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Single-cell Hi-C data analysis: safety in numbers.

Briefings in bioinformatics

Galitsyna AA, Gelfand MS.
PMID: 34406348
Brief Bioinform. 2021 Nov 05;22(6). doi: 10.1093/bib/bbab316.

Over the past decade, genome-wide assays for chromatin interactions in single cells have enabled the study of individual nuclei at unprecedented resolution and throughput. Current chromosome conformation capture techniques survey contacts for up to tens of thousands of individual...

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Galitsyna AA, Gelfand MS. Single-cell Hi-C data analysis: safety in numbers. Brief Bioinform. 2021;22(6)doi: 10.1093/bib/bbab316.
Galitsyna, A. A., & Gelfand, M. S. (2021). Single-cell Hi-C data analysis: safety in numbers. Briefings in bioinformatics, 22(6), . https://doi.org/10.1093/bib/bbab316
Galitsyna, Aleksandra A, and Gelfand, Mikhail S. "Single-cell Hi-C data analysis: safety in numbers." Briefings in bioinformatics vol. 22,6 (2021). doi: https://doi.org/10.1093/bib/bbab316
Galitsyna AA, Gelfand MS. Single-cell Hi-C data analysis: safety in numbers. Brief Bioinform. 2021 Nov 05;22(6). doi: 10.1093/bib/bbab316. PMID: 34406348; PMCID: PMC8575028.
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Cumulative contact frequency of a chromatin region is an intrinsic property linked to its function.

PeerJ

Samborskaia MD, Galitsyna A, Pletenev I, Trofimova A, Mironov AA, Gelfand MS, Khrameeva EE.
PMID: 32864204
PeerJ. 2020 Aug 10;8:e9566. doi: 10.7717/peerj.9566. eCollection 2020.

Regulation of gene transcription is a complex process controlled by many factors, including the conformation of chromatin in the nucleus. Insights into chromatin conformation on both local and global scales can be provided by the Hi-C (high-throughput chromosomes conformation...

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Samborskaia MD, Galitsyna A, Pletenev I, et al. Cumulative contact frequency of a chromatin region is an intrinsic property linked to its function. PeerJ. 2020;8:e9566doi: 10.7717/peerj.9566.
Samborskaia, M. D., Galitsyna, A., Pletenev, I., Trofimova, A., Mironov, A. A., Gelfand, M. S., & Khrameeva, E. E. (2020). Cumulative contact frequency of a chromatin region is an intrinsic property linked to its function. PeerJ, 8e9566. https://doi.org/10.7717/peerj.9566
Samborskaia, Margarita D, et al. "Cumulative contact frequency of a chromatin region is an intrinsic property linked to its function." PeerJ vol. 8 (2020): e9566. doi: https://doi.org/10.7717/peerj.9566
Samborskaia MD, Galitsyna A, Pletenev I, Trofimova A, Mironov AA, Gelfand MS, Khrameeva EE. Cumulative contact frequency of a chromatin region is an intrinsic property linked to its function. PeerJ. 2020 Aug 10;8:e9566. doi: 10.7717/peerj.9566. eCollection 2020. PMID: 32864204; PMCID: PMC7425636.
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A machine learning framework for the prediction of chromatin folding in .

PeerJ. Computer science

Rozenwald MB, Galitsyna AA, Sapunov GV, Khrameeva EE, Gelfand MS.
PMID: 33816958
PeerJ Comput Sci. 2020 Nov 30;6:e307. doi: 10.7717/peerj-cs.307. eCollection 2020.

Technological advances have lead to the creation of large epigenetic datasets, including information about DNA binding proteins and DNA spatial structure. Hi-C experiments have revealed that chromosomes are subdivided into sets of self-interacting domains called Topologically Associating Domains (TADs)....

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Rozenwald MB, Galitsyna AA, Sapunov GV, et al. A machine learning framework for the prediction of chromatin folding in . PeerJ Comput Sci. 2020;6:e307doi: 10.7717/peerj-cs.307.
Rozenwald, M. B., Galitsyna, A. A., Sapunov, G. V., Khrameeva, E. E., & Gelfand, M. S. (2020). A machine learning framework for the prediction of chromatin folding in . PeerJ. Computer science, 6e307. https://doi.org/10.7717/peerj-cs.307
Rozenwald, Michal B, et al. "A machine learning framework for the prediction of chromatin folding in ." PeerJ. Computer science vol. 6 (2020): e307. doi: https://doi.org/10.7717/peerj-cs.307
Rozenwald MB, Galitsyna AA, Sapunov GV, Khrameeva EE, Gelfand MS. A machine learning framework for the prediction of chromatin folding in . PeerJ Comput Sci. 2020 Nov 30;6:e307. doi: 10.7717/peerj-cs.307. eCollection 2020. PMID: 33816958; PMCID: PMC7924456.
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Perspectives for the reconstruction of 3D chromatin conformation using single cell Hi-C data.

PLoS computational biology

Kos PI, Galitsyna AA, Ulianov SV, Gelfand MS, Razin SV, Chertovich AV.
PMID: 34793453
PLoS Comput Biol. 2021 Nov 18;17(11):e1009546. doi: 10.1371/journal.pcbi.1009546. eCollection 2021 Nov.

Construction of chromosomes 3D models based on single cell Hi-C data constitute an important challenge. We present a reconstruction approach, DPDchrom, that incorporates basic knowledge whether the reconstructed conformation should be coil-like or globular and spring relaxation at contact...

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Kos PI, Galitsyna AA, Ulianov SV, et al. Perspectives for the reconstruction of 3D chromatin conformation using single cell Hi-C data. PLoS Comput Biol. 2021;17(11):e1009546doi: 10.1371/journal.pcbi.1009546.
Kos, P. I., Galitsyna, A. A., Ulianov, S. V., Gelfand, M. S., Razin, S. V., & Chertovich, A. V. (2021). Perspectives for the reconstruction of 3D chromatin conformation using single cell Hi-C data. PLoS computational biology, 17(11), e1009546. https://doi.org/10.1371/journal.pcbi.1009546
Kos, Pavel I, et al. "Perspectives for the reconstruction of 3D chromatin conformation using single cell Hi-C data." PLoS computational biology vol. 17,11 (2021): e1009546. doi: https://doi.org/10.1371/journal.pcbi.1009546
Kos PI, Galitsyna AA, Ulianov SV, Gelfand MS, Razin SV, Chertovich AV. Perspectives for the reconstruction of 3D chromatin conformation using single cell Hi-C data. PLoS Comput Biol. 2021 Nov 18;17(11):e1009546. doi: 10.1371/journal.pcbi.1009546. eCollection 2021 Nov. PMID: 34793453; PMCID: PMC8601426.
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Mitochondrial diseases caused by mtDNA mutations: a mini-review.

Therapeutics and clinical risk management

Ryzhkova AI, Sazonova MA, Sinyov VV, Galitsyna EV, Chicheva MM, Melnichenko AA, Grechko AV, Postnov AY, Orekhov AN, Shkurat TP.
PMID: 30349272
Ther Clin Risk Manag. 2018 Oct 09;14:1933-1942. doi: 10.2147/TCRM.S154863. eCollection 2018.

There are several types of mitochondrial cytopathies, which cause a set of disorders, arise as a result of mitochondria's failure. Mitochondria's functional disruption leads to development of physical, growing and cognitive disabilities and includes multiple organ pathologies, essentially disturbing...

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Ryzhkova AI, Sazonova MA, Sinyov VV, et al. Mitochondrial diseases caused by mtDNA mutations: a mini-review. Ther Clin Risk Manag. 2018;14:1933-1942doi: 10.2147/TCRM.S154863.
Ryzhkova, A. I., Sazonova, M. A., Sinyov, V. V., Galitsyna, E. V., Chicheva, M. M., Melnichenko, A. A., Grechko, A. V., Postnov, A. Y., Orekhov, A. N., & Shkurat, T. P. (2018). Mitochondrial diseases caused by mtDNA mutations: a mini-review. Therapeutics and clinical risk management, 141933-1942. https://doi.org/10.2147/TCRM.S154863
Ryzhkova, Anastasia I, et al. "Mitochondrial diseases caused by mtDNA mutations: a mini-review." Therapeutics and clinical risk management vol. 14 (2018): 1933-1942. doi: https://doi.org/10.2147/TCRM.S154863
Ryzhkova AI, Sazonova MA, Sinyov VV, Galitsyna EV, Chicheva MM, Melnichenko AA, Grechko AV, Postnov AY, Orekhov AN, Shkurat TP. Mitochondrial diseases caused by mtDNA mutations: a mini-review. Ther Clin Risk Manag. 2018 Oct 09;14:1933-1942. doi: 10.2147/TCRM.S154863. eCollection 2018. PMID: 30349272; PMCID: PMC6186303.
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RedChIP identifies noncoding RNAs associated with genomic sites occupied by Polycomb and CTCF proteins.

Proceedings of the National Academy of Sciences of the United States of America

Gavrilov AA, Sultanov RI, Magnitov MD, Galitsyna AA, Dashinimaev EB, Lieberman Aiden E, Razin SV.
PMID: 34969862
Proc Natl Acad Sci U S A. 2022 Jan 04;119(1). doi: 10.1073/pnas.2116222119.

Nuclear noncoding RNAs (ncRNAs) are key regulators of gene expression and chromatin organization. The progress in studying nuclear ncRNAs depends on the ability to identify the genome-wide spectrum of contacts of ncRNAs with chromatin. To address this question, a...

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Gavrilov AA, Sultanov RI, Magnitov MD, et al. RedChIP identifies noncoding RNAs associated with genomic sites occupied by Polycomb and CTCF proteins. Proc Natl Acad Sci U S A. 2022;119(1)doi: 10.1073/pnas.2116222119.
Gavrilov, A. A., Sultanov, R. I., Magnitov, M. D., Galitsyna, A. A., Dashinimaev, E. B., Lieberman Aiden, E., & Razin, S. V. (2022). RedChIP identifies noncoding RNAs associated with genomic sites occupied by Polycomb and CTCF proteins. Proceedings of the National Academy of Sciences of the United States of America, 119(1), . https://doi.org/10.1073/pnas.2116222119
Gavrilov, Alexey A, et al. "RedChIP identifies noncoding RNAs associated with genomic sites occupied by Polycomb and CTCF proteins." Proceedings of the National Academy of Sciences of the United States of America vol. 119,1 (2022). doi: https://doi.org/10.1073/pnas.2116222119
Gavrilov AA, Sultanov RI, Magnitov MD, Galitsyna AA, Dashinimaev EB, Lieberman Aiden E, Razin SV. RedChIP identifies noncoding RNAs associated with genomic sites occupied by Polycomb and CTCF proteins. Proc Natl Acad Sci U S A. 2022 Jan 04;119(1). doi: 10.1073/pnas.2116222119. PMID: 34969862.
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Showing 1 to 6 of 6 entries