Yun S. Song | EECS at UC Berkeley

Yun S. Song

Contact Information

304B Stanley Hall

tel: 510-642-2351

yss@berkeley.edu

Office Hours

TuTh 5-6pm, 304B Stanley

Links

Personal Homepage

Research Support

Catie Anders
cmanders@berkeley.edu

Biography

Yun S. Song is a professor of EECS and Statistics working in mathematical and computational biology. Recent honors and awards include NIH Pathway to Independence Award K99/R00 (2006), Alfred P. Sloan Research Fellowship (2008), Packard Fellowship for Science and Engineering (2008), NSF CAREER Award (2009), Jim and Donna Gray Faculty Award for Excellence in Undergraduate Teaching (2013), Miller Research Professorship (2014), Math+X Simons Chair (2015), and Chan Zuckerberg Biohub Investigator Award (2017)

Education

2001, PhD, Physics, Stanford University

1997, B.S., Mathematics, MIT

1996, B.S., Physics, MIT

Research Areas

Biosystems & Computational Biology (BIO)

Artificial Intelligence (AI)

Applied Probability and Statistics

Research Centers

Center for Computational Biology (CCB)

Simons Institute for the Theory of Computing (SITC)

G. Benegas, S. Batra, and Y. S. Song, "DNA language models are powerful predictors of genome-wide variant effects," PNAS, vol. 120, no. 44, pp. e2311219120, Oct. 2023.
M. Jagota, C. Ye, C. Albors, R. Rastogi, K. Antoine, N. Ioannidis, and Y. S. Song, "Cross-protein transfer learning substantially improves disease variant prediction," Genome Biology, vol. 24, no. 182, Aug. 2023.
S. Prillo, Y. Song, P. Boyeau, X. Li, P. Chen, and Y. S. Song, "CherryML: Scalable maximum likelihood estimation of phylogenetic models," Nature Methods, vol. 20, pp. 1232-1236, June 2023.
D. Erdmann-Pham, K. Dao Duc, and Y. S. Song, "The key parameters that govern translation efficiency," Cell Systems, vol. 10, no. 2, pp. 183-192.e6, Jan. 2020.
R. Rao, N. Bhattacharya, N. Thomas, Y. Duan, P. Chen, J. F. Canny, P. Abbeel, and Y. S. Song, "Evaluating Protein Transfer Learning with TAPE," in Advances in Neural Information Processing Systems (NeurIPS), Vol. 32, 2019.
J. Spence and Y. S. Song, "Inference and analysis of population-specific fine-scale recombination maps across 26 diverse human populations," Science Advances, vol. 5, no. 10, pp. eaaw9206, Oct. 2019.
M. Wang, J. Fischer, and Y. S. Song, "Three-way clustering of multi-tissue multi-individual gene expression data using semi-nonnegative tensor decomposition," Annals of Applied Statistics,, vol. 13, no. 2, pp. 1103-1127, June 2019.
J. Chan, V. Perrone, J. Spence, P. Jenkins, S. Mathieson, and Y. S. Song, "A likelihood-free inference framework for population genetic data using exchangeable neural networks," in Advances in Neural Information Processing Systems (NeurIPS), 2018.
P. Palamara, J. Terhorst, Y. S. Song, and A. Price, "High-throughput inference of pairwise coalescence times identifies signals of selection and enriched disease heritability," Nature Genetics, vol. 50, pp. 1311-1317, Aug. 2018.
K. Dao Duc and Y. S. Song, "The impact of ribosomal interference, codon usage, and exit tunnel interactions on translation elongation rate variation," PLoS Genetics, vol. 14, no. 1, pp. e1007166, Jan. 2018.
M. Wang, K. Dao Duc, J. Fischer, and Y. S. Song, "Operator norm inequalities between tensor unfoldings on the partition lattice," Linear Algebra and its Applications, vol. 520, pp. 44-66, May 2017.
J. Terhorst, J. A. Kamm, and Y. S. Song, "Robust and scalable inference of population history from hundreds of unphased whole genomes," Nature Genetics, vol. 49, pp. 303-309, Jan. 2017.
S. Sheehan and Y. S. Song, "Deep learning for population genetic inference," PLoS Comput Biol, vol. 12, no. 5, pp. e1004845, March 2016.
A. Bhaskar, Y. X. R. Wang, and Y. S. Song, "Efficient inference of population size histories and locus-specific mutation rates from large-sample genomic variation data," Genome Research, vol. 25, no. 2, pp. 268-279, 2015.
J. Terhorst and Y. S. Song, "Fundamental limits on the accuracy of demographic inference based on the sample frequency spectrum," PNAS, vol. 112, no. 25, pp. 7677-7682, June 2015.
M. Steinrücken, A. Bhaskar, and Y. S. Song, "A novel spectral method for inferring general diploid selection from time series genetic data," Annals of Applied Statistics, vol. 8, no. 4, pp. 2203-2222, 2014.
A. Bhaskar and Y. S. Song, "Descartes' rule of signs and the identifiability of population demographic models from genomic variation data," Annals of Statistics, vol. 42, no. 6, pp. 2469-2493, Dec. 2014.
A. Bhaskar, A. G. Clark, and Y. S. Song, "Distortion of genealogical properties when the sample is very large," PNAS, vol. 111, no. 6, pp. 2385-2390, Feb. 2014.
P. A. Jenkins and Y. S. Song, "Padé approximants and exact two-locus sampling distributions," Annals of Applied Probability, vol. 22, no. 2, pp. 576-607, 2012.
Y. S. Song and M. Steinrücken, "A simple method for finding explicit analytic transition densities of diffusion processes with general diploid selection," Genetics, vol. 190, no. 3, pp. 1117-1129, March 2012.