Transforming MEGA for Big Data Molecular Phylogenetics
- Institution
- Temple University, PA
- Principal investigator
- Sudhir Kumar
- Funding
- $1.5M
- Duration
- 2025–2028
Moonbase score
Still being scored
Abstract
An award is made to Temple University to support transforming the Molecular Evolutionary Genetics Analysis (MEGA) software into a next-generation platform for analyzing large datasets in molecular evolution and phylogenetics. MEGA has long supported scientists in many areas of the life sciences, from biodiversity to biomedicine, by providing powerful tools for DNA and protein sequence analysis through user-friendly interfaces. The improved MEGA will enhance this support by significantly lowering the memory and processing requirements needed to analyze large, complex genomic datasets, making advanced computing more practical on personal desktops and accessible to a broader range of researchers and students. The project will also create MEGA-based educational modules for college and high school classrooms to boost participation in STEM and improve scientific literacy. The project will advance bioinformatics by developing new algorithms for big data analysis and enhancing the software’s architecture for faster parallel processing and improved memory utilization. These advancements will enable researchers to perform accurate evolutionary analyses of large biological datasets, which are becoming increasingly common due to lower DNA sequencing costs and the rapid growth of databases. The project’s success will be judged by improvements in computational efficiency, increased software adoption across diverse computing environments, a higher number of citations, and broader use in various biological fields. Ultimately, the upgraded MEGA will be a scalable, efficient, and user-friendly tool for phylogenomics, while also promoting environmentally sustainable computing practices. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Research team
- Sudhir KumarPI
- Caryn Babaian
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