ArticlebioRxiv : the preprint server for biology2024
An Exact and Fast SAT Formulation for the DCJ Distance.
Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Reducing into a satisfiability (SAT) formulation has been proven effective in solving certain NP-hard problems. In this work, we extend this research by presenting a novel SAT formulation for computing the double-cut-and-join (DCJ) distance between two genomes with duplicate genes. The DCJ distance serves as a crucial metric in studying genome rearrangement. Previous work achieved an exact solution by transforming it into a maximum cycle decomposition (MCD) problem on the corresponding adjacency graph of two genomes, followed by reducing this problem into an integer linear programming (ILP) formulation. Using both simulated datasets and real genomic datasets, we firmly conclude that the SAT-based method scales much better and runs faster than using ILP, being able to solve a whole new range of instances which the ILP-based method cannot solve in a reasonable amount of time. This underscores the SAT-based approach as a versatile and more powerful alternative to ILP, with promising implications for broader applications in computational biology.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.