Welcome to the NIMFFAB Bioinformatics Laboratory
Following recent advances in technology and the development of ultra high-throughput research, the field of biotechnology is beginning to suffer from data overload, and thus, applications of Bioinformatics & Computational Biology have expanded with these so-called '-omics' technologies (Genomics, Transcriptomics, Proteomics, Metabolomics). This discipline now sits as an umbrella over biotechnology. NIMFFAB is engaged in analyzing such large-scale sequence data, developing novel computational tools / algorithms and incorporating them into bioinformatics resources / databases. NIMFFAB is located on the first floor of OSU's new establishment, the Henry Bellmon Research Center.
National Institute for Microbial Forensics & Food and Agricultural Biosecurity (NIMFFAB) is, a coalition of National and State investigators conducting research on crop and food biosecurity and forensics issues. NIMFFAB assess current National capabilities for microbial forensics as related to plant pathogens and food safety and provides strategic planning, a long-range vision and prioritization of needs and resources related to plant and food-related microbial forensics and agricultural biosecurity.
Our bioinformatics research interests span a range of topics in applying statistical pattern recognition, artificial intelligence and machine learning technologies in the area of agricultural biosecurity, metagenomics, regulatory mechanisms of gene expression, genome-wide host-pathogen interaction networks and genome annotation for functional studies. Through collaborations NIMFFAB developed bioinformatics tools that are useful within the real biological situations. These include algorithms for pathogen detection and discrimination, identification of species-specific signatures, and using artificial intelligence to predict biosecurity threats. For example, discriminating pathogen genotypes in a fundamentally different way from distance-based and BLAST algorithms and instead, using the Neural Networks, Support Vector Machine or Decision Tree classifiers to build patterns from genome regions (e.g. DNA barcodes) that are under selective pressure; and ultimately incorporating them into a database(s) / visualization tool(s).
Our lab has active collaborations with the Samuel Roberts Noble Foundation, located in Ardmore (OK), focusing on basic plant biology research aimed at software development in computational biology, bioinformatics and genomics for biological discovery.