PHOsphoproteomic dissecTiOn using Networks
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Updated
Jan 25, 2021 - Python
PHOsphoproteomic dissecTiOn using Networks
Toolkit for concretely describing non-canonical DNA, RNA, and proteins
CWL workflow that facilitate performing a series of structural and phenotype related third party prediction methods starting from either a protein FASTA file or a list of Uniprot IDs. Integrated prediction methods refer to secondary structure, solvent accessibility, disordered regions, PTS modifications (phosphorylation, glycosylation, lipid mod…
This project is conduct research using deep learning to predict phosphorylation site in protein sequences
Model training for prot2vec-based phosphorylation site prediction
This code was written and used for statistical analysis and visualisation of data included in Drube et al. 2021.
Scripts used for the phosho data analysis
Algorithms for the generation of substitution matrices from intra-taxa variation data. Implemented and published on human genetic variation data.
Searching for Sulfotyrosines (sY) in a HA(pY)STACK
PhosphoFind provides functions to identify phosphorylation positions (aminoacid number in proteins) in phosphoproteomics experiments.
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