Program

Invited Speakers

Dr. Janet Kelso

Dr. Janet Kelso is head of the Bioinformatics research group at the Max-Planck Institute for Evolutionary Anthropology in Leipzig, Germany. Her research focuses on comparative primate genomics and ancient DNA with a particular emphasis on analysis of the genomes of archaic humans. Her group has a special interest in the development of novel software for processing and analysis of high-throughput sequence data and uses computational approaches to gain insights into genome evolution. Janet received her PhD in bioinformatics from the South African National Bioinformatics Institute at the University of the Western Cape under the supervision of Professor Winston Hide developing an ontology for classifying gene expression data for which she won the L'Oreal women in science fellowship. She is author of more than 80 peer-reviewed scientific publications. Together with Alfonso Valencia, Janet is the co-Editor-in-chief of the journal Bioinformatics, and also an editor of the journal Database.

Janet is an active member of the Board of the International Society of Computational Biology. She has held positions as both Vice-president and Secretary, and was named a Fellow of the Society in 2015.

Dr. Julio Sáez-Rodríguez

Dr. Julio Sáez-Rodríguez is since June 2018 Professor of Medical Bioinformatics and Data Analysis at the Faculty of Medicine of the University of Heidelberg. He is an affiliated member of Sage-Bionetworks and a director of the DREAM challenges to catalyze the development of methods in systems biology, and the scientific coordinator of the EU-H2020 PrECISE (Personalized engine for Cancer integrative study and evaluation) consortium. He obtained his PhD in 2007 at the University of Magdeburg and the Max-Planck-Institute. He was a postdoctoral fellow at Harvard Medical School and M.I.T., and a Scientific Coordinator of the NIH-NIGMS Cell Decision Process Center. From 2010 until 2015 he was a group leader at EMBL-EBI with a joint appointment in the EMBL Genome Biology Unit in Heidelberg, as well as a senior fellow at Wolfson College (Cambridge). From 2015 to 2018 he was professor of Computational Biomedicine at the RWTH Aachen.

His group develops and applies computational methods to acquire a functional understanding of signaling networks and their deregulation in disease, and to apply this knowledge to develop novel therapeutics. To this end, his group collaborates closely with experimental groups and pharmaceutical companies. More information at www.Sáezlab.org.

Dr. María Rodríguez Martínez

Dr. María Rodríguez Martínez is the technical lead of the group of Systems Biology at IBM Research - Zürich. A physicist by training, she did her PhD and a first postdoc in High Energy Physics at the Institut d’Astrophysique de Paris and Hebrew University respectively. In 2006, she transitioned into Systems Biology as a postdoc at the Weizmann Institute of Science and later at Columbia University. Her training was supported by a number of prestigious fellowships, among which: EARA Marie Curie Visiting Fellowships, Cambridge (UK), French Ministry of Research Fellowship, (France), Higher Education Teaching Initiation Fellowship, France, Lady Davies Fellowship, Jerusalem (Israel), etc. She also had extended academic visits in prestigious universities: Caltech, New York University, The University of Texas, Univ. of Cambridge, etc.

Since 2013 she is a member of the Systems Biology group at IBM Research – Zürich, and an associated member of the Department of Biology at ETH since 2014. Her current research focuses on the development of computational and statistical approaches to unravel cancer molecular mechanisms using high-throughput multi-omics datasets and single-cell molecular data. In recent years, her team has focused on the development of mathematical and statistical models to unravel cancer evolution mechanisms, to develop new approaches for data integration and for the analysis of single cell data. She is currently the technical coordinator of an H2020 grant, PrECISE, focused on developing personalized medicine approaches for prostate cancer patients.