Nikita Moshkov
Overview
Explore the profile of Nikita Moshkov including associated specialties, affiliations and a list of published articles.
Author names and details appear as published. Due to indexing inconsistencies, multiple individuals may share a name, and a single author may have variations. MedLuna displays this data as publicly available, without modification or verification
Snapshot
Snapshot
Articles
11
Citations
155
Followers
0
Related Specialties
Related Specialties
Top 10 Co-Authors
Top 10 Co-Authors
Published In
Published In
Affiliations
Affiliations
Soon will be listed here.
Recent Articles
1.
SuperCUT, an unsupervised multimodal image registration with deep learning for biomedical microscopy
Grexa I, Ivan Z, Migh E, Kovacs F, Bolck H, Zheng X, et al.
Brief Bioinform
. 2024 Mar;
25(2).
PMID: 38483256
Numerous imaging techniques are available for observing and interrogating biological samples, and several of them can be used consecutively to enable correlative analysis of different image modalities with varying resolutions...
2.
Moshkov N, Bornholdt M, Benoit S, Smith M, McQuin C, Goodman A, et al.
Nat Commun
. 2024 Feb;
15(1):1594.
PMID: 38383513
Measuring the phenotypic effect of treatments on cells through imaging assays is an efficient and powerful way of studying cell biology, and requires computational methods for transforming images into quantitative...
3.
Doron M, Moutakanni T, Chen Z, Moshkov N, Caron M, Touvron H, et al.
bioRxiv
. 2023 Jul;
PMID: 37398158
Accurately quantifying cellular morphology at scale could substantially empower existing single-cell approaches. However, measuring cell morphology remains an active field of research, which has inspired multiple computer vision algorithms over...
4.
Moshkov N, Becker T, Yang K, Horvath P, Dancik V, Wagner B, et al.
Nat Commun
. 2023 Apr;
14(1):1967.
PMID: 37031208
Predicting assay results for compounds virtually using chemical structures and phenotypic profiles has the potential to reduce the time and resources of screens for drug discovery. Here, we evaluate the...
5.
Hollandi R, Moshkov N, Paavolainen L, Tasnadi E, Piccinini F, Horvath P
Trends Cell Biol
. 2022 Jan;
32(4):295-310.
PMID: 35067424
Single nucleus segmentation is a frequent challenge of microscopy image processing, since it is the first step of many quantitative data analysis pipelines. The quality of tracking single cells, extracting...
6.
Moshkov N, Smetanin A, Tatarinova T
PeerJ
. 2022 Jan;
9:e12502.
PMID: 35003914
Summary: We developed , a new tool for determining local ancestry along a genome using whole-genome sequencing data or high-density genotyping experiments. PyLAE can process an arbitrarily large number of...
7.
Grexa I, Diosdi A, Harmati M, Kriston A, Moshkov N, Buzas K, et al.
Sci Rep
. 2021 Jul;
11(1):14813.
PMID: 34285291
Recent statistics report that more than 3.7 million new cases of cancer occur in Europe yearly, and the disease accounts for approximately 20% of all deaths. High-throughput screening of cancer...
8.
Moshkov N, Mathe B, Kertesz-Farkas A, Hollandi R, Horvath P
Sci Rep
. 2021 Feb;
11(1):3327.
PMID: 33531545
No abstract available.
9.
Hollandi R, Diosdi A, Hollandi G, Moshkov N, Horvath P
Mol Biol Cell
. 2020 Jul;
31(20):2179-2186.
PMID: 32697683
AnnotatorJ combines single-cell identification with deep learning (DL) and manual annotation. Cellular analysis quality depends on accurate and reliable detection and segmentation of cells so that the subsequent steps of...
10.
Piccinini F, Balassa T, Carbonaro A, Diosdi A, Toth T, Moshkov N, et al.
Comput Struct Biotechnol J
. 2020 Jul;
18:1287-1300.
PMID: 32612752
Today, we are fully immersed into the era of 3D biology. It has been extensively demonstrated that 3D models: () better mimic the physiology of human tissues; () can effectively...