ArticleAnalytical chemistry2025
Collisional Cross-Section Prediction for Multiconformational Peptide Ions with IM2Deep.
Article in Analytical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Instrument-Software Synergy in Proteomics: Systematic Evaluation across Mass Spectrometry Platforms, Search Engines, and Rescoring Methods.Journal of proteome research · 2026Article
- Bimodal Peptide Collision Cross Section Distribution Reflects Two Stable Conformations in the Gas Phase.Journal of proteome research · 2026Article
- Carafe2 enables high qualitybioRxiv : the preprint server for biology · 2026Article
- Unlocking the Next Decade of Proteomics with Standardized, Structured Metadata.Journal of proteome research · 2026Review
- Perspectives in computational mass spectrometry: recent developments and key challenges.Bioinformatics advances · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
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Abstract
Peptide collisional cross-section (CCS) prediction is complicated by the tendency of peptide ions to exhibit multiple conformations in the gas phase. This adds further complexity to downstream analysis of proteomics data, for example for identification or quantification through feature finding. Here, we present an improved version of IM2Deep that is trained on a carefully curated data set to predict CCS values of multiconformational peptides. The training data is derived from a large and comprehensive set of publicly available data sets. This comprehensive training data set together with a tailored architecture allows for the accurate CCS prediction of multiple peptide conformational states. Furthermore, the enhanced IM2Deep model also retains high precision for peptides with a single observed conformation. IM2Deep is publicly available under a permissive open-source license at https://github.com/compomics/IM2Deep.
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Registered trials
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