2nd Annual Three Rivers Evolution Event (TREE)

We are excited to announce the second annual Three Rivers Evolution Event (TREE), a regional conference serving Western Pennsylvania and the surrounding areas, sponsored in part by SMBE. TREE aims to bring together researchers to share and discuss all aspects of evolutionary biology in a diverse, exciting, and accessible environment. Last year, 168 attendees from 38 different institutions joined us in our shared passion for evolution, and we expect our community to grow even larger in 2018. This year’s keynote address will be delivered by Dr. L Lacey Knowles of the University of Michigan.

Researchers of all stages and institutional affiliations are welcome to present. The deadline for both registration and abstract submission is July 31st. To register and/or submit an abstract for a talk or poster, please see our website: https://sites.google.com/view/treepgh There is no fee for registration.

Chikina Lab Publish in Nucleic Acids Research

Dr. Maria Chikina and associates contributed to a publication regarding a web-interface that provides access to a variety of tools for testing associations between epigenetic data samples.

Functional genomics assays produce sets of genomic regions as one of their main outputs. To biologically interpret such region-sets, researchers often use colocalization analysis, where the statistical significance of colocalization (overlap, spatial proximity) between two or more region-sets is tested. Existing colocalization analysis tools vary in the statistical methodology and analysis approaches, thus potentially providing different conclusions for the same research question. As the findings of colocalization analysis are often the basis for follow-up experiments, it is helpful to use several tools in parallel and to compare the results. We developed the Coloc-stats web service to facilitate such analyses. Coloc-stats provides a unified interface to perform colocalization analysis across various analytical methods and method-specific options (e.g. colocalization measures, resolution, null models). Coloc-stats helps the user to find a method that supports their experimental requirements and allows for a straightforward comparison across methods. Coloc-stats is implemented as a web server with a graphical user interface that assists users with configuring their colocalization analyses. Coloc-stats is freely available at https://hyperbrowser.uio.no/coloc-stats/.

Click here to view the full publication