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de novo peptide sequencing

De novo peptide sequencing refers to the process of determining the amino acid sequence of a peptide without prior knowledge of the DNA or protein it comes from. This technique is used in proteomics to analyze proteins and peptides, especially when the genomic sequence of the organism is unknown or the protein sequence is not available in databases.

The process typically involves mass spectrometry (MS), where peptides are ionized and fragmented. The mass spectrometer measures the masses of these peptide fragments. By analyzing the mass differences between the fragments, the machine learning model can infer the sequence of amino acids in the peptide.

This method is particularly useful for studying proteins from organisms with unsequenced genomes, post-translational modifications, and for discovering new proteins or variants.

Papers

Showing 1120 of 24 papers

TitleStatusHype
PGPointNovo: an efficient neural network-based tool for parallel de novo peptide sequencingCode0
Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencingCode1
Sequence-to-sequence translation from mass spectra to peptides with a transformer modelCode1
DPST: De Novo Peptide Sequencing with Amino-Acid-Aware TransformersCode0
DePS: An improved deep learning model for de novo peptide sequencing0
PepNet: A Fully Convolutional Neural Network for De novo Peptide SequencingCode1
Computationally instrument-resolution-independent de novo peptide sequencing for high-resolution devicesCode1
Uncovering Thousands of New Peptides with Sequence-Mask-Search Hybrid De Novo Peptide Sequencing FrameworkCode1
Improving the Results of De novo Peptide Identification via Tandem Mass Spectrometry Using a Genetic Programming-based Scoring Function for Re-ranking Peptide-Spectrum Matches0
pNovo 3: precise de novo peptide sequencing using a learning-to-rank frameworkCode0
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