General, 15 January 2020 Bridging Excellence Fellowships The EMBL | Stanford Life Science Alliance invites ambitious researchers who want to bridge two leading research institutions, work with cutting-edge technology, and develop a global profile to submit an application for a Bridging Excellence Fellowship. The Bridging Excellence Fellowships enable postdoctoral researchers to work on creative, high-impact joint projects between EMBL and Stanford. Fellows will have access to researchers and technology at both sites, and as well as first-rate postdoctoral training opportunities from both institutions.
Heidelberg, 14 January 2020 EMBL book club: a forum for diverse perspectives Inspired by the STEMMinist Book Club on Twitter, PhD student Samantha Seah started the book club at EMBL Heidelberg to create a space for people to come together to discuss feminism, activism, racism and other societal issues in a respectful, inclusive and safe environment. The club meets every two to three months, and members vote on which books to read. The choices so far have been Invisible Women by Caroline Criado Perez – an exploration of data bias and the gender data gap – Superior by Angela Saini, which addresses racism in science, and Margaret Atwood’s The Handmaid’s Tale and The Testaments.
Heidelberg, 23 December 2019 EMBL co-develops new method that could facilitate cancer diagnosis Researchers led by EMBL Heidelberg and the Center for Bioinformatics at Saarland University have developed a cheaper and faster method to check for genetic differences in individual cells, which outperforms existing techniques with respect to the information received. This new method could become a new standard in single cell research, and potentially for clinical diagnosis in disease genetics, including cancer. The results have been published in Nature Biotechnology.
Heidelberg, 23 December 2019 Innovative method delivers new insights into the stem cell microenvironment Researchers from EMBL and the German Cancer Research Center (DKFZ) in Heidelberg, Germany, have developed new methods to reveal the three-dimensional organisation of bone marrow at a single cell level. Since bone marrow harbours blood stem cells responsible for life-long blood generation, these results and the new method provides a novel scientific basis to study blood cancer. The results have been published in Nature Cell Biology.
Heidelberg, 20 December 2019 A classification tool for transcription factors Researchers in the Zaugg group at EMBL Heidelberg have developed a software named diffTF. It identifies differentially active transcription factors and captures their dominant mode of action. diffTF is the first data-driven tool that provides a generalised classification of transcription factors as activators or repressors. The software can be applied in any research project in which chromatin-based data is used on a large scale.
General, 19 December 2019 Empowering European structural biology The iNEXT-Discovery consortium enables leading European facilities to offer advanced technological instrumentation and expertise to all European scientists, allowing them to perform high-end structural biology research with state-of-the-art equipment that is often unavailable in their home countries.
General, 16 December 2019 Building Euro-BioImaging Euro-BioImaging’s new status as a European Research Infrastructure Consortium (ERIC) was confirmed in November. It means that 14 countries across Europe, along with EMBL, have now made a formal commitment to participate in and fund the initiative, and more are expected to join over the coming year. This will significantly advance Euro-BioImaging’s aim of promoting uptake of the latest technologies in biological and biomedical imaging, and making them openly available to scientists across Europe. EMBL’s Jan Ellenberg reflects on the process of forming a European research infrastructure.
Hinxton, 13 December 2019 Machine learning finds functional human phosphosites Researchers at the EMBL’s European Bioinformatics Institute (EMBL-EBI) have created the largest reference phosphoproteome to date of almost 120 000 human phosphosites. To identify those most likely to be critical, they used a machine learning approach capable of ranking them according to functional importance.