Stephen K. Burley M.D., D.Phil. Director, RCSB Protein Data Bank, RCSB Protein Data Bank Rutgers University/UC San Diego
Stephen Burley is an expert in structural biology, proteomics, bioinformatics, structure/fragment based drug discovery, and clinical medicine/oncology.
Marija Buljan , ETH Zurich
Marija's research focuses on how disease-associated mutations affect the choice and affinity of protein interactions and how this then affects the cellular function.
Elizabeth Brunk , UCSD
Elizabeth is a Computational scientist with a focus on developing and applying workflows that integrate large-scale data sets, network-based analysis and structure-based modeling.
Hannah Carter , UCSD, Medical Genetics
Dr. Hannah Carter’s research focuses on computationally modeling how DNA mutations in tumor genomes impact intracellular biological processes and cellular behaviors, and how these cellular level changes cause cancer.
Gil Omenn Director, Center for Computational Medicine and Bioinformatics, University of Michigan
Dr. Omenn's research focuses on cancer proteomics and informatics. He is especially interested in the role of differential expression of alternative splice isoforms of proteins and transcripts in specific cancer-related pathways.
Ariel Rokem , University of Washington eScience Institute
Ariel creates and facilitates the use of ideas, processes and technologies that advance data-intensive discovery in all fields.
Gwênlyn Glusman , Institute for Systems Biology - Kaviar database
Dr. Glusman investigates genome structure and evolution; multi-gene families; prediction and discovery of genes and transcripts; genes not coding for proteins; visualization of complex data; and image analysis.
Eric Deutsch Senior Research Scientist, Institute for Systems Biology
Dr. Deutsch’s research activities include software development for the analysis and integration of data for systems biology research.
John Moult , Institute for Bioscience and Biotechnology Research
Modeling of effects of single nucleotide polymorphisms (SNPs) on protein structure and human diseases.
Lydie Lane , Swiss Institute of Bioinformatics
Annotating the effects of human protein variations in the context of cancers and genetic diseases, and analysing results of high-throughput experiments to shed light on the function of selected sets of uncharacterized human proteins
Torsten Schwede , University of Basel, Biozentrum
Torsten develops computer programs which allow to model the structure of proteins that have not previously been elucidated experimentally.
Jianjiong Gao , Memorial Sloan Kettering Cancer Center, cBioPortal
Our team develops resources such as cBioPortal which allow interactive and explorative analysis and interpretation of cancer genomics data.
Rachel Karchin , Johns Hopkins University
We develop computational models to interpret and predict the impact of individual variation in the genome, transcriptome, and proteome.
Hagen Tilgner Assistant Professor of Neuroscience, Weill Cornell Medical College, Cornell University
We are interested in how the same, within an individual mostly invariant genome, can give rise to functionally extremely diverse cell types – such as the ones that are the building blocks of the human brain.
We are mapping continuous-valued functional and clinical data from cystic fibrosis-associated CFTR variants onto CFTR homology models. Two functional assays report either the degree of CFTR misfolding or the attenuation in chloride conductance resulting from specific CFTR variants. Additionally, we consider a clinical measurement of variant-specific cystic fibrosis disease severity (sweat chloride level). The clustering of these endophenotypes on the 3D CFTR structure could help identify specific CFTR structural regions that are enriched for disease-causing variants, and to infer mechanism.
David Masica Assistant Research Professor, Johns Hopkins University
David is interested in developing novel computational methods to predict the impact of (epi)genetic alterations on human disease and drug response.
Sheila Reynolds Senior Research Scientist, Institute for Systems Biology
Sheila is interested in applying a wide range of machine-learning techniques to large heterogeneous datasets to further our understanding of the complex interplay of genomic rearrangements and epigenetic alterations in cancer and to help translate these findings into new and improved treatment protocols.
Adam Godzik , Sanford Burnham Prebys Medical Discovery Institute
We try to combine insights from physics and biology to answer basic questions about the relation between the protein sequence and its structure and function.
Geoff Barton Professor of Bioinformatics and Head of Division of Computational Biology, University of Dundee
Geoff Barton is Professor of Bioinformatics and Head of the Division of Computational Biology at the University of Dundee School of Life Sciences. Before moving to Dundee in 2001 he was Head of the Protein Data Bank in Europe and Research and Development Team leader at the EMBL European Bioinformatics Institute, Hinxton, Cambridge. Prior to EMBLEBI he was Head of Genome Informatics at the Wellcome Trust Centre for Human Genetics, University of Oxford, a position he held concurrently with a Royal Society University Research Fellowship in the Department of Biochemistry.
Geoff’s longest running research interest is the study of the relationship between a protein’s sequence, its structure and function by computational methods. His work exploits large publicly available datasets to identify novel properties and to develop effective prediction methods. His group have contributed many tools and techniques in the area of protein sequence and structure analysis and structure prediction. Two of the best known are the Jalview (www.jalview.org) multiple alignment visualisation and analysis workbench which is in use by over 70,000 groups for research and teaching, and the JPred (www.compbio.dundee.ac.uk/jpred) multi-Neural Net protein secondary structure prediction algorithm that performs predictions on up to 250,000 proteins/month for users worldwide. In addition to his work on protein sequence and structure, Geoff has collaborated on many projects that probe biological processes by proteomics and highthroughput sequencing. In particular, he has a long-running collaboration with Prof Gordon Simpson that seeks to understand the control of mRNA termination and methylation. Geoff’s group has deep expertise in RNA-seq methods and has recently published a two-condition 48 replicate RNA-seq study that is now a key reference work for users of this technology.
Frances Pearl Bioinformatics Academic Research Manager (Biochemistry), University of Sussex
We use bioinformatics and cheminformatics techniques to support the translational drug discovery initiative in Sussex, to analyse cancer data and to study protein evolution.
Andeas Prlić Technical and Scientific Team Lead RCSB Protein Data Bank, RCSB PDB, UCSD