KiNext

KiNext identifies and classifies conventional eukaryotic protein kinases (ePKs) and atypical protein kinases (aPKs) from predicted proteomes using Hidden Markov Models (HMMs) in a reproducible Nextflow workflow.

Key Features:

• Kinase Identification: Detects both conventional eukaryotic protein kinases (ePKs) and atypical protein kinases (aPKs) using HMMs generated from catalytic kinase domains.
• Kinase Classification: Categorizes ePKs into eight kinase groups using dedicated HMMs tailored for each group.
• Reproducible Workflow: Implements a FAIR-compliant Nextflow pipeline ensuring traceability and reproducibility of results.
• Customizable HMM Models: Includes default HMM models optimized for eukaryotes with the capability to incorporate HMM models for other taxa.

Scientific Applications:

• Kinome Characterization: Determines the complete complement of protein kinases in an organism to understand physiological capabilities, limitations, and environmental adaptations.
• Comparative Kinomics: Enables examination and comparison of kinomes across diverse organisms using increasingly available genome data.
• Marine Species Validation: Identified previously unidentified kinases and classified previously unclassified kinases in Crassostrea gigas and Ostreococcus tauri.

Methodology:

KiNext uses Hidden Markov Models (HMMs) generated from catalytic domains of kinases to identify ePKs and aPKs, then applies group-specific HMMs to classify ePKs into eight kinase groups.