SearcharxivSearch

arXiv subjects

Manuel Lafond

Publications and source records attributed to Manuel Lafond.

At least 19 recordsLinked to original sources

The $\ominus$-metric to compare phylogenetic networks

We introduce two novel distances for comparing rooted phylogenetic networks based on the $\ominus$-operator, which removes a vertex while preserving the ancestor relations among the remaining vertices. The distance $d_{\ominus}$ measures the minimum number of such removals needed to obtain isomorphic networks, whereas $d_{\ominus}^-$ ignores shortcut arcs and therefore compares the induced ancestry structures. We show that $d_{\ominus}$ is a metric up to leaf-fixing isomorphism and that $d_{\ominus}^-$ is a metric up to shortcut-free isomorphism. Moreover, both distances extend the Robinson--Foulds distance on phylogenetic trees and are bounded below by the hardwired cluster distances. For several broad network classes, including tree-child, normal, level-$1$, and regular networks, $d_{\ominus}^-$ can be computed in polynomial time. In contrast, computing $d_{\ominus}$ is NP-hard, W[2]-hard when parameterized by the distance value, and admits no polynomial-time constant-factor approximation unless $\mathrm{P}=\mathrm{NP}$. Although computing $d_{\ominus}^-$ is NP-hard in general, for distinct-cluster networks it reduces to \textsc{Vertex Cover}, yielding a fixed-parameter algorithm and a polynomial-time $2$-approximation.

cs.DM

A $O^*((2 + \epsilon)^k)$ Time Algorithm for Cograph Deletion Using Unavoidable Subgraphs in Large Prime Graphs

We study the parameterized complexity of the Cograph Deletion problem, which asks whether one can delete at most $k$ edges from a graph to make it $P_4$-free. This is a well-known graph modification problem with applications in computation biology and social network analysis. All current parameterized algorithms use a similar strategy, which is to find a $P_4$ and explore the local structure around it to perform an efficient recursive branching. The best known algorithm achieves running time $O^*(2.303^k)$ and requires an automated search of the branching cases due to their complexity. Since it appears difficult to further improve the current strategy, we devise a new approach using modular decompositions. We solve each module and the quotient graph independently, with the latter being the core problem. This reduces the problem to solving on a prime graph, in which all modules are trivial. We then use a characterization of Chudnovsky et al. stating that any large enough prime graph has one of seven structures as an induced subgraph. These all have many $P_4$s, with the quantity growing linearly with the graph size, and we show that these allow a recursive branch tree algorithm to achieve running time $O^*((2 + \epsilon)^k)$ for any $\epsilon > 0$. This appears to be the first algorithmic application of the prime graph characterization and it could be applicable to other modification problems. Towards this goal, we provide the exact set of graph classes $\H$ for which the $\H$-free editing problem can make use of our reduction to a prime graph, opening the door to improvements for other modification problems.

cs.DS

On the hardness of recognizing graphs of small mim-width and its variants

The mim-width of a graph is a powerful structural parameter that, when bounded by a constant, allows several hard problems to be polynomial-time solvable - with a recent meta-theorem encompassing a large class of problems [SODA2023]. Since its introduction, several variants such as sim-width and omim-width were developed, along with a linear version of these parameters. It was recently shown that mim-width and all these variants all paraNP-hard, a consequence of the NP-hardness of distinguishing between graphs of linear mim-width at most 1211 and graphs of sim-width at least 1216 [ICALP2025]. The complexity of recognizing graphs of small width, particularly those close to $1$, remained open, despite their especially attractive algorithmic applications. In this work, we show that the width recognition problems remain NP-hard even on small widths. Specifically, after introducing the novel parameter Omim-width sandwiched between omim-width and mim-width, we show that: (1) deciding whether a graph has sim-width = 1, omim-width = 1, or Omin-width = 1 is NP-hard, and the same is true for their linear variants; (2) the problems of deciding whether mim-width $\leq$ 2 or linear mim-width $\leq$ 2 are both NP-hard. Interestingly, our reductions are relatively simple and are from the Unrooted Quartet Consistency problem, which is of great interest in computational biology but is not commonly used (if ever) in the theory of algorithms.

cs.DM

Recognizing Leaf Powers and Pairwise Compatibility Graphs is NP-Complete

Leaf powers and pairwise compatibility graphs were introduced over twenty years ago as simplified graph models for phylogenetic trees. Despite significant research, several properties of these graph classes remain poorly understood. In this paper, we establish that the recognition problem for both classes is NP-complete. We extend this hardness result to a broader hierarchy of graph classes, including pairwise compatibility graphs and their generalizations, multi interval pairwise compatibility graphs.

math.CO

Eukaryotic ancestry in a finite world

Following genetic ancestry in eukaryote populations poses several open problems due to sexual reproduction and recombination. The history of extant genetic material is usually modeled backwards in time, but tracking chromosomes at a large scale is not trivial, as successive recombination events break them into several segments. For this reason, the behavior of the distribution of genetic segments across the ancestral population is not fully understood. Moreover, as individuals transmit only half of their genetic content to their offspring, after a few generations, it is possible that ghosts arise, that is, genealogical ancestors that transmit no genetic material to any individual. While several theoretical predictions exist to estimate properties of ancestral segments or ghosts, most of them rely on simplifying assumptions such as an infinite population size or an infinite chromosome length. It is not clear how well these results hold in a finite universe, and current simulators either make other approximations or cannot handle the scale required to answer these questions. In this work, we use an exact back-in-time simulator of large diploid populations experiencing recombination that tracks genealogical and genetic ancestry, without approximations. We focus on the distinction between genealogical and genetic ancestry and, additionally, we explore the effects of genome structure on ancestral segment distribution and the proportion of genetic ancestors. Our study reveals that some of the theoretical predictions hold well in practice, but that, in several cases, it highlights discrepancies between theoretical predictions assuming infinite parameters and empirical results in finite populations, emphasizing the need for cautious application of mathematical models in biological contexts.

q-bio.PE

Novel Complexity Results for Temporal Separators with Deadlines

We consider two variants, (s,z,l)-Temporal Separator and (s,z,l)-Temporal Cut, respectively, of the vertex separator and the edge cut problem in temporal graphs. The goal is to remove the minimum number of vertices (temporal edges, respectively) in order to delete all the temporal paths that have time travel at most l between a source vertex s and target vertex z. First, we solve an open problem in the literature showing that (s,z,l)-Temporal Separator is NP-complete even when the underlying graph has pathwidth bounded by four. We complement this result showing that (s,z,l)-Temporal Separator can be solved in polynomial time for graphs of pathwidth bounded by three. Then we consider the approximability of (s,z,l)-Temporal Separator and we show that it cannot be approximated within factor$2^{\Omega(\log^{1-\varepsilon}|V|)}$ for any constant $\varepsilon> 0$, unless $NP \subseteq ZPP$ (V is the vertex set of the input temporal graph) and that the strict version is approximable within factor l - 1 (we show also that it is unliklely that this factor can be improved). Then we consider the (s,z,l)-Temporal Cut problem, we show that it is APX-hard and we present a $2 \log_2(2\ell)$ approximation algorithm.

cs.DS

The Parameterized Landscape of Labeled Graph Contractions

In this work, we study the problem of computing a maximum common contraction of two vertex-labeled graphs, i.e. how to make them identical by contracting as little edges as possible in the two graphs. We study the problem from a parameterized complexity point of view, using parameters such as the maximum degree, the degeneracy, the clique-width or treewidth of the input graphs as well as the number of allowed contractions. We put this complexity in perspective with that of the labeled contractibility problem, i.e determining whether a labeled graph is a contraction of another. Surprisingly, our results indicate very little difference between these problems in terms of parameterized complexity status. We only prove their status to differ when parameterizing by both the degeneracy and the number of allowed contractions, showing W[1]-hardness of the maximum common contraction problem in this case, whereas the contractibility problem is FPT.

cs.DS

Cluster Editing on Cographs and Related Classes

In the Cluster Editing problem, sometimes known as (unweighted) Correlation Clustering, we must insert and delete a minimum number of edges to achieve a graph in which every connected component is a clique. Owing to its applications in computational biology, social network analysis, machine learning, and others, this problem has been widely studied for decades and is still undergoing active research. There exist several parameterized algorithms for general graphs, but little is known about the complexity of the problem on specific classes of graphs. Among the few important results in this direction, if only deletions are allowed, the problem can be solved in polynomial time on cographs, which are the $P_4$-free graphs. However, the complexity of the broader editing problem on cographs is still open. We show that even on a very restricted subclass of cographs, the problem is NP-hard, W[1]-hard when parameterized by the number $p$ of desired clusters, and that time $n^{o(p/\log p)}$ is forbidden under the ETH. This shows that the editing variant is substantially harder than the deletion-only case, and that hardness holds for the many superclasses of cographs (including graphs of clique-width at most $2$, perfect graphs, circle graphs, permutation graphs). On the other hand, we provide an almost tight upper bound of time $n^{O(p)}$, which is a consequence of a more general $n^{O(cw \cdot p)}$ time algorithm, where $cw$ is the clique-width. Given that forbidding $P_4$s maintains NP-hardness, we look at $\{P_4, C_4\}$-free graphs, also known as trivially perfect graphs, and provide a cubic-time algorithm for this class.

cs.DS

Improved Kernelization and Fixed-parameter Algorithms for Bicluster Editing

Given a bipartite graph $G$, the \textsc{Bicluster Editing} problem asks for the minimum number of edges to insert or delete in $G$ so that every connected component is a bicluster, i.e. a complete bipartite graph. This has several applications, including in bioinformatics and social network analysis. In this work, we study the parameterized complexity under the natural parameter $k$, which is the number of allowed modified edges. We first show that one can obtain a kernel with $4.5k$ vertices, an improvement over the previously known quadratic kernel. We then propose an algorithm that runs in time $O^*(2.581^k)$. Our algorithm has the advantage of being conceptually simple and should be easy to implement.

cs.DS

Galled Perfect Transfer Networks

Predicting horizontal gene transfers often requires comparative sequence data, but recent work has shown that character-based approaches could also be useful for this task. Notably, perfect transfer networks (PTN) explain the character diversity of a set of taxa for traits that are gained once, rarely lost, but that can be transferred laterally. Characterizing the structure of such characters is an important step towards understanding more complex characters. Although efficient algorithms can infer such networks from character data, they can sometimes predict overly complicated transfer histories. With the goal of recovering the simplest possible scenarios in this model, we introduce galled perfect transfer networks, which are PTNs that are galled trees. Such networks are useful for characters that are incompatible in terms of tree-like evolution, but that do fit in an almost-tree scenario. We provide polynomial-time algorithms for two problems: deciding whether one can add transfer edges to a tree to transform it into a galled PTN, and deciding whether a set of characters are galled-compatible, that is, they can be explained by some galled PTN. We also analyze a real dataset comprising of a bacterial species trees and KEGG functions as characters, and derive several conclusions on the difficulty of explaining characters in a galled tree, which provide several directions for future research.

cs.DM

Path Partitions of Phylogenetic Networks

In phylogenetics, evolution is traditionally represented in a tree-like manner. However, phylogenetic networks can be more appropriate for representing evolutionary events such as hybridization, horizontal gene transfer, and others. In particular, the class of forest-based networks was recently introduced to represent introgression, in which genes are swapped between between species. A network is forest-based if it can be obtained by adding arcs to a collection of trees, so that the endpoints of the new arcs are in different trees. This contrasts with so-called tree-based networks, which are formed by adding arcs within a single tree. We are interested in the computational complexity of recognizing forest-based networks, which was recently left as an open problem by Huber et al. Forest-based networks coincide with directed acyclic graphs that can be partitioned into induced paths, each ending at a leaf of the original graph. Several types of path partitions have been studied in the graph theory literature, but to our knowledge this type of leaf induced path partition has not been considered before. The study of forest-based networks in terms of these partitions allows us to establish closer relationships between phylogenetics and algorithmic graph theory, and to provide answers to problems in both fields. We show that deciding whether a network is forest-based is NP-complete, even on input networks that are tree-based, binary, and have only three leaves. This shows that partitioning a directed acyclic graph into three induced paths is NP-complete, answering a recent question of Fernau et al. We then show that the problem is polynomial-time solvable on binary networks with two leaves and on the class of orchards. Finally, for undirected graphs, we introduce unrooted forest-based networks and provide hardness results for this class as well.

cs.DS

The Path-Label Reconciliation (PLR) Dissimilarity Measure for Gene Trees

In this study, we investigate the problem of comparing gene trees reconciled with the same species tree using a novel semi-metric, called the Path-Label Reconciliation (PLR) dissimilarity measure. This approach not only quantifies differences in the topology of reconciled gene trees, but also considers discrepancies in predicted ancestral gene-species maps and speciation/duplication events, offering a refinement of existing metrics such as Robinson-Foulds (RF) and their labeled extensions LRF and ELRF. A tunable parameter {\alpha} also allows users to adjust the balance between its species map and event labeling components. We show that PLR can be computed in linear time and that it is a semi-metric. We also discuss the diameters of reconciled gene tree measures, which are important in practice for normalization, and provide initial bounds on PLR, LRF, and ELRF. To validate PLR, we simulate reconciliations and perform comparisons with LRF and ELRF. The results show that PLR provides a more evenly distributed range of distances, making it less susceptible to overestimating differences in the presence of small topological changes, while at the same time being computationally efficient. Our findings suggest that the theoretical diameter is rarely reached in practice. The PLR measure advances phylogenetic reconciliation by combining theoretical rigor with practical applicability. Future research will refine its mathematical properties, explore its performance on different tree types, and integrate it with existing bioinformatics tools for large-scale evolutionary analyses. The open source code is available at: https://pypi.org/project/parle/.

cs.DM

$k$-Leaf Powers Cannot be Characterized by a Finite Set of Forbidden Induced Subgraphs for $k \geq 5$

A graph $G=(V,E)$ is a $k$-leaf power if there is a tree $T$ whose leaves are the vertices of $G$ with the property that a pair of leaves $u$ and $v$ induce an edge in $G$ if and only if they are distance at most $k$ apart in $T$. For $k\le 4$, it is known that there exists a finite set $F_k$ of graphs such that the class $L(k)$ of $k$-leaf power graphs is characterized as the set of strongly chordal graphs that do not contain any graph in $F_k$ as an induced subgraph. We prove no such characterization holds for $k\ge 5$. That is, for any $k\ge 5$, there is no finite set $F_k$ of graphs such that $L(k)$ is equivalent to the set of strongly chordal graphs that do not contain as an induced subgraph any graph in $F_k$.

math.CO

Finding Maximum Common Contractions Between Phylogenetic Networks

In this paper, we lay the groundwork on the comparison of phylogenetic networks based on edge contractions and expansions as edit operations, as originally proposed by Robinson and Foulds to compare trees. We prove that these operations connect the space of all phylogenetic networks on the same set of leaves, even if we forbid contractions that create cycles. This allows to define an operational distance on this space, as the minimum number of contractions and expansions required to transform one network into another. We highlight the difference between this distance and the computation of the maximum common contraction between two networks. Given its ability to outline a common structure between them, which can provide valuable biological insights, we study the algorithmic aspects of the latter. We first prove that computing a maximum common contraction between two networks is NP-hard, even when the maximum degree, the size of the common contraction, or the number of leaves is bounded. We also provide lower bounds to the problem based on the Exponential-Time Hypothesis. Nonetheless, we do provide a polynomial-time algorithm for weakly-galled trees, a generalization of galled trees.

cs.DS

Median and Small Parsimony Problems on RNA trees

Motivation: Non-coding RNAs (ncRNAs) express their functions by adopting molecular structures. Specifically, RNA secondary structures serve as a relatively stable intermediate step before tertiary structures, offering a reliable signature of molecular function. Consequently, within an RNA functional family, secondary structures are generally more evolutionarily conserved than sequences. Conversely, homologous RNA families grouped within an RNA clan share ancestors but typically exhibit structural differences. Inferring the evolution of RNA structures within RNA families and clans is crucial for gaining insights into functional adaptations over time and providing clues about the Ancient RNA World Hypothesis. Results: We introduce the median problem and the small parsimony problem for ncRNA families, where secondary structures are represented as leaf-labelled trees. We utilize the Robinson-Foulds (RF) tree distance, which corresponds to a specific edit distance between RNA trees, and a new metric called the Internal-Leafset (IL) distance. While the RF tree distance compares sets of leaves descending from internal nodes of two RNA trees, the IL distance compares the collection of leaf-children of internal nodes. The latter is better at capturing differences in structural elements of RNAs than the RF distance, which is more focused on base pairs. We also consider a more general tree edit distance that allows the mapping of base pairs that are not perfectly aligned. We study the theoretical complexity of the median problem and the small parsimony problem under the three distance metrics and various biologically-relevant constraints, and we present polynomial-time maximum parsimony algorithms for solving some versions of the problems. Our algorithms are applied to ncRNA families from the RFAM database, illustrating their practical utility

cs.DS

Predicting Horizontal Gene Transfers with Perfect Transfer Networks

Horizontal gene transfer inference approaches are usually based on gene sequences: parametric methods search for patterns that deviate from a particular genomic signature, while phylogenetic methods use sequences to reconstruct the gene and species trees. However, it is well-known that sequences have difficulty identifying ancient transfers since mutations have enough time to erase all evidence of such events. In this work, we ask whether character-based methods can predict gene transfers. Their advantage over sequences is that homologous genes can have low DNA similarity, but still have retained enough important common motifs that allow them to have common character traits, for instance the same functional or expression profile. A phylogeny that has two separate clades that acquired the same character independently might indicate the presence of a transfer even in the absence of sequence similarity. We introduce perfect transfer networks, which are phylogenetic networks that can explain the character diversity of a set of taxa under the assumption that characters have unique births, and that once a character is gained it is rarely lost. Examples of such traits include transposable elements, biochemical markers and emergence of organelles, just to name a few. We study the differences between our model and two similar models: perfect phylogenetic networks and ancestral recombination networks. Our goals are to initiate a study on the structural and algorithmic properties of perfect transfer networks. We then show that in polynomial time, one can decide whether a given network is a valid explanation for a set of taxa, and show how, for a given tree, one can add transfer edges to it so that it explains a set of taxa. We finally provide lower and upper bounds on the number of transfers required to explain a set of taxa, in the worst case.

cs.DM

The Longest Subsequence-Repeated Subsequence Problem

Motivated by computing duplication patterns in sequences, a new fundamental problem called the longest subsequence-repeated subsequence (LSRS) is proposed. Given a sequence $S$ of length $n$, a letter-repeated subsequence is a subsequence of $S$ in the form of $x_1^{d_1}x_2^{d_2}\cdots x_k^{d_k}$ with $x_i$ a subsequence of $S$, $x_j\neq x_{j+1}$ and $d_i\geq 2$ for all $i$ in $[k]$ and $j$ in $[k-1]$. We first present an $O(n^6)$ time algorithm to compute the longest cubic subsequences of all the $O(n^2)$ substrings of $S$, improving the trivial $O(n^7)$ bound. Then, an $O(n^6)$ time algorithm for computing the longest subsequence-repeated subsequence (LSRS) of $S$ is obtained. Finally we focus on two variants of this problem. We first consider the constrained version when $Σ$ is unbounded, each letter appears in $S$ at most $d$ times and all the letters in $Σ$ must appear in the solution. We show that the problem is NP-hard for $d=4$, via a reduction from a special version of SAT (which is obtained from 3-COLORING). We then show that when each letter appears in $S$ at most $d=3$ times, then the problem is solvable in $O(n^5)$ time.

cs.DS

Relative Timing Information and Orthology in Evolutionary Scenarios

Evolutionary scenarios describing the evolution of a family of genes within a collection of species comprise the mapping of the vertices of a gene tree $T$ to vertices and edges of a species tree $S$. The relative timing of the last common ancestors of two extant genes (leaves of $T$) and the last common ancestors of the two species (leaves of $S$) in which they reside is indicative of horizontal gene transfers (HGT) and ancient duplications. Orthologous gene pairs, on the other hand, require that their last common ancestors coincides with a corresponding speciation event. The relative timing information of gene and species divergences is captured by three colored graphs that have the extant genes as vertices and the species in which the genes are found as vertex colors: the equal-divergence-time (EDT) graph, the later-divergence-time (LDT) graph and the prior-divergence-time (PDT) graph, which together form an edge partition of the complete graph. Here we give a complete characterization in terms of informative and forbidden triples that can be read off the three graphs and provide a polynomial time algorithm for constructing an evolutionary scenario that explains the graphs, provided such a scenario exists. We show that every EDT graph is perfect. While the information about LDT and PDT graphs is necessary to recognize EDT graphs in polynomial-time for general scenarios, this extra information can be dropped in the HGT-free case. However, recognition of EDT graphs without knowledge of putative LDT and PDT graphs is NP-complete for general scenarios. In contrast, PDT graphs can be recognized in polynomial-time. We finally connect the EDT graph to the alternative definitions of orthology that have been proposed for scenarios with horizontal gene transfer. With one exception, the corresponding graphs are shown to be colored cographs.

q-bio.PE