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Single-molecule tracking dataset of histone H3 (Hht1) in Saccharomyces cerevisiae
Single-Molecule Tracking (SMT) is a powerful method to quantify protein dynamics in live cells. Recently, we have established a data analysis pipeline for estimating various biophysical parameters (mean squared displacement, diffusion coefficient, bound fraction, residence time, jump distances, jump...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9926182/ https://www.ncbi.nlm.nih.gov/pubmed/36798603 http://dx.doi.org/10.1016/j.dib.2023.108925 |
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author | Podh, Nitesh Kumar Das, Ayan Dey, Partha Paliwal, Sheetal Mehta, Gunjan |
author_facet | Podh, Nitesh Kumar Das, Ayan Dey, Partha Paliwal, Sheetal Mehta, Gunjan |
author_sort | Podh, Nitesh Kumar |
collection | PubMed |
description | Single-Molecule Tracking (SMT) is a powerful method to quantify protein dynamics in live cells. Recently, we have established a data analysis pipeline for estimating various biophysical parameters (mean squared displacement, diffusion coefficient, bound fraction, residence time, jump distances, jump angles, and track statistics) from the single-molecule time-lapse movies acquired from yeast Saccharomyces cerevisiae. We acquired the time-lapse movies using different time intervals (i.e. 15 ms, 200 ms, and 1000 ms) to extract the diffusion parameters (from 15 ms time interval movies) and residence time (from 200 ms and 1000 ms time interval movies). We tracked the single molecules from these movies using three MATLAB-based software packages (MatlabTrack, TrackIT, DiaTrack (Sojourner, and Spot-On)) to quantify various biophysical parameters. In this article, we have quantified the biophysical parameters of chromatin-bound histone H3 (Hht1), labeled using JF646 HaloTag Ligand (HTL), and shared a few raw time-lapse SMT movies for the same. Histone H3 is a chromatin-bound protein and it serves as a benchmark for the stably bound molecules for the SMT experiments. Hence, this dataset can be used by various researchers to quantify the biophysical parameters of chromatin-bound molecules (Histone H3). Any newly developed tracking software can use this dataset to validate the accuracy of its tracking algorithms. |
format | Online Article Text |
id | pubmed-9926182 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-99261822023-02-15 Single-molecule tracking dataset of histone H3 (Hht1) in Saccharomyces cerevisiae Podh, Nitesh Kumar Das, Ayan Dey, Partha Paliwal, Sheetal Mehta, Gunjan Data Brief Data Article Single-Molecule Tracking (SMT) is a powerful method to quantify protein dynamics in live cells. Recently, we have established a data analysis pipeline for estimating various biophysical parameters (mean squared displacement, diffusion coefficient, bound fraction, residence time, jump distances, jump angles, and track statistics) from the single-molecule time-lapse movies acquired from yeast Saccharomyces cerevisiae. We acquired the time-lapse movies using different time intervals (i.e. 15 ms, 200 ms, and 1000 ms) to extract the diffusion parameters (from 15 ms time interval movies) and residence time (from 200 ms and 1000 ms time interval movies). We tracked the single molecules from these movies using three MATLAB-based software packages (MatlabTrack, TrackIT, DiaTrack (Sojourner, and Spot-On)) to quantify various biophysical parameters. In this article, we have quantified the biophysical parameters of chromatin-bound histone H3 (Hht1), labeled using JF646 HaloTag Ligand (HTL), and shared a few raw time-lapse SMT movies for the same. Histone H3 is a chromatin-bound protein and it serves as a benchmark for the stably bound molecules for the SMT experiments. Hence, this dataset can be used by various researchers to quantify the biophysical parameters of chromatin-bound molecules (Histone H3). Any newly developed tracking software can use this dataset to validate the accuracy of its tracking algorithms. Elsevier 2023-01-25 /pmc/articles/PMC9926182/ /pubmed/36798603 http://dx.doi.org/10.1016/j.dib.2023.108925 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Podh, Nitesh Kumar Das, Ayan Dey, Partha Paliwal, Sheetal Mehta, Gunjan Single-molecule tracking dataset of histone H3 (Hht1) in Saccharomyces cerevisiae |
title | Single-molecule tracking dataset of histone H3 (Hht1) in Saccharomyces cerevisiae |
title_full | Single-molecule tracking dataset of histone H3 (Hht1) in Saccharomyces cerevisiae |
title_fullStr | Single-molecule tracking dataset of histone H3 (Hht1) in Saccharomyces cerevisiae |
title_full_unstemmed | Single-molecule tracking dataset of histone H3 (Hht1) in Saccharomyces cerevisiae |
title_short | Single-molecule tracking dataset of histone H3 (Hht1) in Saccharomyces cerevisiae |
title_sort | single-molecule tracking dataset of histone h3 (hht1) in saccharomyces cerevisiae |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9926182/ https://www.ncbi.nlm.nih.gov/pubmed/36798603 http://dx.doi.org/10.1016/j.dib.2023.108925 |
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