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Biorxiv : the Preprint Server for Biology
|
November 24, 2025
Empirical Evaluation of Single-Cell Foundation Models for Predicting Cancer Outcomes
Haitham Elmarakeby, Ahmed Roman, Shreya Johri, et al.
Genome Medicine
|
December 1, 2018
Genomics of response to immune checkpoint therapies for cancer: implications for precision medicine
Jake R Conway, Eric Kofman, Shirley S Mo, et al.
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|
August 29, 2017
Beacon Editor: Capturing Signal Transduction Pathways Using the Systems Biology Graphical Notation Activity Flow Language
Haitham Elmarakeby, Mostafa Arefiyan, Elijah Myers, et al.
Frontiers in Plant Science
|
January 10, 2017
A Machine Learning Approach to Predict Gene Regulatory Networks in Seed Development in Arabidopsis
Ying Ni, Delasa Aghamirzaie, Haitham Elmarakeby, et al.
Biorxiv : the Preprint Server for Biology
|
May 4, 2026
Expanding P-NET, a multi-purpose biologically informed deep learning framework
Marc Glettig, Andrew Zhou, Chenzhang Zhou, et al.
The Plant Journal : for Cell and Molecular Biology
|
December 19, 2015
Potential targets of VIVIPAROUS1/ABI3-LIKE1 (VAL1) repression in developing Arabidopsis thaliana embryos
Andrew Schneider, Delasa Aghamirzaie, Haitham Elmarakeby, et al.
JCO Clinical Cancer Informatics
|
August 7, 2020
Natural Language Processing to Ascertain Cancer Outcomes From Medical Oncologist Notes
Kenneth L Kehl, Wenxin Xu, Eva Lepisto, et al.
JAMA Oncology
|
July 26, 2019
Assessment of Deep Natural Language Processing in Ascertaining Oncologic Outcomes From Radiology Reports
Kenneth L Kehl, Haitham Elmarakeby, Mizuki Nishino, et al.
JCO Clinical Cancer Informatics
|
June 7, 2021
Clinical Inflection Point Detection on the Basis of EHR Data to Identify Clinical Trial-Ready Patients With Cancer
Kenneth L Kehl, Stefan Groha, Eva M Lepisto, et al.
Nature Communications
|
December 16, 2021
Artificial intelligence-aided clinical annotation of a large multi-cancer genomic dataset
Kenneth L Kehl, Wenxin Xu, Alexander Gusev, et al.
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of 2
Search research articles
Search
Showing results (1-10 of 14) with videos related to
Sort By:
Page
of 2
Biorxiv : the Preprint Server for Biology
|
November 24, 2025
Empirical Evaluation of Single-Cell Foundation Models for Predicting Cancer Outcomes
Haitham Elmarakeby, Ahmed Roman, Shreya Johri, et al.
Genome Medicine
|
December 1, 2018
Genomics of response to immune checkpoint therapies for cancer: implications for precision medicine
Jake R Conway, Eric Kofman, Shirley S Mo, et al.
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|
August 29, 2017
Beacon Editor: Capturing Signal Transduction Pathways Using the Systems Biology Graphical Notation Activity Flow Language
Haitham Elmarakeby, Mostafa Arefiyan, Elijah Myers, et al.
Frontiers in Plant Science
|
January 10, 2017
A Machine Learning Approach to Predict Gene Regulatory Networks in Seed Development in Arabidopsis
Ying Ni, Delasa Aghamirzaie, Haitham Elmarakeby, et al.
Biorxiv : the Preprint Server for Biology
|
May 4, 2026
Expanding P-NET, a multi-purpose biologically informed deep learning framework
Marc Glettig, Andrew Zhou, Chenzhang Zhou, et al.
The Plant Journal : for Cell and Molecular Biology
|
December 19, 2015
Potential targets of VIVIPAROUS1/ABI3-LIKE1 (VAL1) repression in developing Arabidopsis thaliana embryos
Andrew Schneider, Delasa Aghamirzaie, Haitham Elmarakeby, et al.
JCO Clinical Cancer Informatics
|
August 7, 2020
Natural Language Processing to Ascertain Cancer Outcomes From Medical Oncologist Notes
Kenneth L Kehl, Wenxin Xu, Eva Lepisto, et al.
JAMA Oncology
|
July 26, 2019
Assessment of Deep Natural Language Processing in Ascertaining Oncologic Outcomes From Radiology Reports
Kenneth L Kehl, Haitham Elmarakeby, Mizuki Nishino, et al.
JCO Clinical Cancer Informatics
|
June 7, 2021
Clinical Inflection Point Detection on the Basis of EHR Data to Identify Clinical Trial-Ready Patients With Cancer
Kenneth L Kehl, Stefan Groha, Eva M Lepisto, et al.
Nature Communications
|
December 16, 2021
Artificial intelligence-aided clinical annotation of a large multi-cancer genomic dataset
Kenneth L Kehl, Wenxin Xu, Alexander Gusev, et al.
Page
of 2