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

• Main Author: Zhou, Jian (10336650)
• Format: Dataset
• Language: unknown
• Published: 2021
• Subjects: Genetics; Molecular Biology; Evolutionary Biology; Ecology; Marine Biology; Inorganic Chemistry; Biological Sciences not elsewhere classified; Information Systems not elsewhere classified; modeling framework; hg 38 reference genome; core resource files; genome 3 D architecture; micro-C mcool files; Orca; Sequence-based modeling
• Online Access: https://doi.org/10.5281/zenodo.4594207

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.