Recent Posts

• May 10, 2021

  New summer student

  We are very excited to announce that Shanna Schneidewind has joined the lab as a summer student from the University of Poitiers, France. Shanna will be working with us for the next 3 months, focusing on modeling interactions between biological pathways and clinical features in cancer.

• April 12, 2021

  Postdoctoral position available

  We have an open position for a 3-year postdoctoral fellowship regarding patient-specific gene regulatory network analysis in breast cancer. Please check the open positions page for more information.

• April 06, 2021

  New group member

  We are very excited to announce that Daniel Osorio has joined the lab as a postdoctoral fellow through the Marie Curie Scientia Fellows II program. Daniel is joining us from the University of A&M Texas, where he did his PhD in the group of James Cai. Daniel will be working on regulatory network modeling in single-cell data. Here's a news article to learn more.

• March 26, 2021

  New BioRχiv pre-print

  We have a new BioRχiv pre-print by Ping-Han! Ping-Han found that certain normalization methods, in specific quantile-based methods, can introduce false positive associations in co-expression measurements. However, there methods can be very powerful. Smooth quantile normalization, for example, allows one to normalize heterogeneous data, while keeping global expression differences between different subgroups of samples. Ping-Han therefore developed a new algorithm, called CAIMAN, to correct for these false-positive associations....

• March 12, 2021

  New publication and Biorxiv pre-print

  We recently contributed to a new publication as well as a newly posted BioRxiv pre-print. The new publication in PLoS ONE done in collaboration with Ola Myklebost and Leonardo Meza-Zepeda's groups from the University of Bergen and Oslo, respectively. It involved high-throughput drug screening to discover novel candidates for treatment of liposarcoma. We contributed with bioinformatics analyses to identify potential biomarkers of drug response....