Cargando…
ProteomicsML: An Online Platform for Community-Curated Data sets and Tutorials for Machine Learning in Proteomics
[Image: see text] Data set acquisition and curation are often the most difficult and time-consuming parts of a machine learning endeavor. This is especially true for proteomics-based liquid chromatography (LC) coupled to mass spectrometry (MS) data sets, due to the high levels of data reduction that...
Autores principales: | Rehfeldt, Tobias G., Gabriels, Ralf, Bouwmeester, Robbin, Gessulat, Siegfried, Neely, Benjamin A., Palmblad, Magnus, Perez-Riverol, Yasset, Schmidt, Tobias, Vizcaíno, Juan Antonio, Deutsch, Eric W. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
|
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9903315/ https://www.ncbi.nlm.nih.gov/pubmed/36693629 http://dx.doi.org/10.1021/acs.jproteome.2c00629 |
Ejemplares similares
-
Toward an
Integrated Machine Learning Model of a Proteomics
Experiment
por: Neely, Benjamin A., et al.
Publicado: (2023) -
Future Prospects of Spectral Clustering Approaches in Proteomics
por: Perez‐Riverol, Yasset, et al.
Publicado: (2018) -
Making proteomics data accessible and reusable: Current state of proteomics databases and repositories
por: Perez-Riverol, Yasset, et al.
Publicado: (2015) -
The mzIdentML Data Standard Version 1.2, Supporting Advances in Proteome Informatics
por: Vizcaíno, Juan Antonio, et al.
Publicado: (2017) -
ms-data-core-api: an open-source, metadata-oriented library for computational proteomics
por: Perez-Riverol, Yasset, et al.
Publicado: (2015)