction of lung cancer
Michael P A Davies, Takahiro Sato, Haitham Ashoor, et al.
Journal of Cheminformatics
|
January 12, 2021
DTiGEMS+: drug-target interaction prediction using graph embedding, graph mining, and similarity-based techniques
Maha A Thafar, Rawan S Olayan, Haitham Ashoor, et al.
Page
of 2
Search research articles
Search
Showing results (1-10 of 15) with videos related to
Sort By:
Page
of 2
Genomics, Proteomics & Bioinformatics
|
December 23, 2018
TELS: A Novel Computational Framework for Identifying Motif Signatures of Transcribed Enhancers
Dimitrios Kleftogiannis, Haitham Ashoor, Vladimir B Bajic
Bioinformatics (Oxford, England)
|
November 30, 2017
DDR: efficient computational method to predict drug-target interactions using graph mining and machine learning approaches
Rawan S Olayan, Haitham Ashoor, Vladimir B Bajic
Bioinformatics (Oxford, England)
|
June 20, 2018
DDR: efficient computational method to predict drug-target interactions using graph mining and machine learning approaches
Rawan S Olayan, Haitham Ashoor, Vladimir B Bajic
Database : the Journal of Biological Databases and Curation
|
September 7, 2015
DENdb: database of integrated human enhancers
Haitham Ashoor, Dimitrios Kleftogiannis, Aleksandar Radovanovic, et al.
Nucleic Acids Research
|
January 6, 2017
HMCan-diff: a method to detect changes in histone modifications in cells with different genetic characteristics
Haitham Ashoor, Caroline Louis-Brennetot, Isabelle Janoueix-Lerosey, et al.
Bioinformatics (Oxford, England)
|
September 12, 2013
HMCan: a method for detecting chromatin modifications in cancer samples using ChIP-seq data
Haitham Ashoor, Aurélie Hérault, Aurélie Kamoun, et al.
Scientific Reports
|
January 12, 2021
epihet for intra-tumoral epigenetic heterogeneity analysis and visualization
Xiaowen Chen, Haitham Ashoor, Ryan Musich, et al.
Nature Communications
|
March 5, 2020
Graph embedding and unsupervised learning predict genomic sub-compartments from HiC chromatin interaction data
Haitham Ashoor, Xiaowen Chen, Wojciech Rosikiewicz, et al.
Ebiomedicine
|
June 28, 2023
Plasma protein biomarkers for early prediction of lung cancer
Michael P A Davies, Takahiro Sato, Haitham Ashoor, et al.
Journal of Cheminformatics
|
January 12, 2021
DTiGEMS+: drug-target interaction prediction using graph embedding, graph mining, and similarity-based techniques
Maha A Thafar, Rawan S Olayan, Haitham Ashoor, et al.
Page
of 2