Rasmus Nielsen

Primary Research Area: 
Applied & Theoretical Statistics
nielsen [at] stat [dot] berkeley [dot] edu
Office / Location: 
4098 VLSB

Rasmus Nielsen  is a professor of computational biology at UC Berkeley (since 2008) and a professor of biology at University of Copenhagen (since 2004).  He graduated with a PhD in Integrative Biology from UC Berkeley in 1998, did two years of postdoc at Harvard University and held his first faculty position at Cornell University 2000 – 2004 in the department of Biometrics (now BSCB). RN’s research focuses on developing statistical and computational methods for analyses of genomic data.  His methods, distributed in popular packages such as IM and PAML, have been used in numerous scientific studies. He is a Senior Editor for Genetics and an Associate Editor for Molecular Biology and Evolution

Select Publications: 


Junjie Qin, et al. 2012. A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature 490; 55–60 doi:10.1038/nature11450.

Nielsen R, et al. 2012. SNP Calling, Genotype Calling, and Sample Allele Frequency Estimation from New-Generation Sequencing Data. PLoS ONE; 7(7): e37558. doi:10.1371/journal.pone.0037558.

Brawand, D. et al. 2011. The evolution of gene expression levels in mammalian organs. Nature 478: 343–348.

Rasmussen, M. et al. 2011. An Aboriginal Australian Genome Reveals Separate Human Dispersals into Asia. Science 7: Vol. 334 no. 6052 pp. 94-98, DOI:10.1126/science.1211177.

Nielsen, R. et al (2011). Genotype and SNP calling from next-generation sequencing data. Nature Reviews Genetics, 12:443-451.

Green et al. 2010. A Draft Sequence of the Neandertal Genome. Science 328: 710-722.

Li, R. et al. 2010. The sequence and de novo assembly of the giant panda genome. Nature 463: 1106-1111.

Yi, X. et al. 2010. Sequencing of 50 Human Exomes Reveals Adaptation to High Altitude. Science 329: 75-78.

For full list, see http://cteg.berkeley.edu/~nielsen/resources/publications/.

Research Interests: 

My work focuses on the development and application of statistical methods in genomics. Most of it concentrates on making inferences regarding function and evolution from molecular and genetic data. Some of the projects that I am currently involved in are in the areas of human population genetics, comparative evolutionary genomics, coalescent theory, and statistical methods in molecular ecology. Examples include evolutionary analyses of whole genome data from a diverse set of organisms including bacteria, the Giant Panda, the Rhesus Macaque monkey, humans, and chimpanzees, development of methods for association mapping which can accommodate non-linear interactions, and the development of MCMC methods for inferring demographic parameters in population genetics.