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Reconciling gene trees with a species tree is a fundamental problem to understand the evolution of gene families. Many existing approaches reconcile each gene tree independently. However, it is well-known that the evolution of gene families…

Populations and Evolution · Quantitative Biology 2018-06-12 Riccardo Dondi , Manuel Lafond , Celine Scornavacca

We consider the process of uncovering the vertices of a random labeled tree according to their labels. First, a labeled tree with $n$ vertices is generated uniformly at random. Thereafter, the vertices are uncovered one by one, in order of…

Probability · Mathematics 2023-01-03 Benjamin Hackl , Alois Panholzer , Stephan Wagner

Neural Networks and Decision Trees: two popular techniques for supervised learning that are seemingly disconnected in their formulation and optimization method, have recently been combined in a single construct. The connection pivots on…

Machine Learning · Statistics 2020-02-27 Giuseppe Nuti , Lluís Antoni Jiménez Rugama , Kaspar Thommen

We show that the problem of constructing tree-structured descriptions of data layouts that are optimal with respect to space or other criteria from given sequences of displacements, can be solved in polynomial time. The problem is relevant…

Data Structures and Algorithms · Computer Science 2015-07-01 Robert Ganian , Martin Kalany , Stefan Szeider , Jesper Larsson Träff

An important problem in evolutionary biology is to reconstruct the evolutionary history of a set $X$ of species. This history is often represented as a phylogenetic network, that is, a connected graph with leaves labelled by elements in $X$…

Combinatorics · Mathematics 2017-02-01 Leo van Iersel , Vincent Moulton

The tree-metric theorem provides a necessary and sufficient condition for a dissimilarity matrix to be a tree metric, and has served as the foundation for numerous distance-based reconstruction methods in phylogenetics. Our main result is…

Combinatorics · Mathematics 2007-05-23 Lior Pachter , David E Speyer

We consider the problem of reconstructing an undirected graph $G$ on $n$ vertices given multiple random noisy subgraphs or "traces". Specifically, a trace is generated by sampling each vertex with probability $p_v$, then taking the…

Information Theory · Computer Science 2025-08-01 Andrew McGregor , Rik Sengupta

Learning vector representations for programs is a critical step in applying deep learning techniques for program understanding tasks. Various neural network models are proposed to learn from tree-structured program representations, e.g.,…

Software Engineering · Computer Science 2023-01-10 Wenhan Wang , Kechi Zhang , Ge Li , Shangqing Liu , Anran Li , Zhi Jin , Yang Liu

In the trace reconstruction problem an unknown string ${\bf x}=(x_0,\dots,x_{n-1})\in\{0,1,...,m-1\}^n$ is observed through the deletion channel, which deletes each $x_k$ with a certain probability, yielding a contracted string…

Probability · Mathematics 2017-08-08 Lisa Hartung , Nina Holden , Yuval Peres

The reconstruction of a species phylogeny from genomic data faces two significant hurdles: 1) the trees describing the evolution of each individual gene--i.e., the gene trees--may differ from the species phylogeny and 2) the molecular…

Machine Learning · Computer Science 2017-07-17 Gautam Dasarathy , Elchanan Mossel , Robert Nowak , Sebastien Roch

The problem of string reconstruction from substring information has found many applications due to its relevance in DNA- and polymer-based data storage. One practically important and challenging paradigm requires reconstructing mixtures of…

Information Theory · Computer Science 2020-10-22 Ryan Gabrys , Srilakshmi Pattabiraman , Olgica Milenkovic

General graphs are difficult for learning due to their irregular structures. Existing works employ message passing along graph edges to extract local patterns using customized graph kernels, but few of them are effective for the integration…

Computer Vision and Pattern Recognition · Computer Science 2020-07-23 Yecheng Lyu , Ming Li , Xinming Huang , Ulkuhan Guler , Patrick Schaumont , Ziming Zhang

Invariants for complicated objects such as those arising in phylogenetics, whether they are invariants as matrices, polynomials, or other mathematical structures, are important tools for distinguishing and working with such objects. In this…

Populations and Evolution · Quantitative Biology 2022-04-06 Joan Carles Pons , Tomás M. Coronado , Michael Hendriksen , Andrew Francis

Phylogenomics commonly aims to construct evolutionary trees from genomic sequence information. One way to approach this problem is to first estimate event-labeled gene trees (i.e., rooted trees whose non-leaf vertices are labeled by…

Combinatorics · Mathematics 2019-05-09 Marc Hellmuth , Katharina T. Huber , Vincent Moulton

Motivation: Millions of genes in the modern species belong to only thousands of `gene families'. A gene family includes instances of the same gene in different species (orthologs) and duplicate genes in the same species (paralogs). Genes…

Populations and Evolution · Quantitative Biology 2012-05-04 Yu Zheng , Taoyang Wu , Louxin Zhang

We provide a short combinatorial proof of Cayley's formula by means of a bijective map to an outcome space of an urn-drawing problem. Furthermore we introduce an algebraic structure on the set of labeled trees, which provides a more…

Combinatorics · Mathematics 2011-02-01 Victor N. Ermolaev , Giulio Iacobelli

The reconstruction of phylogenetic networks is an important but challenging problem in phylogenetics and genome evolution, as the space of phylogenetic networks is vast and cannot be sampled well. One approach to the problem is to solve the…

Populations and Evolution · Quantitative Biology 2023-04-14 Louxin Zhang , Niloufar Abhari , Caroline Colijn , Yufeng Wu

Recovering a tree that represents the evolutionary history of a group of species is a key task in phylogenetics. Performing this task using sequence data from multiple genetic markers poses two key challenges. The first is the discordance…

Populations and Evolution · Quantitative Biology 2026-03-12 Ortal Reshef , Ofer Glassman , Or Zuk , Yariv Aizenbud , Boaz Nadler , Ariel Jaffe

\emph{Population recovery} is the problem of learning an unknown distribution over an unknown set of $n$-bit strings, given access to independent draws from the distribution that have been independently corrupted according to some noise…

Data Structures and Algorithms · Computer Science 2019-04-12 Frank Ban , Xi Chen , Adam Freilich , Rocco A. Servedio , Sandip Sinha

Tree-based phylogenetic networks, which may be roughly defined as leaf-labeled networks built by adding arcs only between the original tree edges, have elegant properties for modeling evolutionary histories. We answer an open question of…

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