Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Suleiman A Khan

Showing results (1-10 of 14) with videos related to

Pageof 2
Sort By:
Bioinformatics (Oxford, England)|November 30, 2017
Global proteomics profiling improves drug sensitivity prediction: results from a multi-omics, pan-cancer modeling approachMehreen Ali, Suleiman A Khan, Krister Wennerberg, et al.
Bioinformatics (Oxford, England)|September 9, 2017
Systematic identification of feature combinations for predicting drug response with Bayesian multi-view multi-task linear regressionMuhammad Ammad-Ud-Din, Suleiman A Khan, Krister Wennerberg, et al.
The Journal of Contemporary Dental Practice|January 5, 2017
Influence of Television Advertising on Behavior of Children across Socioeconomic BackgroundsRachana Bahuguna, Atul Jain, Divya Suryavanshi, et al.
Bioinformatics (Oxford, England)|August 28, 2014
Identification of structural features in chemicals associated with cancer drug response: a systematic data-driven analysisSuleiman A Khan, Seppo Virtanen, Olli P Kallioniemi, et al.
Drug Discovery Today|March 17, 2016
Transcriptional response networks for elucidating mechanisms of action of multitargeted agentsMilla Kibble, Suleiman A Khan, Niina Saarinen, et al.
Bioinformatics (Oxford, England)|September 3, 2016
Drug response prediction by inferring pathway-response associations with kernelized Bayesian matrix factorizationMuhammad Ammad-Ud-Din, Suleiman A Khan, Disha Malani, et al.
Disease Models & Mechanisms|October 7, 2015
From drug response profiling to target addiction scoring in cancer cell modelsBhagwan Yadav, Peddinti Gopalacharyulu, Tea Pemovska, et al.
Royal Society Open Science|November 18, 2020
An integrative machine learning approach to discovering multi-level molecular mechanisms of obesity using data from monozygotic twin pairsMilla Kibble, Suleiman A Khan, Muhammad Ammad-Ud-Din, et al.
BMC Bioinformatics|June 1, 2012
Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugsSuleiman A Khan, Ali Faisal, John Patrick Mpindi, et al.
NPJ Precision Oncology|July 24, 2021
Bayesian multi-source regression and monocyte-associated gene expression predict BCL-2 inhibitor resistance in acute myeloid leukemiaBrian S White, Suleiman A Khan, Mike J Mason, et al.
Pageof 2

Showing results (1-10 of 14) with videos related to

Sort By:
Pageof 2
Bioinformatics (Oxford, England)|November 30, 2017
Global proteomics profiling improves drug sensitivity prediction: results from a multi-omics, pan-cancer modeling approachMehreen Ali, Suleiman A Khan, Krister Wennerberg, et al.
Bioinformatics (Oxford, England)|September 9, 2017
Systematic identification of feature combinations for predicting drug response with Bayesian multi-view multi-task linear regressionMuhammad Ammad-Ud-Din, Suleiman A Khan, Krister Wennerberg, et al.
The Journal of Contemporary Dental Practice|January 5, 2017
Influence of Television Advertising on Behavior of Children across Socioeconomic BackgroundsRachana Bahuguna, Atul Jain, Divya Suryavanshi, et al.
Bioinformatics (Oxford, England)|August 28, 2014
Identification of structural features in chemicals associated with cancer drug response: a systematic data-driven analysisSuleiman A Khan, Seppo Virtanen, Olli P Kallioniemi, et al.
Drug Discovery Today|March 17, 2016
Transcriptional response networks for elucidating mechanisms of action of multitargeted agentsMilla Kibble, Suleiman A Khan, Niina Saarinen, et al.
Bioinformatics (Oxford, England)|September 3, 2016
Drug response prediction by inferring pathway-response associations with kernelized Bayesian matrix factorizationMuhammad Ammad-Ud-Din, Suleiman A Khan, Disha Malani, et al.
Disease Models & Mechanisms|October 7, 2015
From drug response profiling to target addiction scoring in cancer cell modelsBhagwan Yadav, Peddinti Gopalacharyulu, Tea Pemovska, et al.
Royal Society Open Science|November 18, 2020
An integrative machine learning approach to discovering multi-level molecular mechanisms of obesity using data from monozygotic twin pairsMilla Kibble, Suleiman A Khan, Muhammad Ammad-Ud-Din, et al.
BMC Bioinformatics|June 1, 2012
Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugsSuleiman A Khan, Ali Faisal, John Patrick Mpindi, et al.
NPJ Precision Oncology|July 24, 2021
Bayesian multi-source regression and monocyte-associated gene expression predict BCL-2 inhibitor resistance in acute myeloid leukemiaBrian S White, Suleiman A Khan, Mike J Mason, et al.
Pageof 2