Author

Boris Zhurov

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Assay:electronic health records· 2 Organism:human· 2 Approach:statistical model· 2 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

L. I. Men’shikov· 2 shared Mikhail A. PyatnitskiyiD· 2 shared Peter O. FedicheviD· 2 shared Timothy V. PyrkoviD· 2 shared Aleksandr ZeniniD· 1 shared Alexey Kondrashin· 1 shared Andrei V. GudkoviD· 1 shared Evgeny Getmantsev· 1 shared

Activity by Year

2018-2018 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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2 shared papersSystems Biology

L. I. Men’shikov

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2 papers

Recent·Most cited

Quantitative Characterization of Biological Age and Frailty Based on Locomotor Activity Records

Timothy V. Pyrkov, Evgeny Getmantsev, Boris Zhurov, Konstantin Avchaciov, Mikhail A. Pyatnitskiy, L. I. Men’shikov, Kristina Khodova, Andrei V. Gudkov, Peter O. Fedichev

The paper quantifies biological age and frailty using locomotor activity data from NHANES and UKB, linking aging trajectories to mortality and health outcomes.

Aging · Oct 25, 2018Peer-reviewedSystems Biology

Extracting biological age from biomedical data via deep learning: too much of a good thing?

Timothy V. Pyrkov, Konstantin Slipensky, Mikhail Barg, Alexey Kondrashin, Boris Zhurov, Aleksandr Zenin, Mikhail A. Pyatnitskiy, L. I. Men’shikov, Sergei Markov, Peter O. Fedichev

This study compares biological age models using NHANES data, finding that supervised models improve age estimation but reduce mortality prediction accuracy, and introduces a new mortality risk model.

Scientific Reports · Mar 26, 2018Peer-reviewedBioinformatics