Ph.D., University of Minnesota, 2003
firstname.lastname@example.org | 516-422-4123
Next generation sequencing technologies revolutionized many areas of genetics and molecular biology, enabling quantitative analyses of the entire genomes and paving the way for Personalized Medicine. We develop novel statistical methods and computational algorithms for multi-omics processing and integration, and leverage Big Genomic Data to elucidate various problems in precision health, such as genetic and epigenetic mechanisms of cancer development and progression, and clinical impact of functional variants.
Advancements in high-throughput sequencing technologies resulted in an explosive growth of multi-omics data. While presenting a tremendous opportunity for quantitative studies of numerous biological processes, crucial for both fundamental research and clinical applications, it also created a set of unique bioinformatics challenges for processing, integrating and interpreting of the vast amounts of data.
Dr. Alexander Dobin and colleagues are biological data scientists working to resolve these challenging via developing of highly efficient and accurate algorithms, such as STAR, the popular RNA-seq analysis software used by thousands of researchers worldwide. We are conceiving novel computational approaches to process data from emerging sequencing technologies, such as single-cell RNA-seq and long read nanopore sequencing, with a special emphasis on detecting RNA and DNA aberrations in tumors.
Another exciting research area in our group is functional annotation of the non-coding genome via integration of multi-omics data generated by ENCODE, Roadmap Epigenomics and GTeX consortia, essential for deciphering of gene regulation mechanisms, interpretation of disease associated variants in GWAS studies, and understanding epigenetic effects in cancer biology.
Alexander Dobin dives into genomic data
June 8, 2018
Alexander Dobin joins the faculty as its newest assistant professor, working on the computational side of genomics research