The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology
A Zhavoronkov , Q Vanhaelen , A Aliper , K Khrabrov
SCOPUS-2017-8-7-SID85012890514
266
2017
Using Signaling Pathway Activation Analysis to Identify Prospective Drugs that May Be Used for Treatment of Androgenetic Alopecia
E Schastnaya , P Mamoshina , A Aliper , A Artemov
Using Signaling Pathway Activation Analysis to Identify Prospective Drugs that May Slow Down or Reverse the Effects of Skin Aging and Photoaging
A Aliper , P Mamoshina , A Artemov , A Moskalev
Arabidopsis DNA topoisomerase I alpha is required for adaptive response to light and flower development.
Evgenia V. Kupriyanova , Evgeniy V. Albert , Aleksandra I. Bliznina , Polina O. Mamoshina
Biology Open 6 ( 6) 832 -843
1
2017
IN VITRO EVALUATION OF CELLS PROLIFERATIVE CAPACITY OF ARABIDOPSIS THALIANA MUTANT WITH DISTURBED SHOOT APICAL MERISTEM FUNCTION
PO Mamoshina , EV Kupriyanova , UN Kavai-ool , TA Ezhova
Plant Genetics, Genomics, Bioinformatics and Biotechnology 33 -33
2015
Toward a broader view of mechanisms of drug cardiotoxicity.
Alfonso Bueno-Orovio , Blanca Rodriguez , Polina Mamoshina
Cell reports. Medicine 2 ( 3) 100216 -100216
29
2021
Deep Aging Clocks: The Emergence of AI-Based Biomarkers of Aging and Longevity
Alex Zhavoronkov , Polina Mamoshina
Trends in Pharmacological Sciences 40 ( 8) 546 -549
13
2019
ARDD 2020: from aging mechanisms to interventions
Garik V Mkrtchyan , Kotb Abdelmohsen , Pénélope Andreux , Ieva Bagdonaite
Aging 12 ( 24) 24484 -24503
1
2020
Aging and drug discovery.
Daniela Bakula , Alexander M. Aliper , Polina Mamoshina , Michael A. Petr
Aging 10 ( 11) 3079 -3088
15
2018
Deep biomarkers of aging and longevity: from research to applications.
Alex Zhavoronkov , Ricky Li , Candice Ma , Polina Mamoshina
Aging (Albany NY) 11 ( 22) 10771 -10780
12
2019
Biohorology and biomarkers of aging: Current state-of-the-art, challenges and opportunities.
Fedor Galkin , Polina Mamoshina , Alex Aliper , João Pedro de Magalhães
Ageing Research Reviews 60 101050
61
2020
Machine Learning on Human Muscle Transcriptomic Data for Biomarker Discovery and Tissue-Specific Drug Target Identification.
Polina Mamoshina , Marina Volosnikova , Ivan V. Ozerov , Evgeny Putin
Frontiers in Genetics 9 242 -242
46
2018
Human Gut Microbiome Aging Clock Based on Taxonomic Profiling and Deep Learning.
Fedor Galkin , Polina Mamoshina , Alex Aliper , Evgeny Putin
iScience 23 ( 6) 101199
16
2020
Deep Integrated Biomarkers of Aging
Polina Mamoshina , Alex Zhavoronkov
Springer, Cham 281 -291
4
2019
Dual Transcriptomic and Molecular Machine Learning Predicts all Major Clinical Forms of Drug Cardiotoxicity
Polina Mamoshina , Alfonso Bueno-Orovio , Blanca Rodriguez
Frontiers in Pharmacology 11 639
2
2020
Applications of Deep Learning in Biomedicine
Polina Mamoshina , Armando Vieira , Evgeny Putin , Alex Zhavoronkov
Molecular Pharmaceutics 13 ( 5) 1445 -1454
602
2016
Deep Learning Applications for Predicting Pharmacological Properties of Drugs and Drug Repurposing Using Transcriptomic Data
Alexander Aliper , Sergey Plis , Artem Artemov , Alvaro Ulloa
Molecular Pharmaceutics 13 ( 7) 2524 -2530
407
2016
Entangled Conditional Adversarial Autoencoder for de Novo Drug Discovery
Daniil Polykovskiy , Alexander Zhebrak , Dmitry Vetrov , Yan Ivanenkov
Molecular Pharmaceutics 15 ( 10) 4398 -4405
161
2018
Machine learning for six forms of cardiotoxicity prediction
Polina Mamoshina , Alfonso Bueno-Orovio , Blanca Rodriguez
Journal of Pharmacological and Toxicological Methods 105 106802
2020
Population Specific Biomarkers of Human Aging: A Big Data Study Using South Korean, Canadian, and Eastern European Patient Populations.
Polina Mamoshina , Kirill Kochetov , Evgeny Putin , Franco Cortese
The Journals of Gerontology: Series A 73 ( 11) 1482 -1490
50
2018