We are currently witnessing a deep knowledge revolution due to the availability of exponentially expanding DNA sequence databases. This is made possible by the continuous acceleration of DNA sequencing throughput. Sequencing data is accumulating faster than Moore’s Law, bringing fundamental new insights, conjecture, and understanding, with impacts in medicine, agronomy and ecology.
GenScale is a bioinformatics research team. Its main goal is to develop scalable methods, tools, and software forprocessing genomic data.
Our research is motivated by the fast development of next-generation sequencing (NGS) and third generation (TGS) technologies that provide very challenging problems both in terms of bioinformatics and computer sciences.
GenScale research is organized along four main axes:
- Data structures
- Indexing the mass of genomic data
- Focus on the de-Bruijn graph structure.
- Provide end-user and optimized library
- Optimized (time and memory) tools dedicated to NGS processing
- Data compression, genome assembly, variant detection, metagenomics, GWAS (genome-wide association Study)
- Combine several levels of parallelism
- Use existing techniques as multithreading or MapReduce
- Constrained algorithmic development, in particular, targeting hardware accelerators
- Participate in biology-oriented projects
- Inra, CEA, National Museum, Hospitals, …