Author

Polina Mamoshina

Hong Kong Science and Technology Parks CorporationORCID 0000-0002-7705-4694Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Organism:human· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Assay:metagenomics· 1

Frequent Co-Authors

Alex A. ZhavoronkoviD· 2 shared Alex AliperiD· 2 shared Eugene LaneiD· 2 shared Fedor GalkiniD· 1 shared Kirill Kochetov· 1 shared Vadim N. GladysheviD· 1 shared Владимир Борисович МоскалевiD· 1 shared

Activity by Year

2019-2020 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 18 mutual co-author links

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2 shared papersBioinformatics

Alex A. ZhavoronkovORCID

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2 papers

Recent·Most cited

Human microbiome aging clocks based on deep learning and tandem of permutation feature importance and accumulated local effects

Fedor Galkin, Polina Mamoshina, Alex Aliper, Eugene Lane, Владимир Борисович Москалев, Vadim N. Gladyshev, Alex A. Zhavoronkov

The paper develops a deep learning model to predict human biological age from gut microbiome data and identifies key microbial biomarkers associated with aging.

iScience · May 23, 2020Peer-reviewedBioinformatics

Testing for batch effect through age predictors

Polina Mamoshina, Kirill Kochetov, Eugene Lane, Alex Aliper, Alex A. Zhavoronkov

The paper develops a deep-learned age predictor from transcriptomic data and shows that batch effects can obscure age-related changes.

bioRxiv · Jan 27, 2019 · PreprintBioinformatics