Dr. Yana Bromberg is an associate professor at the Department of Biochemistry and Microbiology, Rutgers University. She holds an adjunct position at the Department of Genetics at Rutgers and is the Chief Scientific Officer at BioSof — a company for bioinformatics tool development. She is also a fellow at the Institute of Advanced Studies in the Technical University of Munich.
Dr. Bromberg received her Bachelor degrees in Biology and Computer Sciences from the State University of New York at Stony Brook and a Ph.D. in Biomedical Informatics from Columbia University, New York. She is known for her seminal work on a method for screening for non-acceptable polymorphisms, or SNAP for short, which evaluates the effects of single amino acid substitutions on protein function. Currently, research in the Bromberg lab is focused on the molecular functional annotation of microbiomes, aiming to identify emergent functionality specific to individual environmental niches. The lab also analyses human variomes for disease predisposition and the studies evolution of life’s electron transfer reactions. Dr. Bromberg is a member of the Board of Directors of the International Society for Computational Biology and actively participates in organizing the ISMB/ECCB conferences (ISMB stands for Intelligent Systems for Molecular Biology, and ECCB is it's European equivalent). She chairs poster and talk sessions, conducts workshops, and organizes a special interest group aimed at the study of genomic variation — VarI-SIG. Dr. Bromberg's work has been recognized by several awards in addition to the TSS young investigator award, including the recent NSF CAREER award, the Rutgers Board of Trustees Research fellowship for Scholarly Excellence, the PhRMA foundation young investigator research starter award and the Hans-Fischer award for outstanding early career scientists from the Institute of Advanced Studies in Technical University of Munich.
Dr. Bromberg also serves as an editor and a reviewer of several top bioinformatics journals, including BMC Genomics and PLoS Computational Biology. To date, she has authored or co-authored 40 peer reviewed scientific articles and has been invited to give over 70 talks.
2016 Rutgers Board of Trustees Research Fellowship for Scholarly Excellence
2016 Theobald Smith Society Young Investigator Award
2015 PhRMA Foundation Research Starter Grant
2014-2017 Hans Fischer Fellowship for Outstanding Early Career Scientists, Institute for Advanced Study at Technical University of Munich
2014 Brooklyn Tech Younger Alumni Recognition Award for Career Progress
2008 International Society for Computational Biology Travel Fellowship
2001-2005 NLM Biomedical Informatics research training fellow
2000 Weizmann Institute of Science, Karyn Kupcinet International Science School Scholar
1997-2001 SUNY at Stony Brook Honors Scholar
1997 National Merit Scholar
1997 Guideposts Scholar
The primary focus of Yana Bromberg’s research can be summarized in one word – function. Where does the functional machinery of life come from? Why and how does it run? Is there a minimum set of the functional gears that represents a viable entity? The DNA blueprint of biological machinery holds many of the answers to these questions. Her long-term goal is to understand how function is encoded in genetic data, whether by a single gene, a genome, or a metagenome. Her current research aims to (1) correlate genome variation to phenotype, (2) identify the specifics of sequence-encoded molecular functions, and (3) elucidate complex system/community interactions.
Keywords: sequence analysis; function prediction; metagenomics; genome variation; SNP analysis; genotype-phenotype mapping; machine learning and clustering in biology
- Evolutionary history of redox metal-binding domains across the tree of life. Proceedings of the National Academy of Sciences 111 (19), 2014, 7042-7047 more… BibTeX Full text ( DOI )
- Function-based assessment of structural similarity measurements using metal co-factor orientation. Proteins 82 (4), 2013, 648-656 more… BibTeX Full text ( DOI )
- Neutral and weakly nonneutral sequence variants may define individuality. Proceedings of the National Academy of Sciences 110 (35), 2013, 14255-14260 more… BibTeX Full text ( DOI )
- Collective judgment predicts disease-associated single nucleotide variants. BMC Genomics 14 (Suppl 3), 2013, S2 more… BibTeX Full text ( DOI )
- Comparative genomic and physiological analysis provides insights into the role of Acidobacteria in organic carbon utilization in Arctic tundra soils. FEMS Microbiol Ecol 82 (2), 2012, 341-355 more… BibTeX Full text ( DOI )
- TrAnsFuSE refines the search for protein function: oxidoreductases. Integr. Biol. 4 (7), 2012, 765 more… BibTeX Full text ( DOI )
- SNPdbe: constructing an nsSNP functional impacts database. Bioinformatics 28 (4), 2011, 601-602 more… BibTeX Full text ( DOI )
- In silico mutagenesis: a case study of the melanocortin 4 receptor. The FASEB Journal 23 (9), 2009, 3059-3069 more… BibTeX Full text ( DOI )
- Correlating protein function and stability through the analysis of single amino acid substitutions. BMC Bioinformatics 10 (Suppl 8), 2009, S8 more… BibTeX Full text ( DOI )
- Comprehensive in silico mutagenesis highlights functionally important residues in proteins. Bioinformatics 24 (16), 2008, i207-i212 more… BibTeX Full text ( DOI )
- SNAP: predict effect of non-synonymous polymorphisms on function. Nucleic Acids Research 35 (11), 2007, 3823-3835 more… BibTeX Full text ( DOI )