Phase transition in the computational complexity of the shortest common superstring and genome assembly.
Phys Rev E
; 109(1-1): 014133, 2024 Jan.
Article
em En
| MEDLINE
| ID: mdl-38366408
ABSTRACT
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 polynomial-time algorithms). In addition, we propose a Markov-chain Monte Carlo method that outperforms common deterministic algorithms in the hard regime.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
Phys Rev E
Ano de publicação:
2024
Tipo de documento:
Article