Research Highlights

Gene function prediction

• For many species, sequenced genomes are available
• However, for the majority of genes in those genomes, there is no experimental evidence for their function
• Based on sequence similarity, one can infer with reasonable accuracy the molecular function of a gene (as described by the MF category of the Gene Ontology)
• However, assigning biological processes (BP in Gene Ontology) is much more difficult based on sequence similarity only
• We have been working on methods to use additional data, in particular networks that describe relationships between genes

References:

Biological process annotation of proteins across the plant kingdom

Prioritization of candidate genes in QTL regions based on associations between traits and biological processes

A large-scale evaluation of computational protein function prediction

Gene Ontology consistent protein function prediction: the FALCON algorithm applied to six eukaryotic genomes

Genome-wide computational function prediction of Arabidopsis proteins by integration of multiple data sources

Bayesian Markov Random Field analysis for protein function prediction based on network data

Protein Interaction Site Prediction

• Sequence based prediction of interaction sites
• Applying various types of machine-learning approaches
• Comparison with sequence variation data
• Experimental validation

References:

Interactome-wide prediction of protein-protein binding sites reveals effects of protein sequence variation in Arabidopsis thaliana

Predicting the impact of alternative splicing on plant MADS domain protein function

SLIDER: a generic metaheuristic for the discovery of correlated motifs in protein-protein interaction networks

Mining Minimal Motif Pair Sets Maximally Covering Interactions in a Protein-Protein Interaction Network

Sequence motifs in MADS transcription factors responsible for specificity and diversification of protein-protein interaction

Predicting and understanding transcription factor interactions based on sequence level determinants of combinatorial control

Structural determinants of DNA recognition by plant MADS-domain transcription factors