cpanse / 2023-EuBIC-MS-proc

Proceedings EuBIC-MS dev meeting 2023 (JPROT-D-24-00190)
https://doi.org/10.1016/j.jprot.2024.105246
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The description of hackathons could be more homogeneous #4

Closed cpanse closed 3 months ago

cpanse commented 3 months ago

The description of hackathons could be more homogeneous. Even though the writing may closely derive from an abstract written by a different author/organizer, it should have a common section each time: e.g. a small indication on the progress of the project during the meeting. This could help the reader understand the possibilities offered by this kind of session.

mmattano commented 3 months ago

For the metabolomics hackathon you can add

During this hackathon, different spectral similarity scoring functions were compared and their target and off-target scores were evaluated based on similarity of the compounds.

brvpuyve commented 3 months ago

Input for the hackathon of Tim Van Den Bossche: During the hackathon, we developed a prototype tool named Pathway Pilot. This tool features a user-friendly interface designed for exploring and visualizing metabolic pathways identified in metaproteomic samples.

MatthewThe commented 3 months ago

For the interactive HTML plots:

During the hackathon, five teams employed pair programming techniques to each develop a new component for a fundamental plot type: histogram, bar plot, swarm plot, violin plot, and line plot. Each team successfully produced a functional component, complete with customization options and unit tests. These components are now available from the node package manager (npm) as part of the @biowc organization.

di-hardt commented 3 months ago

For Rusteomics:

During the hackathon the participants build the basis for a community driven mass-spectrometry based proteomics framework written in Rust, starting with prototypes for a spectral library writer and a FASTA reader, including easy to use Python bindings.

LLautenbacher commented 3 months ago

During the hackathon we established the framework of the model hosting platform and started adding multiple popular machine learning models. Including Prosit, AlphaPeptDeep, MS2PIP and DeepLC.