P
Polina Mamoshina
Researcher at University of Oxford
Publications - 20
Citations - 957
Polina Mamoshina is an academic researcher from University of Oxford. The author has contributed to research in topics: Biomarkers of aging & Cardiotoxicity. The author has an hindex of 11, co-authored 20 publications receiving 490 citations. Previous affiliations of Polina Mamoshina include Johns Hopkins University.
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Journal ArticleDOI
Entangled Conditional Adversarial Autoencoder for de Novo Drug Discovery
Daniil Polykovskiy,Alexander Zhebrak,Dmitry Vetrov,Yan A. Ivanenkov,Yan A. Ivanenkov,Vladimir A. Aladinskiy,Polina Mamoshina,Marine E. Bozdaganyan,Alexander Aliper,Alex Zhavoronkov,Artur Kadurin +10 more
TL;DR: A new generative architecture is proposed, entangled conditional adversarial autoencoder, that generates molecular structures based on various properties, such as activity against a specific protein, solubility, or ease of synthesis, that is applied to generate a novel inhibitor of Janus kinase 3.
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Population Specific Biomarkers of Human Aging: A Big Data Study Using South Korean, Canadian, and Eastern European Patient Populations.
Polina Mamoshina,Kirill Kochetov,Kirill Kochetov,Evgeny Putin,Evgeny Putin,Franco Cortese,Alexander Aliper,Won-Suk Lee,Sung-Min Ahn,Lee Uhn,Neil Skjodt,Olga Kovalchuk,Morten Scheibye-Knudsen,Alex Zhavoronkov +13 more
TL;DR: A deep learning-based hematological aging clock modeled using the large combined dataset of Canadian, South Korean, and Eastern European population blood samples that show increased predictive accuracy in individual populations compared to population specific hematologic aging clocks is presented.
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Artificial intelligence for aging and longevity research: Recent advances and perspectives.
Alex Zhavoronkov,Polina Mamoshina,Quentin Vanhaelen,Morten Scheibye-Knudsen,Alexey Moskalev,Alexander Aliper +5 more
TL;DR: AI biomarkers of aging enable a holistic view of biological processes and allow for novel methods for building causal models-extracting the most important features and identifying biological targets and mechanisms.
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Human Gut Microbiome Aging Clock Based on Taxonomic Profiling and Deep Learning.
Fedor Galkin,Polina Mamoshina,Alexander Aliper,Evgeny Putin,Vladimir Moskalev,Vadim N. Gladyshev,Alex Zhavoronkov +6 more
TL;DR: The described intestinal clock represents a unique quantitative model of gut microflora aging and provides a starting point for building host aging and gut community succession into a single narrative.
Journal ArticleDOI
Biohorology and biomarkers of aging: Current state-of-the-art, challenges and opportunities.
Fedor Galkin,Polina Mamoshina,Alexander Aliper,João Pedro de Magalhães,Vadim N. Gladyshev,Alex Zhavoronkov +5 more
TL;DR: A detailed comparison of existing mouse and human aging clocks is offered, and deep learning, deep neural networks and generative approaches are expected to be the next power tools in this timely and actively developing field.