%0 Journal Article
%A Fernández Pérez, Luis Antonio
%A Martín Mayor, Víctor
%A Yllanes, D.
%T Phase transition in the computational complexity of the shortest common superstring and genome assembly
%D 2024
%@ 2470-0045
%U https://hdl.handle.net/20.500.14352/125779
%X Genome assembly, the process of reconstructing a long genetic sequence by aligning and merging short fragments, or reads, is known to be NP-hard, either as a version of the shortest common superstring problem or in a Hamiltonian-cycle formulation. That is, the computing time is believed to grow exponentially with the problem size in the worst case. Despite this fact, high-throughput technologies and modern algorithms currently allow bioinformaticians to handle datasets of billions of reads. Using methods from statistical mechanics, we address this conundrum by demonstrating the existence of a phase transition in the computational complexity of the problem and showing that practical instances always fall in the “easy” phase (solvable by polynomialtime algorithms). In addition, we propose a Markov-chain Monte Carlo method that outperforms common deterministic algorithms in the hard regime.
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