Translational Biomolecular Informatics

DBMI faculty members focus on understanding and communicating the molecular consequences of sequence variation and or downstream biomolecular gene products and metabolic products from a plethora of informatics-based research angles.

• In rare disease genetics, our faculty are focusing on finding structural variants (Quinlan), precision medicine from Omics data (Lussier, Quinlan), Single-Subject Studies of rare and infrequent disorders (Lussier), sequence Ontology (Eilbeck), synergistic and antagonistic interactions of non-coding variants (Lussier), functional Convergence of non-coding variants for drug-repositioning and discovery of new clinical syndromes (Lussier), and predicting impact of variation from protein structure simulation (Facelli).

• The Quinlan group has used the underlying strength in rare disease genetics to pivot to precision oncology, building on strengths to evaluate tumor heterogeneity.

• The Eilbeck lab is working with the state health department to improve newborn screening with secondary genomic panel testing and is exploring standards-based communication of genetic data to parents and physicians. Dr. Eilbeck also engages in the international standards community – overseeing the Sequence Ontology and co-directing the GA4GH sequence Annotation Group. The faculty in this group excel at collaborative partnerships both internally at the U and externally at a national level.

• The Lussier group has demonstrated the reduction of clinical trial cohort size by a factor of five- to ten-fold for analyzing statistically powered studies by conducting meta-analyses of single-subject responses to therapy of stimulus rather than conventional cross-subject studies

• The Ilardo lab explores evolution in adapted human populations from genetic and physiological perspectives. By understanding and replicating the biology of these unique populations, we can leverage the power of natural selection to improve the wellness of all.

• The Clement lab is interested in developing new computational tools and leveraging cutting-edge experimental technologies to understand the genetics and epigenetics of disease initiation.