Upload dataset (part 00001-of-00002)
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README.md
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---
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language: en
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license: cc-by-4.0
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tags:
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- chemistry
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- biology
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computer time over the course of the project. This research was also
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supported in part by PLGrid Infrastructure (to PS). The authors thank Hera
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Vlamakis and Damian Plichta from the Broad Institute for helpful discussions.
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The work was supported by the Flatiron Institute as part of the Simons Foundation
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to J.K.L., P.D.R., V.G., D.B., C.C., A.P., N.C., I.F., and R.B. This research
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was also supported by grants NAWA PPN/PPO/2018/1/00014 to P.S. and T.K.,
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PLGrid to P.S., and NIH - DK043351 to T.V. and R.J.X.
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repo: https://github.com/microbiome-immunity-project/protein_universe
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citation_bibtex:
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}
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citation_apa: >-
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Koehler Leman, J., Szczerbiak, P., Renfrew, P. D., Gligorijevic, V., Berenberg,
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D., Vatanen, T., … Kosciolek, T. (2023). Sequence-structure-function relationships
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in the microbial protein universe. Nature Communications, 14(1), 2351.
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doi:10.1038/s41467-023-37896-w
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---
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# Microbiome Immunity Project: Protein Universe
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~200,000 predicted structures for diverse protein sequences from 1,003
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---
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language: en
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license: cc-by-4.0
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size_categories:
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- 100k<n<1M
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pretty_name: 'Microbiome Immunity Project: Protein Universe'
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tags:
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- chemistry
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- biology
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dataset_summary: ~200,000 predicted structures for diverse protein sequences from
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1,003 representative genomes across the microbial tree of life and annotate them
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functionally on a per-residue basis.
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dataset_description: Large-scale structure prediction on representative protein domains
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from the Genomic Encyclopedia of Bacteria and Archaea (GEBA1003) reference genome
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database across the microbial tree of life. From a non-redundant GEBA1003 gene catalog
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protein sequences without matches to any structural databases and which produced
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multiple-sequence alignments of N_eff > 16 and all putative novel domains between
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40 and 200 residues were extracted. For each sequence 20,000 Rosetta de novo models
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and up to 5 DMPfold models were generated. The initial output dataset (MIP_raw)
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of about 240,000 models were curated to high-quality models comprising about 75%
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of the original dataset (MIP_curated). Functional annotations of the entire dataset
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were created using structure-based Graph Convolutional Network embeddings from DeepFRI.
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acknowledgements: We kindly acknowledge the support of the IBM World Community Grid
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team (Caitlin Larkin, Juan A Hindo, Al Seippel, Erika Tuttle, Jonathan D Armstrong,
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Kevin Reed, Ray Johnson, and Viktors Berstis), and the community of 790,000 volunteers
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who donated 140,661 computational years since Aug 2017 of their computer time over
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the course of the project. This research was also supported in part by PLGrid Infrastructure
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(to PS). The authors thank Hera Vlamakis and Damian Plichta from the Broad Institute
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for helpful discussions. The work was supported by the Flatiron Institute as part
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of the Simons Foundation to J.K.L., P.D.R., V.G., D.B., C.C., A.P., N.C., I.F.,
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and R.B. This research was also supported by grants NAWA PPN/PPO/2018/1/00014 to
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P.S. and T.K., PLGrid to P.S., and NIH - DK043351 to T.V. and R.J.X.
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repo: https://github.com/microbiome-immunity-project/protein_universe
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citation_bibtex: "@article{KoehlerLeman2023,\n title = {Sequence-structure-function\
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\ relationships in the microbial protein universe},\n volume = {14},\n ISSN =\
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\ {2041-1723},\n url = {http://dx.doi.org/10.1038/s41467-023-37896-w},\n DOI =\
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\ {10.1038/s41467-023-37896-w},\n number = {1},\n journal = {Nature Communications},\n\
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\ publisher = {Springer Science and Business Media LLC},\n author = {Koehler Leman,\
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\ Julia and Szczerbiak, Pawel and Renfrew, P. Douglas and Gligorijevic, Vladimir\
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\ and Berenberg, Daniel and Vatanen, Tommi and Taylor, Bryn C. and Chandler,\
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\ Chris and Janssen, Stefan and Pataki, Andras and Carriero, Nick and Fisk,\
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\ Ian and Xavier, Ramnik J. and Knight, Rob and Bonneau, Richard and Kosciolek,\
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\ Tomasz},\n year = {2023},\n month = apr\n}"
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citation_apa: Koehler Leman, J., Szczerbiak, P., Renfrew, P. D., Gligorijevic, V.,
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Berenberg, D., Vatanen, T., … Kosciolek, T. (2023). Sequence-structure-function
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relationships in the microbial protein universe. Nature Communications, 14(1), 2351.
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doi:10.1038/s41467-023-37896-w
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dataset_info:
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features:
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- name: id
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dtype: string
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- name: pdb
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dtype: large_string
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- name: Filter_Stage2_aBefore
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dtype: float64
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- name: Filter_Stage2_bQuarter
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dtype: float64
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- name: Filter_Stage2_cHalf
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dtype: float64
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- name: Filter_Stage2_dEnd
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dtype: float64
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- name: clashes_bb
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dtype: float64
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- name: clashes_total
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dtype: float64
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- name: score
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dtype: float64
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- name: silent_score
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dtype: float64
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- name: time
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dtype: float64
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splits:
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- name: train
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num_bytes: 26606148779
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num_examples: 211069
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download_size: 9111920009
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dataset_size: 26606148779
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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---
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# Microbiome Immunity Project: Protein Universe
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~200,000 predicted structures for diverse protein sequences from 1,003
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data/train-00050-of-00054.parquet
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