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Theodore Sakellaropoulos

Showing results (31-40 of 37) with videos related to

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The Journal of Investigative Dermatology|November 10, 2021
Deep Learning and Pathomics Analyses Reveal Cell Nuclei as Important Features for Mutation Prediction of BRAF-Mutated MelanomasRandie H Kim, Sofia Nomikou, Nicolas Coudray, et al.
Pharmacology & Therapeutics|August 3, 2019
Machine learning and data mining frameworks for predicting drug response in cancer: An overview and a novel in silico screening process based on association rule miningKonstantinos Vougas, Theodore Sakellaropoulos, Athanassios Kotsinas, et al.
Scientific Data|May 16, 2015
The species translation challenge-a systems biology perspective on human and rat bronchial epithelial cellsCarine Poussin, Carole Mathis, Leonidas G Alexopoulos, et al.
Proceedings of the National Academy of Sciences of the United States of America|April 21, 2019
MAPK pathway and B cells overactivation in multiple sclerosis revealed by phosphoproteomics and genomic analysisEkaterina Kotelnikova, Narsis A Kiani, Dimitris Messinis, et al.
Cell Reports|December 12, 2019
A Deep Learning Framework for Predicting Response to Therapy in CancerTheodore Sakellaropoulos, Konstantinos Vougas, Sonali Narang, et al.
Cancer Discovery|February 3, 2026
A targetable developmental program co-regulates angiogenesis and immune evasion in melanomaPietro Berico, Amanda Flores Yanke, Fatemeh Vand-Rajabpour, et al.
Nature Communications|November 8, 2023
Inflammation in the tumor-adjacent lung as a predictor of clinical outcome in lung adenocarcinomaIgor Dolgalev, Hua Zhou, Nina Murrell, et al.
Pageof 4

Showing results (31-40 of 37) with videos related to

Sort By:
Pageof 4
You have reached the last page of results.This site can display upto 37 results.
The Journal of Investigative Dermatology|November 10, 2021
Deep Learning and Pathomics Analyses Reveal Cell Nuclei as Important Features for Mutation Prediction of BRAF-Mutated MelanomasRandie H Kim, Sofia Nomikou, Nicolas Coudray, et al.
Pharmacology & Therapeutics|August 3, 2019
Machine learning and data mining frameworks for predicting drug response in cancer: An overview and a novel in silico screening process based on association rule miningKonstantinos Vougas, Theodore Sakellaropoulos, Athanassios Kotsinas, et al.
Scientific Data|May 16, 2015
The species translation challenge-a systems biology perspective on human and rat bronchial epithelial cellsCarine Poussin, Carole Mathis, Leonidas G Alexopoulos, et al.
Proceedings of the National Academy of Sciences of the United States of America|April 21, 2019
MAPK pathway and B cells overactivation in multiple sclerosis revealed by phosphoproteomics and genomic analysisEkaterina Kotelnikova, Narsis A Kiani, Dimitris Messinis, et al.
Cell Reports|December 12, 2019
A Deep Learning Framework for Predicting Response to Therapy in CancerTheodore Sakellaropoulos, Konstantinos Vougas, Sonali Narang, et al.
Cancer Discovery|February 3, 2026
A targetable developmental program co-regulates angiogenesis and immune evasion in melanomaPietro Berico, Amanda Flores Yanke, Fatemeh Vand-Rajabpour, et al.
Nature Communications|November 8, 2023
Inflammation in the tumor-adjacent lung as a predictor of clinical outcome in lung adenocarcinomaIgor Dolgalev, Hua Zhou, Nina Murrell, et al.
Pageof 4