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AdaNovo: Adaptive \emph{De Novo} Peptide Sequencing with Conditional Mutual Information
March 13, 2024, 4:42 a.m. | Jun Xia, Shaorong Chen, Jingbo Zhou, Tianze Lin, Wenjie Du, Sizhe Liu, Stan Z. Li
cs.LG updates on arXiv.org arxiv.org
Abstract: Tandem mass spectrometry has played a pivotal role in advancing proteomics, enabling the analysis of protein composition in biological samples. Despite the development of various deep learning methods for identifying amino acid sequences (peptides) responsible for observed spectra, challenges persist in \emph{de novo} peptide sequencing. Firstly, prior methods struggle to identify amino acids with post-translational modifications (PTMs) due to their lower frequency in training data compared to canonical amino acids, further resulting in decreased peptide-level …
abstract acid analysis arxiv challenges cs.lg deep learning development enabling information pivotal protein proteomics q-bio.bm q-bio.qm responsible role samples sequencing type
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