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Video: PhD Students Talk about New Research on Transposable Elements and Cancer
In the new paper published in Nature Reviews, “Towards targeting transposable elements for cancer therapy”, graduate students Xuan Qu and Yonghao Liang (Holden) summarized the latest research developments in the field. In this video, they talk about their research focus in Dr. Ting Wang’s lab.
Using Interpretable Deep Learning Tools to Decipher Gene Regulation
In this paper, recently published in PLOS Computational Biology, Dr. Michael White, Associate Professor of Genetics and colleagues used a new AI learning package to model data generated with synthetic regulatory DNA elements to further the understanding of regulatory DNA.
The Turner Lab Develops HAT to Call De Novo Variants for Short-read and Long-read Sequencing Data
The Turner Lab has recently released Hare And Tortoise (HAT), an automated de novo variant (DNV) detection workflow for highly accurate short-read and long-read sequencing data. The method was published in Bioinformatics in January 2024.
The Schedl Lab Receives R35 Grant
The Schedl Lab led by Dr. Tim Schedl recently received NIGMS R35 grant. The grant provides funding for studying “control of germline stem cells and the switch to meiotic development in C. elegans” for 5 years.
New computational tools developed to identify TE-derived antigens in cancer using long-read CAGE sequencing data
In the new study published in Genome Research, postdoctoral fellow Ju Heon Maeng has developed a suite of computational tools to significantly improve immunopeptidome detection from transposable element expression, utilizing long-read data.
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