Dataset: FASTA file of protein identifications from R/V Kilo Moana KM1128 in the North Pacific during 2011 (MetZyme project)

Final no updates expectedVersion 1 (2017-07-14)Dataset Type:Cruise Results

Principal Investigator: Mak A. Saito (Woods Hole Oceanographic Institution)

BCO-DMO Data Manager: Hannah Ake (Woods Hole Oceanographic Institution)

BCO-DMO Data Manager: Amber D. York (Woods Hole Oceanographic Institution)

Program: U.S. GEOTRACES (U.S. GEOTRACES)

Project: Connecting Trace Elements and Metalloenzymes Across Marine Biogeochemical Gradients (GPc03) (MetZyme)

Abstract

FASTA file of protein identifications from the KM1128 in 2011. There is one entry for every protein ID.

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These data are part of the Ocean Protein Portal "MetZyme 0.2" dataset version 5 (https://proteinportal.whoi.edu/; Saito et al., 2020).

Related Datasets

IsRelatedTo
Dataset: https://proteinportal.whoi.edu/
Protein Portal (2024). Ocean Protein Portal. Available from https://proteinportal.whoi.edu/
IsRelatedTo
Dataset: Station locations
Relationship Description: Station locations and sampling information for these data.
Saito, M. (2019) Station locations for the global metaproteomic dataset from R/V Kilo Moana cruise KM1128, the METZYME expedition in the tropical North Pacific in 2011. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 3) Version Date 2019-04-12 doi:10.1575/1912/bco-dmo.730891.3
IsRelatedTo
Dataset: Peptide spectral counts (MetZyme 0.2)
Relationship Description: Related peptides and their spectral counts. This dataset is part of the same "MetZyme 0.2" dataset at the Ocean Protein Portal (https://proteinportal.whoi.edu/).
Saito, M. A. (2021) Peptides and their spectral counts from KM1128 the METZYME expedition on R/V Kilo Moana in the tropical North Pacific in 2011. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 4) Version Date 2021-03-30 http://lod.bco-dmo.org/id/dataset/731314
IsRelatedTo
Dataset: Total spectral count of proteins (MetZyme 0.2)
Relationship Description: This dataset is part of the same "MetZyme 0.2" dataset at the Ocean Protein Portal (https://proteinportal.whoi.edu/).
Saito, M. A. (2022) Total spectral count of proteins from R/V Kilo Moana cruise KM1128 for the METZYME expedition in the tropical North Pacific in 2011. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 5) Version Date 2022-07-06 http://lod.bco-dmo.org/id/dataset/730722

Related Publications

Methods
Saito, M. A., Bertrand, E. M., Duffy, M. E., Gaylord, D. A., Held, N. A., Hervey, W. J., Hettich, R. L., Jagtap, P. D., Janech, M. G., Kinkade, D. B., Leary, D. H., McIlvin, M. R., Moore, E. K., Morris, R. M., Neely, B. A., Nunn, B. L., Saunders, J. K., Shepherd, A. I., Symmonds, N. I., & Walsh, D. A. (2019). Progress and Challenges in Ocean Metaproteomics and Proposed Best Practices for Data Sharing. Journal of Proteome Research, 18(4), 1461–1476. https://doi.org/10.1021/acs.jproteome.8b00761
Related Research
Saito, M. A., Saunders, J. K., Chagnon, M., Gaylord, D. A., Shepherd, A., Held, N. A., Dupont, C., Symmonds, N., York, A., Charron, M., & Kinkade, D. B. (2020). Development of an Ocean Protein Portal for Interactive Discovery and Education. Journal of Proteome Research, 20(1), 326–336. https://doi.org/10.1021/acs.jproteome.0c00382

Saito, M. A. (2017) FASTA file of protein identifications from R/V Kilo Moana KM1128 in the North Pacific during 2011 (MetZyme project). Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2017-07-14 [if applicable, indicate subset used]. http://lod.bco-dmo.org/id/dataset/708816 [access date]

Terms of Use

This dataset is licensed under Creative Commons Attribution 4.0.


If you wish to use this dataset, it is highly recommended that you contact the original principal investigators (PI). Should the relevant PI be unavailable, please contact BCO-DMO (info@bco-dmo.org) for additional guidance. For general guidance please see the BCO-DMO Terms of Use document.

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Funded by the U.S. National Science Foundation