https://github.com/beam-labs/contranovo
공식 코드ContraNovo: A Contrastive Learning Approach to Enhance De Novo Peptide Sequencing
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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.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
ContraNovo: A Contrastive Learning Approach to Enhance De Novo Peptide Sequencing
Universal Biological Sequence Reranking for Improved De Novo Peptide Sequencing
Transformer-based de novo peptide sequencing for data-independent acquisition mass spectrometry
Transformer-based de novo peptide sequencing for data-independent acquisition mass spectrometry
Transformer-based de novo peptide sequencing for data-independent acquisition mass spectrometry
Disentangling the Complex Multiplexed DIA Spectra in De Novo Peptide Sequencing
DeepNovoV2: Better de novo peptide sequencing with deep learning
DPST: De Novo Peptide Sequencing with Amino-Acid-Aware Transformers
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.