World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
42
Citations
6506
World Ranking
1810
National Ranking
773

Research.com Recognitions

  • 2008 - Fellow of Alfred P. Sloan Foundation

Overview

Yun S. Song is affiliated with the University of California, Berkeley in the United States. Their research primarily falls within the field of Biochemistry, Genetics and Molecular Biology, with a strong focus on several subfields including Molecular Biology, Genetics, Immunology, Artificial Intelligence, and Epidemiology.

The scientist's work covers multiple topics related to genomics and molecular biology. These topics include:

  • Genomics and Phylogenetic Studies
  • Single-cell and spatial transcriptomics
  • RNA and protein synthesis mechanisms
  • Machine Learning in Bioinformatics
  • Cancer Genomics and Diagnostics
  • Genetic Associations and Epidemiology
  • Genomics and Rare Diseases

Yun S. Song has published extensively, with frequent publications appearing in venues such as:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Zenodo (CERN European Organization for Nuclear Research)
  • arXiv (Cornell University)
  • Proceedings of the National Academy of Sciences
  • Genome Biology

Some recent papers associated with Yun S. Song include:

  • Type I interferon autoantibodies are associated with systemic immune alterations in patients with COVID-19, 2021, Science Translational Medicine
  • Multi-geohazards susceptibility mapping based on machine learning-a case study in Jiuzhaigou, China, 2020, Natural Hazards
  • XYZeq: Spatially resolved single-cell RNA sequencing reveals expression heterogeneity in the tumor microenvironment, 2021, Science Advances
  • DNA language models are powerful predictors of genome-wide variant effects, 2023, Proceedings of the National Academy of Sciences
  • Whole-genome sequencing reveals a complex African population demographic history and signatures of local adaptation, 2023, Cell

Yun S. Song has collaborated frequently with a number of co-authors, including:

  • Milind Jagota
  • Carlos Albors
  • Chengzhong Ye
  • Yun Deng
  • Chun Ye

The scientist has been recognized as a Fellow of the Alfred P. Sloan Foundation in 2008.

Best Publications

  • Robust and scalable inference of population history from hundreds of unphased whole genomes

    Jonathan Terhorst;John A Kamm;Yun S Song

  • Deep Learning for Population Genetic Inference.

    Sara Sheehan;Yun S. Song

  • Estimating Variable Effective Population Sizes from Multiple Genomes: A Sequentially Markov Conditional Sampling Distribution Approach

    Sara Sheehan;Kelley Harris;Yun S. Song

  • Efficiently inferring the demographic history of many populations with allele count data.

    Jack Kamm;Jonathan Terhorst;Richard Durbin;Yun S. Song

  • Constructing minimal ancestral recombination graphs.

    Yun S. Song;Jotun Hein

  • ECHO: A reference-free short-read error correction algorithm

    Wei-Chun Kao;Andrew H. Chan;Yun S. Song

  • BayesCall: A model-based base-calling algorithm for high-throughput short-read sequencing

    Wei-Chun Kao;Kristian Stevens;Yun S. Song

  • A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks.

    Jeffrey Chan;Valerio Perrone;Jeffrey P Spence;Paul A Jenkins

  • Efficient Computation of the Joint Sample Frequency Spectra for Multiple Populations

    John A. Kamm;Jonathan Terhorst;Yun S. Song

  • Fundamental limits on the accuracy of demographic inference based on the sample frequency spectrum.

    Jonathan Terhorst;Yun S. Song

  • Minimum recombination histories by branch and bound

    Rune B. Lyngsø;Yun S. Song;Jotun Hein

  • Inference of complex population histories using whole-genome sequences from multiple populations.

    Matthias Steinrücken;Jack Kamm;Jeffrey P Spence;Yun S Song

  • Efficient inference of population size histories and locus-specific mutation rates from large-sample genomic variation data

    Anand Bhaskar;Y.X. Rachel Wang;Yun S. Song

  • A Simple Method for Finding Explicit Analytic Transition Densities of Diffusion Processes with General Diploid Selection

    Yun S. Song;Matthias Steinrücken

  • Open String Instantons and Relative Stable Morphisms

    Jun Li;Yun S Song

  • High-throughput inference of pairwise coalescence times identifies signals of selection and enriched disease heritability

    Pier Francesco Palamara;Jonathan Terhorst;Yun S. Song;Alkes L. Price

  • The Key Parameters that Govern Translation Efficiency

    Dan D. Erdmann-Pham;Khanh Dao Duc;Yun S. Song

  • Descartes’ rule of signs and the identifiability of population demographic models from genomic variation data

    Anand Bhaskar;Yun S Song

  • Multi-locus Analysis of Genomic Time Series Data from Experimental Evolution

    Jonathan Terhorst;Christian Schlötterer;Yun S. Song

  • A NOVEL SPECTRAL METHOD FOR INFERRING GENERAL DIPLOID SELECTION FROM TIME SERIES GENETIC DATA.

    Matthias Steinrücken;Anand Bhaskar;Yun S. Song

  • Distortion of genealogical properties when the sample is very large.

    Anand Bhaskar;Andrew G. Clark;Yun S. Song

  • An Accurate Sequentially Markov Conditional Sampling Distribution for the Coalescent With Recombination

    Joshua S. Paul;Matthias Steinrücken;Yun S. Song

  • An efficient algorithm for statistical multiple alignment on arbitrary phylogenetic trees.

    Gerton Lunter;István Miklós;Yun S. Song;Jotun Hein

Frequent Co-Authors

Jotun Hein
Jotun Hein University of Oxford
Rasmus Nielsen
Rasmus Nielsen University of California, Berkeley
Charles H. Langley
Charles H. Langley University of California, Davis
Michael I. Jordan
Michael I. Jordan University of California, Berkeley
Montgomery Slatkin
Montgomery Slatkin University of California, Berkeley
Richard Villems
Richard Villems University of Tartu
David J. Meltzer
David J. Meltzer Southern Methodist University
Ene Metspalu
Ene Metspalu University of Tartu
Dan Gusfield
Dan Gusfield University of California, Davis

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