phosphorylation

The Kinase Library: a Global Atlas of the Human Protein Kinome

PHOsphoproteomic dissecTiOn using Networks

Toolkit for concretely describing non-canonical DNA, RNA, and proteins

This project is conduct research using deep learning to predict phosphorylation site in protein sequences

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…

Model training for prot2vec-based phosphorylation site prediction

Searching for Sulfotyrosines (sY) in a HA(pY)STACK

Scripts used for the phosho data analysis

This code was written and used for statistical analysis and visualisation of data included in Drube et al. 2021.

Homology-controlled benchmark and lightweight explainable model for phosphosite prediction

A modern Python implementation of NetPhorest for kinase–substrate prediction and phosphorylation crosstalk analysis.

Algorithms for the generation of substitution matrices from intra-taxa variation data. Implemented and published on human genetic variation data.

PhosphoFind provides functions to identify phosphorylation positions (aminoacid number in proteins) in phosphoproteomics experiments.

Interactive demo of LitePhospho — my first-author thesis model. Paste a protein sequence to predict phosphorylation sites (S/T/Y) with per-site explainability. Trained model served via ONNX.

A Network Dynamics Toolkit for Phosphorylation Cascades