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Predicting protein-protein interactions from sequences is an important goal of computational biology. Various sources of information can be used to this end. Starting from the sequences of two interacting protein families, one can use…

Biomolecules · Quantitative Biology 2023-04-26 Carlos A. Gandarilla-Perez , Sergio Pinilla , Anne-Florence Bitbol , Martin Weigt

Historical linguistics aims at inferring the most likely language phylogenetic tree starting from information concerning the evolutionary relatedness of languages. The available information are typically lists of homologous (lexical,…

Physics and Society · Physics 2015-05-27 Simone Pompei , Vittorio Loreto , Francesca Tria

Survival analysis concerns the task of predicting the time until an event occurs. Often used in the medical field, survival analysis deals with incomplete (i.e., censored) data, for instance, from patients who did not experience the event…

Machine Learning · Computer Science 2026-05-29 Thalea Schlender , Peter A. N. Bosman , Tanja Alderliesten

Rooted phylogenetic networks provide a more complete representation of the ancestral relationship between species than phylogenetic trees when reticulate evolutionary processes are at play. One way to reconstruct a phylogenetic network is…

Combinatorics · Mathematics 2020-12-02 Allan Bai , Peter Erdos , Charles Semple , Mike Steel

Balanced minimum evolution is a distance-based criterion for the reconstruction of phylogenetic trees. Several algorithms exist to find the optimal tree with respect to this criterion. One approach is to minimize a certain linear functional…

Combinatorics · Mathematics 2019-05-23 Cassandra Durell , Stefan Forcey

Matrix factorization is an inference problem that has acquired importance due to its vast range of applications that go from dictionary learning to recommendation systems and machine learning with deep networks. The study of its fundamental…

Disordered Systems and Neural Networks · Physics 2023-08-01 Francesco Camilli , Marc Mézard

The use of machine learning algorithms in finance, medicine, and criminal justice can deeply impact human lives. As a consequence, research into interpretable machine learning has rapidly grown in an attempt to better control and fix…

Machine Learning · Computer Science 2021-02-02 Thibaut Vidal , Toni Pacheco , Maximilian Schiffer

Tree shape statistics quantify some aspect of the shape of a phylogenetic tree. They are commonly used to compare reconstructed trees to evolutionary models and to find evidence of tree reconstruction bias. Historically, to find a useful…

Populations and Evolution · Quantitative Biology 2007-05-23 Frederick A. Matsen

One of the goals of phylogenetic research is to find the species tree describing the evolutionary history of a set of species. But the trees derived from geneti data with the help of tree inference methods are gene trees that need not…

Populations and Evolution · Quantitative Biology 2015-07-28 Mareike Fischer , Martin Kreidl

In this paper we present a novel tool to evaluate problem solving systems. Instead of using a system to solve a problem, we suggest using the problem to evaluate the system. By finding a numerical representation of a problem's complexity,…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Goren Gordon , Uri Einziger-Lowicz

Reconciliation methods aim at recovering macro evolutionary events and at localizing them in the species history, by observing discrepancies between gene family trees and species trees. In this article we introduce an Integer Linear…

Populations and Evolution · Quantitative Biology 2014-10-28 Leo van Iersel , Celine Scornavacca , Steven Kelk

We present an algorithm that enumerates all the minimal triangulations of a graph in incremental polynomial time. Consequently, we get an algorithm for enumerating all the proper tree decompositions, in incremental polynomial time, where…

Data Structures and Algorithms · Computer Science 2023-07-28 Nofar Carmeli , Batya Kenig , Benny Kimelfeld , Markus Kröll

Grouping elements into families to analyse them separately is a standard analysis procedure in many areas of sciences. We propose herein a new algorithm based on the simple idea that members from a family look like each other, and don't…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Axel Descamps , Sélène Forget , Aliénor Lahlou , Claire Lavergne , Camille Berthelot , Guillaume Stirnemann , Rodolphe Vuilleumier , Nicolas Chéron

Multiple sequence alignment is a basic procedure in molecular biology, and it is often treated as being essentially a solved computational problem. However, this is not so, and here I review the evidence for this claim, and outline the…

Populations and Evolution · Quantitative Biology 2018-08-24 David A. Morrison

Distance-based approaches in phylogenetics such as Neighbor-Joining are a fast and popular approach for building trees. These methods take pairs of sequences from them construct a value that, in expectation, is additive under a stochastic…

Populations and Evolution · Quantitative Biology 2008-08-21 Mike Steel

In recent years the importance of finding a meaningful pattern from huge datasets has become more challenging. Data miners try to adopt innovative methods to face this problem by applying feature selection methods. In this paper we propose…

Machine Learning · Computer Science 2014-03-11 Mehdi Naseriparsa , Amir-masoud Bidgoli , Touraj Varaee

It is proposed that the co-expression of statistically significant motifs among the sequences of a proteome is a phylogenetic trait. From the co-expression matrix of such motifs in a group of prokaryotic proteomes a suitable definition of a…

Molecular Networks · Quantitative Biology 2007-05-23 Luca Ferraro , Andrea Giansanti , Giovanni Giuliano , Vittorio Rosato

By providing a framework of accounting for the shared ancestry inherent to all life, phylogenetics is becoming the statistical foundation of biology. The importance of model choice continues to grow as phylogenetic models continue to…

Populations and Evolution · Quantitative Biology 2019-02-05 Jamie R. Oaks , Kerry A. Cobb , Vladimir N. Minin , Adam D. Leaché

The renormalization group has proven to be a very powerful tool in physics for treating systems with many length scales. Here we show how it can be adapted to provide a new class of algorithms for discrete optimization. The heart of our…

Disordered Systems and Neural Networks · Physics 2009-10-31 J. Houdayer , O. C. Martin

The range of applications of traditional optimization methods are limited by the features of the object variables, and of both the objective and the constraint functions. In contrast, population-based algorithms whose optimization…

Neural and Evolutionary Computing · Computer Science 2021-01-27 Mauro S. Innocente , Johann Sienz
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