Dr Casey Bergman
BSc, MAT, PhD
Summary
Contact details:
Michael Smith Building|Oxford Road|Manchester|M13 9PT
Research interests
Research in the Bergman Lab uses diverse computational and statistical methods to study genome structure, function and evolution. Our work capitalizes on the growing number of complete and draft genome sequences made available over the last decade, which offer an unparalleled opportunity for biological discovery in 21st century. The basic logic underlying our research program is that evolutionary processes have encoded functional and historical signals in genomes that can be decoded using computational and statistical methods. Using computational ("in silico") techniques, we aim to infer the mechanistic and evolutionary forces that have shaped modern eukaryotic genomes over long periods of time in their natural environments. This inferential approach complements classical experimental methods in biology, and has the potential to reveal deep insights into biological processes that are not possible using "in vitro" or "in vivo" methods.
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Highlight publications
- Linheiro, R. & Bergman, C (2012). Whole Genome Resequencing Reveals Natural Target Site Preferences of Transposable Elements in Drosophila melanogaster. PLoS One, 7(2), e30008. eScholarID:157662 | PMID:22347367 | DOI:10.1371/journal.pone.0030008
- Haeussler, M., Gerner, M. & Bergman, C (2011). Annotating genes and genomes with DNA sequences extracted from biomedical articles. Bioinformatics, 27(7), 980-6. eScholarID:121672 | PMID:21325301 | DOI:10.1093/bioinformatics/btr043
- Kalinka, A., Varga, K., Gerrard, D., Preibisch, S., Corcoran, D., Jarrells, J., Ohler, U., Bergman, C. & Tomancak, P (2010). Gene expression divergence recapitulates the developmental hourglass model. Nature, 468(7325), 811-4. eScholarID:103156 | PMID:21150996 | DOI:10.1038/nature09634
- Bergman CM, Bensasson D. (2007). Recent LTR retrotransposon insertion contrasts with waves of non-LTR insertion since speciation in Drosophila melanogaster. Proceedings of the National Academy of Sciences (USA), 104, 11340-11345. eScholarID:1c6715 | PMID:17592135 | DOI:10.1073/pnas.0702552104
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