Bioinformatics is a new and rapidly evolving discipline stemming from the fields of molecular biology and biochemistry, and from the algorithmic disciplines of computer science and mathematics. Many real-world problems of biological relevance can be modelled as computational problems but due to incomplete data, a large number of solutions are proposed, making it difficult to find the right one. The EU-funded SAFEBIO project will derive the first safe algorithms for a number of fundamental algorithmic problems. The aim will be to create automated and efficient ways of reporting all safe sub-solutions for problems. The project will apply these inside practical tools for genome assembly, RNA assembly and pan-genome analysis.
Period: 1 March 2020 - 28 February 2025
Many real-world problems are modeled as computational problems, but unfortunately with incomplete data or knowledge. As such, they may admit a large number of solutions, and we have no way of finding the correct one. This issue is sometimes addressed by outputting all solutions, which is infeasible for many practical problems. We aim to construct a general methodology for finding the set of all sub-solutions common to all solutions. We can ultimately trust these to be part of the correct solution. We call this set safe. Ultimately, we aim at creating automated and efficient ways of reporting all safe sub-solutions of a problem.
The main motivation of this project comes from Bioinformatics, in particular from the analysis of high-throughput sequencing (HTS) of DNA. One of the main applications of HTS data is to assemble it back into the original DNA sequence. This genome assembly problem admits many solutions, and current research has indeed considered outputting only partial solutions that are likely to be present in the correct original DNA sequence. However, this problem has been approached only from an experimental point of view, with no definite answer on what are all the safe sub-solutions to report. In fact, the issue of safe sub-solutions has been mostly overlooked in Bioinformatics and Computer Science in general. This project will derive the first safe algorithms for a number of fundamental problems about walks in graphs, network flows, dynamic programming. We will apply these inside practical tools for genome assembly, RNA assembly and pan-genome analysis.