Dealing with the data deluge
As technologies like next generation sequencing approach maturity, terms like "Big Data" are becoming increasingly anachronistic. Dealing with high volume data is now arguably a routine procedure in genomics research, our focus instead is on the analysis and interpretation of this experimental data. Our newly established, computational biology team has a truly multidisciplinary focus on genetic and genomic analysis for translational research and drug discovery. We are achieving this in close partnership with clinicians working on Cardiovascular, Immuno-inflammatory and Endocrine diseases at the William Harvey Research Institute (WHRI).
Towards genomic medicine
Much progress has already been made in understanding the genetic basis of disease, Genome wide association studies (GWAS) have identified common variants, while exome and whole genome resequencing studies are identifying rarer variants. A heterogeneous picture of common diseases is emerging, which argues for a highly integrative approach to help to apply these findings in the clinic. Firstly the overwhelming volume of data needs in-depth functional analysis to pinpoint putative functional variants with a rationale for involvement in disease. Pathway analysis can highlight common mechanisms among these disease variants, and more importantly identify targets that could be the focus of drug discovery or drug repositioning. Overall as a clearer picture of disease pathology emerges we may be able to stratify patients onto more effective therapies.
Defining New Therapeutic Opportunities
In addition to expertise in genomics, our team is experienced in the process of drug discovery and we can advise on target validation and evaluation of druggability. We are also working with clinical teams at the WHRI to identify new opportunities for drug repositioning to rapidly take existing drugs into the clinic for new indications.
Translation through partnership
Good computational biology is built on strong partnerships - this is the philosophy of our team. Just to name a few, we are partnering with Rheumatologists to use RNA-seq to study response to biologic therapy in Rheumatoid Arthritis, leading to new biomarkers for patient stratification. We are partnering with Cardiologists to build clinical databases that allow for the rapid recruitment of clinical trial cohorts by genotype or phenotype. We have taken a lead in partnerships spanning the computational chemistry and computational biology communities to build open access tools for drug discovery.
If you have a project that you think we could help with please get in touch. For more detail contact Dr Michael Barnes (firstname.lastname@example.org)