Chromatin image-driven modelling

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Standard

Chromatin image-driven modelling. / Kadlof, Michał; Banecki, Krzysztof; Chiliński, Mateusz; Plewczynski, Dariusz.

I: Methods, Bind 226, 2024, s. 54-60.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Kadlof, M, Banecki, K, Chiliński, M & Plewczynski, D 2024, 'Chromatin image-driven modelling', Methods, bind 226, s. 54-60. https://doi.org/10.1016/j.ymeth.2024.04.006

APA

Kadlof, M., Banecki, K., Chiliński, M., & Plewczynski, D. (2024). Chromatin image-driven modelling. Methods, 226, 54-60. https://doi.org/10.1016/j.ymeth.2024.04.006

Vancouver

Kadlof M, Banecki K, Chiliński M, Plewczynski D. Chromatin image-driven modelling. Methods. 2024;226:54-60. https://doi.org/10.1016/j.ymeth.2024.04.006

Author

Kadlof, Michał ; Banecki, Krzysztof ; Chiliński, Mateusz ; Plewczynski, Dariusz. / Chromatin image-driven modelling. I: Methods. 2024 ; Bind 226. s. 54-60.

Bibtex

@article{b1a715babd7d44bdbb9efcd6d5bf6c06,

title = "Chromatin image-driven modelling",

abstract = "The challenge of modelling the spatial conformation of chromatin remains an open problem. While multiple data-driven approaches have been proposed, each has limitations. This work introduces two image-driven modelling methods based on the Molecular Dynamics Flexible Fitting (MDFF) approach: the force method and the correlational method. Both methods have already been used successfully in protein modelling. We propose a novel way to employ them for building chromatin models directly from 3D images. This approach is termed image-driven modelling. Additionally, we introduce the initial structure generator, a tool designed to generate optimal starting structures for the proposed algorithms. The methods are versatile and can be applied to various data types, with minor modifications to accommodate new generation imaging techniques.",

author = "Micha{\l} Kadlof and Krzysztof Banecki and Mateusz Chili{\'n}ski and Dariusz Plewczynski",

note = "Publisher Copyright: {\textcopyright} 2024 The Authors",

year = "2024",

doi = "10.1016/j.ymeth.2024.04.006",

language = "English",

volume = "226",

pages = "54--60",

journal = "Methods",

issn = "1046-2023",

publisher = "Academic Press",

}

RIS

TY - JOUR

T1 - Chromatin image-driven modelling

AU - Kadlof, Michał

AU - Banecki, Krzysztof

AU - Chiliński, Mateusz

AU - Plewczynski, Dariusz

PY - 2024

Y1 - 2024

N2 - The challenge of modelling the spatial conformation of chromatin remains an open problem. While multiple data-driven approaches have been proposed, each has limitations. This work introduces two image-driven modelling methods based on the Molecular Dynamics Flexible Fitting (MDFF) approach: the force method and the correlational method. Both methods have already been used successfully in protein modelling. We propose a novel way to employ them for building chromatin models directly from 3D images. This approach is termed image-driven modelling. Additionally, we introduce the initial structure generator, a tool designed to generate optimal starting structures for the proposed algorithms. The methods are versatile and can be applied to various data types, with minor modifications to accommodate new generation imaging techniques.

AB - The challenge of modelling the spatial conformation of chromatin remains an open problem. While multiple data-driven approaches have been proposed, each has limitations. This work introduces two image-driven modelling methods based on the Molecular Dynamics Flexible Fitting (MDFF) approach: the force method and the correlational method. Both methods have already been used successfully in protein modelling. We propose a novel way to employ them for building chromatin models directly from 3D images. This approach is termed image-driven modelling. Additionally, we introduce the initial structure generator, a tool designed to generate optimal starting structures for the proposed algorithms. The methods are versatile and can be applied to various data types, with minor modifications to accommodate new generation imaging techniques.

U2 - 10.1016/j.ymeth.2024.04.006

DO - 10.1016/j.ymeth.2024.04.006

M3 - Journal article

C2 - 38636797

AN - SCOPUS:85190426439

VL - 226

SP - 54

EP - 60

JO - Methods

JF - Methods

SN - 1046-2023

ER -

ID: 389422482

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