Polina Mamoshina

Polina Mamoshina
Insilico Medicine · Research

BS

About

61
Publications
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2,449
Citations

Publications

Publications (61)
Article
Full-text available
DNA methylation aging clocks have become an invaluable tool in biogerontology research since their inception in 2013. Today, a variety of machine learning approaches have been tested for the purpose of predicting human age based on molecular-level features. Among these, deep learning, or neural networks, is an especially promising approach that has...
Article
Full-text available
Identifying prognostic biomarkers and risk stratification for COVID-19 patients is a challenging necessity. One of the core survival factors is patient age. However, chronological age is often severely biased due to dormant conditions and existing comorbidities. In this retrospective cohort study, we analyzed the data from 5315 COVID-19 patients (1...
Article
Full-text available
DeepMAge is a deep-learning DNA methylation aging clock that measures the organismal pace of aging with the information from human epigenetic profiles. In blood samples, DeepMAge can predict chronological age within a 2.8 years error margin, but in saliva samples, its performance is drastically reduced since aging clocks are restricted by the train...
Article
Full-text available
Cardiotoxicity, defined as toxicity that affects the heart, is one of the most common adverse drug effects. Numerous drugs have been shown to have the potential to induce lethal arrhythmias by affecting cardiac electrophysiology, which is the focus of current preclinical testing. However, a substantial number of drugs can also affect cardiac functi...
Article
Full-text available
Aging is emerging as a druggable target with growing interest from academia, industry and investors. New technologies such as artificial intelligence and advanced screening techniques, as well as a strong influence from the industry sector may lead to novel discoveries to treat age-related diseases. The present review summarizes presentations from...
Article
Full-text available
Computational methods can increase productivity of drug discovery pipelines, through overcoming challenges such as cardiotoxicity identification. We demonstrate prediction and preservation of cardiotoxic relationships for six drug-induced cardiotoxicity types using a machine learning approach on a large collected and curated dataset of transcriptio...
Article
Full-text available
The human gut microbiome is a complex ecosystem that both affects and is affected by its host status. Previous metagenomic analyses of gut microflora revealed associations between specific microbes and host age. Nonetheless there was no reliable way to tell a host’s age based on the gut community composition. Here we developed a method of predictin...
Article
Full-text available
The aging process results in multiple traceable footprints, which can be quantified and used to estimate an organism's age. Examples of such aging biomarkers include epigenetic changes, telomere attrition, and alterations in gene expression and metabolite concentrations. More than a dozen aging clocks use molecular features to predict an organism's...
Article
Multiple recent advances in machine learning enabled computer systems to exceed human performance in many tasks including voice, text, and speech recognition and complex strategy games. Aging is a complex multifactorial process driven by and resulting in the many minute changes transpiring at every level of the human organism. Deep learning systems...
Chapter
Recent advances in deep learning (DL) and other machine learning methods (ML) and the availability of large population data sets annotated with age and other features led to the development of the many predictors of chronological age frequently referred to as the deep aging clocks (DACs). Many of these aging clocks were pioneered by Insilico Medici...
Article
Full-text available
First published in 2016, predictors of chronological and biological age developed using deep learning (DL) are rapidly gaining popularity in the aging research community. These deep aging clocks can be used in a broad range of applications in the pharmaceutical industry, spanning target identification, drug discovery, data economics, and synthetic...
Preprint
Full-text available
Transcriptome profiling has been shown really useful in the understanding of the aging process. To date, transcriptomic data is the second most abundant omics data type following genomics. To deconvolute the relationship between transcriptomic changes and aging one needs to conduct an analysis on the comprehensive dataset. At the same time, biologi...
Article
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There is an association between smoking and cancer, cardiovascular disease and all-cause mortality. However, currently, there are no affordable and informative tests for assessing the effects of smoking on the rate of biological aging. In this study we demonstrate for the first time that smoking status can be predicted using blood biochemistry and...
Article
Full-text available
The applications of modern artificial intelligence (AI) algorithms within the field of aging research offer tremendous opportunities. Aging is an almost universal unifying feature possessed by all living organisms, tissues, and cells. Modern deep learning techniques used to develop age predictors offer new possibilities for formerly incompatible dy...
Article
Full-text available
Multiple interventions in the aging process have been discovered to extend the healthspan of model organisms. Both industry and academia are therefore exploring possible transformative molecules that target aging and age-associated diseases. In this overview, we summarize the presented talks and discussion points of the 5th Annual Aging and Drug Di...
Article
Full-text available
Modern computational approaches and machine learning techniques accelerate the invention of new drugs. Generative models can discover novel molecular structures within hours, while conventional drug discovery pipelines require months of work. In this paper, we propose a new generative architecture—Entangled Conditional Adversarial Autoencoder—that...
Article
Full-text available
For the past several decades, research in understanding the molecular basis of human muscle aging has progressed significantly. However, the development of accessible tissue-specific biomarkers of human muscle aging that may be measured to evaluate the effectiveness of therapeutic interventions is still a major challenge. Here we present a method f...
Data
A list of datasets analyzed in this study.
Article
Full-text available
While many efforts have been made to pave the way toward human space colonization, little consideration has been given to the methods of protecting spacefarers against harsh cosmic and local radioactive environments and the high costs associated with protection from the deleterious physiological effects of exposure to high-Linear energy transfer (h...
Article
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The increased availability of data and recent advancements in artificial intelligence present the unprecedented opportunities in healthcare and major challenges for the patients, developers, providers and regulators. The novel deep learning and transfer learning techniques are turning any data about the person into medical data transforming simple...
Article
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Accurate and physiologically meaningful biomarkers for human aging are key to assessing anti-aging therapies. Given ethnic differences in health, diet, lifestyle, behaviour, environmental exposures and even average rate of biological aging, it stands to reason that aging clocks trained on datasets obtained from specific ethnic populations are more...
Article
Background: Cardiotoxicity is one of the major drug safety concerns leading to discontinuation of the drug development process and market withdrawal. Current preclinical methods for drug cardiotoxicity largely rely on hERG ion channel inhibition or prolongation of the QT interval. Despite their recognized role in safety pharmacology, they mostly fo...
Article
Full-text available
Here we present the application of deep neural network (DNN) ensembles trained on transcriptomic data to identify the novel markers associated with the mammalian embryonic-fetal transition (EFT). Molecular markers of this process could provide important insights into regulatory mechanisms of normal development, epimorphic tissue regeneration and ca...
Article
Full-text available
Diversity is one of the fundamental properties for the survival of species, populations, and organizations. Recent advances in deep learning allow for the rapid and automatic assessment of organizational diversity and possible discrimination by race, sex, age and other parameters. Automating the process of assessing the organizational diversity usi...
Article
Full-text available
DNA topoisomerase TOP1α plays a specific role in Arabidopsis thaliana development and is required for stem cell regulation in shoot and floral meristems. Recently, a new role independent of meristem functioning has been described for TOP1α, namely, flowering time regulation. The same feature had been detected by us earlier for fas5, a mutant allele...
Article
Recent advances in deep learning and specifically in generative adversarial networks have demonstrated surprising results in generating new images and videos upon request even using natural language as input. In this paper we present the first application of generative adversarial autoencoders (AAE) for generating novel molecular fingerprints with...
Article
Here, we provide a comprehensive overview of the current status of in silico repurposing methods by establishing links between current technological trends, data availability and characteristics of the algorithms used in these methods. Using the case of the computational repurposing of fasudil as an alternative autophagy enhancer, we suggest a gene...
Article
Full-text available
Populations in developed nations throughout the world are rapidly aging, and the search for geroprotectors, or anti-aging interventions, has never been more important. Yet while hundreds of geroprotectors have extended lifespan in animal models, none have yet been approved for widespread use in humans. GeroScope is a computational tool that can aid...
Article
Full-text available
Deep learning is rapidly advancing many areas of science and technology with multiple success stories in image, text, voice and video recognition, robotics and autonomous driving. In this paper we demonstrate how deep neural networks (DNN) trained on large transcriptional response data sets can classify various drugs to therapeutic categories solel...
Article
Full-text available
One of the major impediments in human aging research is the absence of a comprehensive and actionable set of biomarkers that may be targeted and measured to track the effectiveness of therapeutic interventions. In this study, we designed a modular ensemble of 21 deep neural networks (DNNs) of varying depth, structure and optimization to predict hum...
Article
Increases in throughput and installed base of biomedical research equipment led to a massive accumulation of -omics data known to be highly variable, high-dimensional, and sourced from multiple often incompatible data platforms. While this data may be useful for biomarker identification and drug discovery, the bulk of it remains underutilized. Deep...
Poster
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Androgenetic alopecia or male pattern baldness is the most common form of hair loss in men. It is suspected that to some extent, this type of baldness is mediated by both androgen and non-androgen signals, however the underlying mechanisms remain largely unexplored. To explore signaling and metabolic pathway regulation during balding we used the Ge...
Article
Full-text available
As the level of interest in aging research increases, there is a growing number of geroprotectors, or therapeutic interventions that aim to extend the healthy lifespan and repair or reduce aging‐related damage in model organisms and, eventually, in humans. There is a clear need for a manually‐curated database of geroprotectors to compile and index...
Article
Full-text available
Polymorphisms of 62 peroxidase genes derived from Arabidopsis thaliana were investigated to evaluate evolutionary dynamics and divergence of peroxidase proteins. By comparing divergence of duplicated genes AtPrx53-AtPrx54 and AtPrx36- AtPrx72 and their products, nucleotide and amino acid substitutions were identified that were apparently targets of...

Questions

Questions (2)
Question
Dear colleagues,
Could you please share your experience publishing a paper in Journal of Gerontology? How long is a review process? 
Question
Dear Colleagues,
Can you please provide some good datasets of blood biochemistry and cell count data available for academic use?

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Projects

Projects (3)
Project
Re-defining biomedical data processing by developing legitimate ways to transform clinical data into life-saving traceable and tradable assets.
Project
Developmrnt of a systems bioinformatics platfrom for cell pathway analysis and personalized medicine, including, but not limited to, oncology.
Project
We are collecting blood biochemistry, transcriptomic, metabolomic, clinical and imaging data and training various deep neural network architectures to predict chronological age and health status of individuals. We also perform cross-species comparison. We are very collaborative and invite academic and industry partners to join this project.