ProteomicsML: An Online Platform for Community-Curated Data sets and Tutorials for Machine Learning in Proteomics

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 occur between raw data and machine learning-ready data. Since
predictive proteomics is an emerging field, when predicting peptide
behavior in LC-MS setups, each lab often uses unique and complex data
processing pipelines in order to maximize performance, at the cost
of accessibility and reproducibility. For this reason we introduce
ProteomicsML, an online resource for proteomics-based data sets and
tutorials across most of the currently explored physicochemical peptide
properties. This community-driven resource makes it simple to access
data in easy-to-process formats, and contains easy-to-follow tutorials
that allow new users to interact with even the most advanced algorithms
in the field. ProteomicsML provides data sets that are useful for
comparing state-of-the-art machine learning algorithms, as well as
providing introductory material for teachers and newcomers to the
field alike. The platform is freely available at https://www.proteomicsml.org/, and we welcome the entire proteomics community to contribute to
the project at https://github.com/ProteomicsML/ProteomicsML.