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Polina Mamoshina

Showing results (1-10 of 26) with videos related to

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Trends in Pharmacological Sciences|July 8, 2019
Deep Aging Clocks: The Emergence of AI-Based Biomarkers of Aging and LongevityAlex Zhavoronkov, Polina Mamoshina
Cell Reports. Medicine|March 25, 2021
Toward a broader view of mechanisms of drug cardiotoxicityPolina Mamoshina, Blanca Rodriguez, Alfonso Bueno-Orovio
Frontiers in Pharmacology|June 9, 2020
Dual Transcriptomic and Molecular Machine Learning Predicts all Major Clinical Forms of Drug CardiotoxicityPolina Mamoshina, Alfonso Bueno-Orovio, Blanca Rodriguez
Frontiers in Aging|July 13, 2022
Adapting Blood DNA Methylation Aging Clocks for Use in Saliva Samples With Cell-type DeconvolutionFedor Galkin, Kirill Kochetov, Polina Mamoshina, et al.
Molecular Pharmaceutics|March 24, 2016
Applications of Deep Learning in BiomedicinePolina Mamoshina, Armando Vieira, Evgeny Putin, et al.
Aging|November 27, 2019
Deep biomarkers of aging and longevity: from research to applicationsAlex Zhavoronkov, Ricky Li, Candice Ma, et al.
Aging and Disease|August 3, 2021
DeepMAge: A Methylation Aging Clock Developed with Deep LearningFedor Galkin, Polina Mamoshina, Kirill Kochetov, et al.
Life (Basel, Switzerland)|August 27, 2021
Increased Pace of Aging in COVID-Related MortalityFedor Galkin, Austin Parish, Evelyne Bischof, et al.
Molecular Pharmaceutics|May 21, 2016
Deep Learning Applications for Predicting Pharmacological Properties of Drugs and Drug Repurposing Using Transcriptomic DataAlexander Aliper, Sergey Plis, Artem Artemov, et al.
Oncotarget|December 29, 2016
The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncologyArtur Kadurin, Alexander Aliper, Andrey Kazennov, et al.
Pageof 3

Showing results (1-10 of 26) with videos related to

Sort By:
Pageof 3
Trends in Pharmacological Sciences|July 8, 2019
Deep Aging Clocks: The Emergence of AI-Based Biomarkers of Aging and LongevityAlex Zhavoronkov, Polina Mamoshina
Cell Reports. Medicine|March 25, 2021
Toward a broader view of mechanisms of drug cardiotoxicityPolina Mamoshina, Blanca Rodriguez, Alfonso Bueno-Orovio
Frontiers in Pharmacology|June 9, 2020
Dual Transcriptomic and Molecular Machine Learning Predicts all Major Clinical Forms of Drug CardiotoxicityPolina Mamoshina, Alfonso Bueno-Orovio, Blanca Rodriguez
Frontiers in Aging|July 13, 2022
Adapting Blood DNA Methylation Aging Clocks for Use in Saliva Samples With Cell-type DeconvolutionFedor Galkin, Kirill Kochetov, Polina Mamoshina, et al.
Molecular Pharmaceutics|March 24, 2016
Applications of Deep Learning in BiomedicinePolina Mamoshina, Armando Vieira, Evgeny Putin, et al.
Aging|November 27, 2019
Deep biomarkers of aging and longevity: from research to applicationsAlex Zhavoronkov, Ricky Li, Candice Ma, et al.
Aging and Disease|August 3, 2021
DeepMAge: A Methylation Aging Clock Developed with Deep LearningFedor Galkin, Polina Mamoshina, Kirill Kochetov, et al.
Life (Basel, Switzerland)|August 27, 2021
Increased Pace of Aging in COVID-Related MortalityFedor Galkin, Austin Parish, Evelyne Bischof, et al.
Molecular Pharmaceutics|May 21, 2016
Deep Learning Applications for Predicting Pharmacological Properties of Drugs and Drug Repurposing Using Transcriptomic DataAlexander Aliper, Sergey Plis, Artem Artemov, et al.
Oncotarget|December 29, 2016
The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncologyArtur Kadurin, Alexander Aliper, Andrey Kazennov, et al.
Pageof 3