Mod/Resc Parsimony Inference

TL;DR

This paper introduces the Mod/Resc Parsimony Inference problem in computational biology, linking it to bipartite biclique edge cover, and offers new algorithms with experimental validation on real data.

Contribution

It formalizes the Mod/Resc Parsimony Inference problem, establishes its equivalence to bipartite biclique edge cover, and develops improved fixed-parameter tractability algorithms.

Findings

Complexity results for the problem established.

New fixed-parameter algorithms with improved performance.

Successful application to real-life biological data.

Abstract

We address in this paper a new computational biology problem that aims at understanding a mechanism that could potentially be used to genetically manipulate natural insect populations infected by inherited, intra-cellular parasitic bacteria. In this problem, that we denote by \textsc{Mod/Resc Parsimony Inference}, we are given a boolean matrix and the goal is to find two other boolean matrices with a minimum number of columns such that an appropriately defined operation on these matrices gives back the input. We show that this is formally equivalent to the \textsc{Bipartite Biclique Edge Cover} problem and derive some complexity results for our problem using this equivalence. We provide a new, fixed-parameter tractability approach for solving both that slightly improves upon a previously published algorithm for the \textsc{Bipartite Biclique Edge Cover}. Finally, we present experimental results where we applied some of our techniques to a real-life data set.