16757b78830968bb3fc9 · UniSpec: Deep Learning for Predicting the Full Range of Peptide Fragment Ion Series to Enhance the Proteomics Data Analysis Workflow
UniSpec: Deep Learning for Predicting the Full Range of Peptide Fragment Ion Series to Enhance the Proteomics Data Analysis Workflow
We present UniSpec, an attention-driven deep neural network designed to predict comprehensive collision-induced fragmentation spectra, thereby improving peptide identification in shotgun proteomics. Utilizing a training data set of 1.8 million unique high
{
"title_en": "UniSpec: Deep Learning for Predicting the Full Range of Peptide Fragment Ion Series to Enhance the Proteomics Data Analysis Workflow",
"designation": "",
"series": "",
"status": "",
"date": "2024-02-08",
"date_original": "February 8, 2024",
"url": "https://www.nist.gov/publications/unispec-deep-learning-predicting-full-range-peptide-fragment-ion-series-enhance",
"source": "NIST Publications",
"display_en": "",
"authors_en": "Joel Lapin, Xinjian (Eric) Yan , Qian Dong",
"abstract_excerpt_en": "We present UniSpec, an attention-driven deep neural network designed to predict comprehensive collision-induced fragmentation spectra, thereby improving peptide identification in shotgun proteomics. Utilizing a training data set of 1.8 million unique high",
"id": "16757b78830968bb3fc9",
"sources": [
"NIST Publications"
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{
"title_en": "UniSpec: Deep Learning for Predicting the Full Range of Peptide Fragment Ion Series to Enhance the Proteomics Data Analysis Workflow",
"designation": "",
"series": "",
"status": "",
"date": "2024-02-08",
"date_original": "February 8, 2024",
"url": "https://www.nist.gov/publications/unispec-deep-learning-predicting-full-range-peptide-fragment-ion-series-enhance",
"source": "NIST Publications",
"display_en": "",
"authors_en": "Joel Lapin, Xinjian (Eric) Yan , Qian Dong",
"abstract_excerpt_en": "We present UniSpec, an attention-driven deep neural network designed to predict comprehensive collision-induced fragmentation spectra, thereby improving peptide identification in shotgun proteomics. Utilizing a training data set of 1.8 million unique high"
}
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