Computational Genomics uses the latest sequencing technology and advanced computational methods to study problems in biology and human health, including how genes cause disease, how genomes evolve, and how gene expression changes in response to different conditions within the cell. Bridging the fields of biomedical engineering, computer science, biology, and biostatistics, computational genomicists are designing novel algorithms that can handle the enormous data sets generated by modern sequencing experiments.
The DNA sequencing revolution has allowed us to sequence the genomes of thousands of living species, generating enormous data sets with billions of reads. We develop novel genome assembly methods that can reconstruct genomes from the latest sequencing technologies. Our genome projects range from tiny bacteria to enormous plant genomes.
Researchers are developing computational methods for synthetic biology in order to design new biological assemblies. With better characterization of genetic elements and new tools like CRISPR-Cas9 for genomic and epigenomic editing, researchers are deciphering the principles behind genetic regulation and co-opting them to design yeast cells with fully synthetic DNA.
Transcriptomics and RNA Sequencing
RNA sequencing allows researchers to capture a snapshot of all active genes in a cell, allowing them to develop efficient computational methods to transform the data into accurate readouts of gene activity, and to compare gene expression across many tissues and conditions.
Each person carries many rare genetic variants that may have a significant impact on his or her health. Predicting which of these variants are likely to be harmful is of great interest to researchers, who are developing new methods for integrating genomic and transcriptomic data.