DeepIso: A Deep Learning Model for Peptide Feature Detection from LC-MS map
نویسندگان
چکیده
منابع مشابه
DeepIso: A Deep Learning Model for Peptide Feature Detection
Liquid chromatography with tandem mass spectrometry (LC-MS/MS) based proteomics is a well-established research field with major applications such as identification of disease biomarkers, drug discovery, drug design and development. In proteomics, protein identification and quantification is a fundamental task, which is done by first enzymatically digesting it into peptides, and then analyzing p...
متن کاملMelanoma detection with a deep learning model
Background: Skin cancer is one of the most common forms of cancer in the world and melanoma is the deadliest type of skin cancer. Both melanoma and melanocytic nevi begin in melanocytes (cells that produce melanin). However, melanocytic nevi are benign whereas melanoma is malignant. This work proposes a deep learning model for classification of these two lesions. Methods: In this analytic s...
متن کاملA Report on Finding a New Peptide Aldehyde from Cyanobacterium Nostoc sp. Bahar M by LC-MS and Marfey’s Analysis
Background: Cyanobacteria have a worldwide distribution in the terrestrial habitats, occurring predominantly on the surface of the soils, stones, rocks, and trees, practically in moist, neutral or alkaline aeries. The unique natural and bioactive compounds from cyanobacteria with various biological activities and an extensive range of chemical classes have a significant capabil...
متن کاملBPDA2d — A 2D global optimization based Bayesian peptide detection algorithm for LC-MS
Motivation: Peptide detection is a crucial step in mass spectrometry (MS) based proteomics. Most existing algorithms are based upon greedy isotope template matching and thus may be prone to error propagation and ineffective to detect overlapping peptides. In addition, existing algorithms usually work at different charge states separately, isolating useful information that can be drawn from othe...
متن کاملDeltAMT: a statistical algorithm for fast detection of protein modifications from LC-MS/MS data.
Identification of proteins and their modifications via liquid chromatography-tandem mass spectrometry is an important task for the field of proteomics. However, because of the complexity of tandem mass spectra, the majority of the spectra cannot be identified. The presence of unanticipated protein modifications is among the major reasons for the low spectral identification rate. The conventiona...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Scientific Reports
سال: 2019
ISSN: 2045-2322
DOI: 10.1038/s41598-019-52954-4