Read2Tree: Inferring phylogenetic trees from raw sequencing data

Phylogenetic trees are important tools for illustrating how related different species are on a genetic level. They can even reveal the introduction of invasive species in an ecosystem for instance. Constructing these trees typically involve various time-consuming processes. In this in silico talk, David Dylus introduces Read2Tree, a tool he developed with his colleagues in the SIB Group led by Christophe Dessimoz and Natasha Glover. Read2Tree enables rapid inference of phylogenetic trees directly from raw sequencing data, for a more efficient pipeline and savings on substantial computational and labour costs. If you are interested in comparative genomics, pathogen surveillance or how to efficiently make phylogenetic trees then this talk is a must-watch for you!

About the in silico talks series – The latest in bioinformatics by SIB Scientists

The in silico talks online series aims to inform bioinformaticians, life scientists and clinicians about the latest advances led by SIB Scientists on a wide range of topics in bioinformatics methods, research and resources. Stay abreast of the latest developments, get exclusive insights into recent papers, and discover how these advances might help you in your work or research, by subscribing to the in silico talks mailing list.

Speaker

Name:

David Dylus

Institute:

University of Lausanne

Group:

Comparative Genomics

David Dylus is a senior scientist within the Pharmaceutical Research and Early Development (pRED) division of F. Hoffmann-La Roche Ltd. Following his doctorate in Systems Biology at University College London under the guidance of Paola Oliveri, he continued in research as a Postdoctoral Fellow in the SIB Group of Christophe Dessimoz at the University of Lausanne’s Department of Computational Biology where he contributed to this work on Read2Tree. David then transitioned to the pharmaceutical industry, leveraging his diverse skill set, ranging from benchwork and data analysis to the development of methods and tools. His work now focuses on antibiotic resistance and autoimmune diseases and his current research interests encompass omic data analysis, tool and method development, and knowledge graphs. David is particularly interested in improving the identification of disease-related targets, with the ultimate goal of making a significant positive impact on patient outcomes.