Peter N. Robinson, MD
We are living in a time of unparalleled opportunity to extend our understanding of human disease and improve the care of patients with precision genomic medicine. Sophisticated bioinformatics and computational biology are essential to achieve the full potential of genomics for science as well as for patients. Peter Robinson, Professor and Donald A. Roux Chair, Genomics and Computational Biology, leads a research group dedicated to the development of algorithms and computational resources for genomics. Peter is a PI of the Monarch Initiative, an NIH supported project dedicated to the integration, alignment, and re-distribution of cross-species gene, genotype, variant, disease, and phenotype data. Highlights of the lab’s work include the Human Phenotype Ontology, the Exomiser suite of tools for exome and genome analysis, and algorithms for ChIP-seq and immunogenomics. Peter studied Mathematics (Bachelor) at Columbia College, Medicine at the University of Pennsylvania, and Computer Science (Master's) at Columbia University. He completed an internship in Primary Care Internal Medicine at Yale University, and a residency (Facharzt) in Pediatrics and obtained a Habilitation (roughly equivalent to a PhD) in Human Genetics at the Charité - Universitätsmedizin Berlin. He led the Bioinformatics group at the Institute for Medical Genetics and Human Genetics at the Charité from 2004-2016. From 2016-2023, he led a research group at the Jackson Laboratory (JAX) for Genomic Medicine in Connecticut, USA. From 2024, his primary affiliation will be with the Berlin Institute of Health (BIH) and he will continue to be affiliated with JAX.
Martha Beckwith, Ph.D.
Martha Beckwith obtained her PhD in Physical Chemistry from Cornell University. During her PhD, she also conducted research at the Max-Planck- Institute for Chemical Energy Conversion in Germany. Prior to joining the Robinson Lab, she was a Postdoctoral Research Associate at Lawrence Livermore National Laboratory, and then a Computational Scientist at the CUNY Advanced Science Research Center. Her current work focuses on developing software for incorporating clinical intuition in phenotype-driven prioritization of rare diseases.
Hannah Blau, Ph.D.
Hannah Blau joined the Robinson Lab as Research Software Engineer in May, 2017. She completed her Ph.D. in Computer Science at the University of Massachusetts Amherst. She earned the B.A. in French from Yale University and the M.S.E. in Computer and Information Science from the University of Pennsylvania. Hannah gained international experience at the Artificial Intelligence Center of the Bull Corporation (Louveciennes, France), and in the Machine Learning Group of the Daimler-Benz Research Centre (Ulm, Germany). She worked as a Research Scientist in the Automated Reasoning Group of the Honeywell Technology Center (Minneapolis, Minnesota). While in grad school she served as data scientist in the lab of Professor M. Darby Dyar, Chair of Astronomy at Mount Holyoke College and member of the science team for the Mars Science Laboratory (Curiosity rover).
Leigh Carmody, Ph.D.
Leigh Carmody, Ph.D., obtained her doctorate of philosophy in Molecular Physiology & Biophysics from Vanderbilt University in Spring 2007 where she studied targeting of signaling molecules to F-actin cytoskeleton/dendritic spines. Dr. Carmody continued her studies as a postdoctoral fellow at Massachusetts Institute of Technology where she investigated the role of Rac1 in dendritic spine motility. Late 2008, she joined the Broad Institute of MIT & Harvard as a Scientist where she aided in early-stage drug discovery efforts to identify chemical leads directed at cancer targets and neglected parasitic infections. Dr. Carmody joined Jackson Laboratory in 2015 as a Project Manager, and is currently a Scientific Curator annotating phenotyping and genomics data for the human phenotype ontology (HPO) database.
I am a current MD-PhD student at UConn School of Medicine with a background in physics. I joined the Robinson Lab after two years of medical school to conduct my thesis research. My research focuses on using the Human Phenotype Ontology (HPO) to describe and understand the phenotypic features of neurodevelopmental disorders in a generalizable and computable format. By improving the way we describe patient phenotypes, we will improve our ability to identify the genetic drivers of these phenotypes. To do this, I work with domain experts to expand the HPO's terminology for neurodevelopmental disorders and to develop tools to translate clinical measurements to the HPO.
Daniel Danis, Ph.D.
Daniel has a M.Sc. in Pharmacy from the Comenius University, Bratislava, Slovakia. He is currently working on his Ph.D., mainly focused on the molecular basis and pathomechanisms of rare hereditary diseases in human patients. He has experience in the assembly of custom UNIX-based bioinformatics pipelines for whole exome sequencing data analysis that have identified disease-causing variants in several Slovak families. His work in the Robinson lab involves the development of algorithms for prioritizing exome and genome variants. These new algorithms are designed to integrate into the Exomiser and Genomiser frameworks. In addition, he works on tools for the biocuration of published disease-causing variants.
Michael Gargano has an M.S in Bioinformatics from Northeastern University. First starting as a UI Developer at Cigna, he joined both The Jackson Laboratory & the Robinson Lab in 2017, and has grown to a Senior Scientific Software Engineer. Bringing the Human Phenotype Ontology to the modern web was his flagship project. He now specializes in data engineering on the cloud, restful applications, bioinformatics pipelines, and architecting software solutions for translational & clinical genomics.
Peter Hansen, Ph.D.
Peter Hansen studied bioinformatics at the Free University of Berlin from 2003 to 2010. In 2011, he began his professional career at the Institute for Medical Genetics and Human Genetics at the Charité hospital in Berlin, where he set up analysis pipelines for high-throughput sequencing data. By analyzing ChIP-seq data from different collaborators, he helped to elucidate the roles of various transcription factors in different contexts, for example HOXD13 and PITX1 in limb development, PAX5 in classical Hodgkin's lymphoma, or E2F6 in CGI methylation. In 2014, he continued his education as a doctoral student. He developed the ChIP-seq peak calling software Q and Q-nexus. Moreover, he led the project "Genomic diagnostics for the regulatory genome" at the Charité on behalf of Peter Robinson, with a focus on conducting capture Hi-C experiments and data analysis. In 2019, he received his Ph.D. in Bioinformatics from the Department of Mathematics and Computer Science at the Free University Berlin and joined The Jackson Laboratory for Genomic Medicine as a Bioinformatics Analyst. He developed GOPHER, a desktop application for capture Hi-C probe design, and Diachromatic, a toolset for preprocessing and quality control of Hi-C and capture Hi-C data. Furthermore, he characterized a feature of Hi-C data and used it to assess and mitigate technical bias. In parallel, he contributed to team projects on a variety of topics including the analysis of differential expression and splicing, prediction of isoform functions, prediction of associations between protein kinases and cancer, and challenges in biomedical knowledge graph representation. More recently, he has been working on ontologizing experimental mouse data from the Mouse Phenome Database at JAX and representing it as Phenopakets.
Guy Karlebach, Ph.D.
Guy earned his B.Sc. in Computer Science from the Technion, Israel Institute of Technology, his Masters in Computer Science from Ben Gurion University, and his Ph.D. in Computer Science from Tel-Aviv University. During his Masters he worked on computational protein structure prediction, developing methods for refining approximate 3D structures. During his Ph.D. he developed algorithms for modeling gene regulatory networks using DNA binding and gene expression data. He has acquired research experience in academia at the Max Planck Institute and in industry working for IBM’s medical informatics group. He is now a Postdoctoral Associate in the Robinson lab developing methods that integrate high-throughput genomic data for a better quantification of variation in gene expression under different conditions. The ultimate goal is to use different technologies in a complementary way that compensates for each individual technology’s shortcomings.
Enock is pursuing his BS in Computer Science at Trinity College, CT. He became a member of The Robinson Lab in Fall 2021. From a young age, Enock was deeply intrigued by the potential of Artificial Intelligence in enhancing healthcare. This interest was further cemented during his high school years when he shadowed physicians at a Rwandan hospital and recognized the pressing need for advanced technology in the medical field. Within the Lab, Enock focuses on developing software and algorithms to refine text mining techniques. He integrates Machine Learning and Large Language Models to assist in the curation of the Medical Action Ontology (MAxO) and contributes to various other bioinformatics initiatives.
|Xingmin “Aaron” Zhang, Ph.D.|
|Vida Ravanmehr, Ph.D|
|Sebastian Köhler, Dr. rer. nat. (Homepage)|
|Peter Krawitz, PhD. (Uni Bonn)|
|Marten Jäger, PhD (BIH Core Facility Genomik )|
|Max Schubach, PhD (Computational Genome Biology, BIH)|
|Leon Kuchenbecker, PhD (GHGA)|
|Robin Steinhaus, MSc (BIH)|
|Layal Abo-Kayal. PhD|
|Na Zhu. PhD|
|Martin-Atta Mensah, Dr. med.|
|Patrick Booms, Ph.D.|
|Marcel H Schulz, Ph.D. (Uni Frankfurt)|
|Miriam Sandya Bauer, Dr. med.|
|Begoña Muñoz-Garcia, PhD|
|Dmitri Parkhomchuk, PhD|
|Dr. Sebastian Bauer, PhD. (HTW Berlin)|
|Oliver Stolpe (BIH)|
|Manuel Holgrewe, Ph.D. (CUBI/BIH)|
|Verena Heinrich, Ph.D. (MPG)|