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

Scripts used for the phosho data analysis

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

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

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

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.

Homology-controlled benchmark and lightweight explainable model for phosphosite prediction

A Network Dynamics Toolkit for Phosphorylation Cascades

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.