Orca: Sequence-based modeling of genome 3D architecture from kilobase to chromosome-scale (Part1)

This dataset (Part 1) provide the core resource files required for using the code of Orca, including models and the hg38 reference genome (resources_core.tar.gz), and the micro-C mcool files required for extracting the experimental observations (resources_mcools.tar.gz). Orca is a sequence-based dee...

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Bibliographic Details
Main Author: Zhou, Jian
Format: Dataset
Language:unknown
Published: Zenodo 2022
Subjects:
Orca
Online Access:https://dx.doi.org/10.5281/zenodo.6234936
https://zenodo.org/record/6234936
id ftdatacite:10.5281/zenodo.6234936
record_format openpolar
spelling ftdatacite:10.5281/zenodo.6234936 2023-05-15T17:52:57+02:00 Orca: Sequence-based modeling of genome 3D architecture from kilobase to chromosome-scale (Part1) Zhou, Jian 2022 https://dx.doi.org/10.5281/zenodo.6234936 https://zenodo.org/record/6234936 unknown Zenodo https://dx.doi.org/10.5281/zenodo.4594206 Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess CC-BY Dataset dataset 2022 ftdatacite https://doi.org/10.5281/zenodo.6234936 https://doi.org/10.5281/zenodo.4594206 2022-03-10T15:20:58Z This dataset (Part 1) provide the core resource files required for using the code of Orca, including models and the hg38 reference genome (resources_core.tar.gz), and the micro-C mcool files required for extracting the experimental observations (resources_mcools.tar.gz). Orca is a sequence-based deep learning modeling framework for multiscale genome 3D architecture. Dataset Orca DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
description This dataset (Part 1) provide the core resource files required for using the code of Orca, including models and the hg38 reference genome (resources_core.tar.gz), and the micro-C mcool files required for extracting the experimental observations (resources_mcools.tar.gz). Orca is a sequence-based deep learning modeling framework for multiscale genome 3D architecture.
format Dataset
author Zhou, Jian
spellingShingle Zhou, Jian
Orca: Sequence-based modeling of genome 3D architecture from kilobase to chromosome-scale (Part1)
author_facet Zhou, Jian
author_sort Zhou, Jian
title Orca: Sequence-based modeling of genome 3D architecture from kilobase to chromosome-scale (Part1)
title_short Orca: Sequence-based modeling of genome 3D architecture from kilobase to chromosome-scale (Part1)
title_full Orca: Sequence-based modeling of genome 3D architecture from kilobase to chromosome-scale (Part1)
title_fullStr Orca: Sequence-based modeling of genome 3D architecture from kilobase to chromosome-scale (Part1)
title_full_unstemmed Orca: Sequence-based modeling of genome 3D architecture from kilobase to chromosome-scale (Part1)
title_sort orca: sequence-based modeling of genome 3d architecture from kilobase to chromosome-scale (part1)
publisher Zenodo
publishDate 2022
url https://dx.doi.org/10.5281/zenodo.6234936
https://zenodo.org/record/6234936
genre Orca
genre_facet Orca
op_relation https://dx.doi.org/10.5281/zenodo.4594206
op_rights Open Access
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
info:eu-repo/semantics/openAccess
op_rightsnorm CC-BY
op_doi https://doi.org/10.5281/zenodo.6234936
https://doi.org/10.5281/zenodo.4594206
_version_ 1766160717916930048

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