RESEARCH

Development of SNPstar 2.0 and computational prediction of putative proteoform candidates with high functional proteoform variation

Project D02 focuses on genomic research, aiming to develop a web-based tool, SNPstar 2.0, for the prediction of proteoforms with high functional variation utilizing pangenome data. SNPstar 2.0 will incorporate three-dimensional structural models and highlight amino acid residues affected by nsSNPs. It will also extend to a variety of plant species. The project will create a quantitative score to predict SNPs’ functional impact on proteoform structure and function. This initiative supports the CRC by providing computational predictions of SNP effects on proteoform structure and function, integrating both primary sequences as well as structural information from project D01. Additionally, D02 will serve as a data platform for the consortium, generating scientific resources for future CRC development.

Specifically, this includes developing SNPstar 2.0 and predicting proteoform candidates; developing a Plant Pangenome Browser for constructing, visualizing, and analyzing pangenomes of various plants, and creating bioinformatics and machine learning approaches for analyzing orthology relationships, integrating sequence and 3D-structure data to predict functionally modified proteoforms, and elucidating the effects of non-coding SNPs using diverse omics data.