The availability of large molecular data demands accurate and fast bioinformatics methods to analyze these data. Molecular sequences of common origin are used to infer phylogenetic trees, which help to test various biological hypotheses or to support subsequent analyses. Phylogeny inference relies on sequence alignments, which are usually inferred during a heuristic search navigated by a guide-tree. This circularity calls for methods for joint inference of phylogeny and alignment. This project will develop a fast and practical solution.
The goal is to develop a fast and accurate joint alignment and tree inference algorithm in the frequentist framework, which will be implemented in a user-friendly software package and applicable to large genomic and metagenomic datasets with of sequences.
The aim of the project is to develop tools for the medical community to use to quantify and analyze the 3D shapes of aneurisms and to test the hypothesis that aneurysm 3D shape can be used as a proxy for disease status.
The project AneuX is a collaborative venture led by Dr. Philippe Bijlenga of the Department of Clinical Neurosciences of the University of Geneva Hospital. Additional Swiss partners are ETH Prof. Niels Kuster of the IT'IS Foundation, Dr. Sven Hirsch of the Institute of Applied Simulation (ZHAW), Prof. Brenda Kwak of the Department of Pathology and Immunology of the University of Geneva, Prof. Brigitte von Rechenberg of the University of Zurich Vetsuisse Faculty Equine Department, and Prof. Daniel Rüfenacht of the University of Zurich Center for Applied Biotechnology and Molecular Medicine.