SMSNet

algorithm · CNN + RNN

SMSNet: algorithm · CNN + RNN. Sequence-Mask-Search seq2seq

Sequence-Mask-Search seq2seq

Kind	algorithm
Deep learning	yes
Acquisition	DDA
Family	CNN + RNN

Code

• https://github.com/cmb-chula/SMSNet

Live stars, open issues and last-push figures are on the Code activity chart.

Benchmarks

• denovo_benchmarks: median peptide-level average precision 0.602 over 86 datasets, median rank 10 of 14 (version bm-1.0.0).

Both are mass-based matches on the tool’s most recent run. What these numbers mean.

Papers describing it (2)

• Uncovering thousands of new HLA antigens and phosphopeptides with deep learning-based sequence-mask-search de novo peptide sequencing framework (2019, bioRxiv, preprint)
• Uncovering Thousands of New Peptides with Sequence-Mask-Search Hybrid De Novo Peptide Sequencing Framework (2019, Molecular & Cellular Proteomics, peer-reviewed)

Papers using it (4)

Applications and evaluations that ran this method. They are not counted among its authors below.

• Identification of Daboia siamensis venome using integrated multi-omics data (2022, Scientific Reports, peer-reviewed)
• Combined proteomic strategies for in-depth venomic analysis of the beaked sea snake (Hydrophis schistosus) from Songkhla Lake, Thailand (2022, Journal of Proteomics, peer-reviewed)
• Unsupervised Mining of HLA-I Peptidomes Reveals New Binding Motifs and Potential False Positives in the Community Database (2022, Frontiers in Immunology, peer-reviewed)
• Unsupervised mining of HLA-I peptidomes reveals new binding motifs and substantial false positives in community database (2021, bioRxiv, preprint)

Authors (5)

Korrawe Karunratanakul, Hsin-Yao Tang, David W. Speicher, Ekapol Chuangsuwanich, Sira Sriswasdi

Seen in the charts

• The architectures
• Code activity
• Models and the authors behind them

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