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“The key challenge in bioinformatics today is not the development of new algorithms, but truly understanding the available data. ”
Bjoern Peters, Ph.D.
Associate Professor
Center for Infectious Disease; Division of Vaccine Discovery

cell-bullet1.jpg"The key challenge in bioinformatics today is not the development of new algorithms, but truly understanding the available data." - Bjoern Peters, Ph.D.

Bjoern Peters, Ph.D.Bjoern Peters is an Associate Professor in the Vaccine Discovery Division. Dr. Peters' research focus is on the analysis of immunological information using statistical and computational methods, with a particular interest in modeling the recognition of immune epitopes. In 2000, Dr. Peters received his Diploma from the University of Hamburg in Germany, for a thesis in Laser Physics and Quantum Optics. Dr. Peters then undertook graduate work at the Humboldt University in Berlin, where he became interested in applying quantitative methods commonly used in physics to immunological questions. He earned his PhD in Theoretical Biophysics in 2003 with summa cum laude, writing his thesis on modeling the MHC class I antigen processing and presentation pathway. In 2004, Dr. Peters came to LIAI for a postdoctoral training position in Dr. Sette's lab. From the start, he was heavily involved in the Immune Epitope Database project (http://www.immuneepitope.org), and became its Co-PI in charge of bioinformatics in 2005. Between 2006 and 2007 he was a Research Scientist, before being appointed Assistant Professor at LIAI at the start of 2008.

research focus
cell-bullet2.jpgDr. Peters and his team are developing tools to analyze and predict what parts of a pathogen or allergen are targeted by immune responses. Several of the molecular mechanisms involved in these processes have been well characterized experimentally. By analyzing patterns in the experimental data, it is possible to create predictive computational models. These models can be applied to scan allergens or pathogens in silico for likely immune response targets. Identifying these targets aids in the rational development of treatments and diagnostics. The resulting computational tools are made freely available as part of the Immune Epitope Database Analysis Resource (http://tools.immuneepitope.org) The Immune Epitope Database itself catalogs and organizes immune epitope data, which requires transforming free text information from journal publications into a structured format. To make optimal use of the stored information, it is desirable to connect it with information stored elsewhere. For example, one could ask what the variability of an immune response target in different strains of a pathogen is. This requires connecting the IEDB data to other resources storing genomic information. Doing this efficiently requires a community consensus on knowledge representation standards. Dr. Peters team is contributing to such consensus building and standardization efforts through active work on scientific community initiatives: The Ontology of Biomedical Investigations (OBI, http://obi-ontology.org/), and the NIAID data interoperability working group.
selected publications

cell-bullet3.jpg The immune epitope database (IEDB) 3.0. Nucleic Acid Res. 2015

Transcriptional profile of tuberculosis antigen-specific T cells reveals novel multifunctional features. J. Immunol. 2014

Epigenomic analysis of primary human T cells reveals enhancers associated with TH2 memory cell differentiation and asthma susceptibility. Nat. Immunol. 2014

Using a combined computational-experimental approach to predict antibody-specific B cell epitopes. Structure. 2014

Properties of MHC class I presented peptides that enhance immunogenicity. PLoS Comput. Biol. 2013

Previously undescribed grass pollen antigens are the major inducers of T helper 2 cytokine-producing T cells in allergic individuals. PNAS

Predicting cell types and genetic variations contributing to disease by combining GWAS and epigenetic data. PLoS One 2013

Positional bias of MHC class I restricted T-cell epitopes in viral antigens is likely due to a bias in conservation. PLoS Comput Biol 2013

Drug hypersensitivity caused by alteration of the MHC-presented self-peptide repertoire. Proc Natl Acad Sci U S A. 2012

Pre-existing immunity against swine-origin H1N1 influenza viruses in the general human population. Proc Natl Acad Sci U S A. 2009

A consensus epitope prediction approach identifies the breadth of murine T(CD8+)-cell responses to vaccinia virus. Nat Biotechnol. 2006

A community resource benchmarking predictions of peptide binding to MHC-I molecules. PLoS Comput Biol. 2006

Examining the independent binding assumption for binding of peptide epitopes to MHC-I molecules. Bioinformatics. 2003

Identifying MHC class I epitopes by predicting the TAP transport efficiency of epitope precursors. J Immunol. 2003


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staff list
upcoming seminars
  • LOUIS PICKER  "Cytomegalovirus and Control of CD8+ T Cell Priming: Exploiting the Explorer"
    Wednesday 10/21/15: 12:00 PM
  • HUA YU  "STAT3 in cancer and immune regulation: from fundamental discoveries to clinical translation"
    Wednesday 10/28/15: 12:00 PM
  • Steering committee member of the DAIT data interoperability working group
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