PROSPECT: A web server for predicting protein histidine phosphorylation sites

iPhosH-PseAAC: Identify Phosphohistidine Sites in Proteins by Blending Statistical Moments and Position Relative Features According to the Chou's 5-Step Rule and General Pseudo Amino Acid Composition

(2019) Muhammad Awais et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics

Quokka: a comprehensive tool for rapid and accurate prediction of kinase family-specific phosphorylation sites in the human proteome

(2018) Fuyi Li et al.   BIOINFORMATICS

iFeature: a Python package and web server for features extraction and selection from protein and peptide sequences

(2018) Zhen Chen et al.   BIOINFORMATICS

Widespread bacterial protein histidine phosphorylation revealed by mass spectrometry-based proteomics

(2018) Clement M Potel et al.   NATURE METHODS

UniProt: the universal protein knowledgebase

(2018) The UniProt Consortium   NUCLEIC ACIDS RESEARCH

PhosphoPredict: A bioinformatics tool for prediction of human kinase-specific phosphorylation substrates and sites by integrating heterogeneous feature selection

(2017) Jiangning Song et al.   Scientific Reports

Monoclonal 1- and 3-Phosphohistidine Antibodies: New Tools to Study Histidine Phosphorylation

(2015) Stephen Rush Fuhs et al.   CELL

A pan-specific antibody for direct detection of protein histidine phosphorylation

(2013) Jung-Min Kee et al.   Nature Chemical Biology

Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources

(2009) Da Wei Huang et al.   Nature Protocols