Approximation algorithm cuts steps in complex genome reordering
An Approximation Algorithm for Non-uniform Non-contiguous Translocation Distance
Data Structures and Algorithms
Summary
The paper deals with a problem of rearranging parts of chromosomes by swapping prefixes, which is important in understanding genome changes. The authors focus on a situation where all intermediate genome pieces stay available for further use. They developed the first efficient method that approximates the minimal number of swaps needed to transform one set of chromosome pieces into another. Their approach works efficiently for both single and multiple target pieces, improving the understanding of how difficult these rearrangements are to approximate.
What this means in practice
- •For bioinformatics teams: Optimize computational tools that compare and transform genome sequences by reducing steps in modeling translocation events.
- •For software engineers in string algorithms: Design better algorithms for transforming complex string sets efficiently when intermediate results are reusable.
A theory result. No direct application yet.
Authors
Maria Constantin, Adrian Miclăuş, Alexandru Popa
Abstract
Translocations are genome rearrangement operations that exchange prefixes of two chromosomes. We study the non-uniform non-contiguous translocation distance problem, where every string produced during the computation remains available for reuse. Given an initial set of strings $A$ and a target set $B$, the objective is to produce all strings in $B$ using as few translocations as possible. We present the first polynomial-time approximation algorithm for this problem. For a single target string of length $n$, we obtain an $O(\log n)$-approximation, and we extend the result to arbitrary finite target sets with an $O(\log N)$-approximation, where $N$ is the total length of the targets not already present in the initial set. This resolves the approximability question for the non-uniform non-contiguous case left open by Constantin and Popa (TCS 2025).