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Cellular phenotypes are determined by the dynamical activity of networks of co-regulated genes. Elucidating such networks is crucial for the understanding of normal cell physiology as well as for the dissection of complex pathologic…

Molecular Networks · Quantitative Biology 2007-05-23 Kai Wang , Nilanjana Banerjee , Adam Margolin , Ilya Nemenman , Katia Basso , Riccardo Favera , Andrea Califano

We consider multivariate two-sample tests of means, where the location shift between the two populations is expected to be related to a known graph structure. An important application of such tests is the detection of differentially…

Applications · Statistics 2012-07-02 Laurent Jacob , Pierre Neuvial , Sandrine Dudoit

Motivated by DNA storage in living organisms, and by known biological mutation processes, we study the reverse-complement string-duplication system. We fully classify the conditions under which the system has full expressiveness, for all…

Information Theory · Computer Science 2021-12-23 Eyar Ben-Tolila , Moshe Schwartz

Gene tree/species tree reconciliation is a recent decisive progress in phylo-genetic methods, accounting for the possible differences between gene histories and species histories. Reconciliation consists in explaining these differences by…

Quantitative Methods · Quantitative Biology 2017-10-05 Damir Hasic , Eric Tannier

Large scale databases are available that contain homologous gene families constructed from hundreds of complete genome sequences from across the three domains of Life. Here we discuss approches of increasing complexity aimed at extracting…

Genomics · Quantitative Biology 2011-02-14 Gergely J Szöllősi , Vincent Daubin

Gene set analysis, a popular approach for analysing high-throughput gene expression data, aims to identify sets of genes that show enriched expression patterns between two conditions. In addition to the multitude of methods available for…

Maximal clique enumeration (MCE) is a fundamental problem in graph theory and is used in many applications, such as social network analysis, bioinformatics, intelligent agent systems, cyber security, etc. Most existing MCE algorithms focus…

Databases · Computer Science 2020-12-01 Xiaofan Li , Rui Zhou , Lu Chen , Chengfei Liu , Qiang He , Yun Yang

The supertree problem asking for a tree displaying a set of consistent input trees has been largely considered for the reconstruction of species trees. Here, we rather explore this framework for the sake of reconstructing a gene tree from a…

Data Structures and Algorithms · Computer Science 2016-10-25 Manuel Lafond , Cédric Chauve , Nadia El-Mabrouk , Aïda Ouangraoua

For two strings u, v over some alphabet A, we investigate the problem of embedding u into w as a subsequence under the presence of generalised gap constraints. A generalised gap constraint is a triple (i, j, C_{i, j}), where 1 <= i < j <=…

Data Structures and Algorithms · Computer Science 2024-04-17 Florin Manea , Jonas Richardsen , Markus L. Schmid

We study the challenges of applying deep learning to gene expression data. We find experimentally that there exists non-linear signal in the data, however is it not discovered automatically given the noise and low numbers of samples used in…

Genomics · Quantitative Biology 2018-06-20 Francis Dutil , Joseph Paul Cohen , Martin Weiss , Georgy Derevyanko , Yoshua Bengio

Gene interaction graphs aim to capture various relationships between genes and represent decades of biology research. When trying to make predictions from genomic data, those graphs could be used to overcome the curse of dimensionality by…

String diagrams provide an intuitive language for expressing networks of interacting processes graphically. A discrete representation of string diagrams, called string graphs, allows for mechanised equational reasoning by double-pushout…

Logic in Computer Science · Computer Science 2015-10-14 Aleks Kissinger , Vladimir Zamdzhiev

Galled trees are widely studied as a recombination model in population genetics. This class of phylogenetic networks is generalized into galled networks by relaxing a structural condition. In this work, a linear recurrence formula is given…

Populations and Evolution · Quantitative Biology 2018-12-21 Andreas DM Gunawan , Jeyaram Rathin , Louxin Zhang

Verifying safety and liveness over array systems is a highly challenging problem. Array systems naturally capture parameterized systems such as distributed protocols with an unbounded number of processes. Such distributed protocols often…

Software Engineering · Computer Science 2024-01-08 Chih-Duo Hong , Anthony W. Lin

A statistical network model with overlapping communities can be generated as a superposition of mutually independent random graphs of varying size. The model is parameterized by the number of nodes, the number of communities, and the joint…

Probability · Mathematics 2024-12-19 Tommi Gröhn , Joona Karjalainen , Lasse Leskelä

Many compilers, synthesizers, and theorem provers rely on rewrite rules to simplify expressions or prove equivalences. Developing rewrite rules can be difficult: rules may be subtly incorrect, profitable rules are easy to miss, and rulesets…

Programming Languages · Computer Science 2021-08-25 Chandrakana Nandi , Max Willsey , Amy Zhu , Yisu Remy Wang , Brett Saiki , Adam Anderson , Adriana Schulz , Dan Grossman , Zachary Tatlock

We introduce a notion of genus range as a set of values of genera over all surfaces into which a graph is embedded cellularly, and we study the genus ranges of a special family of four-regular graphs with rigid vertices that has been used…

Geometric Topology · Mathematics 2012-11-22 Dorothy Buck , Egor Dolzhenko , Natasha Jonoska , Masahico Saito , Karin Valencia

The majority of the human genome consists of repeated sequences. An important type of repeated sequences common in the human genome are tandem repeats, where identical copies appear next to each other. For example, in the sequence…

Information Theory · Computer Science 2016-11-18 Siddharth Jain , Farzad Farnoud , Jehoshua Bruck

Graph Neural Networks are powerful models for learning from graph-structured data, yet their effectiveness is often limited by two critical challenges: over-squashing, where information from distant nodes is excessively compressed, and…

Machine Learning · Computer Science 2026-05-05 Hugo Attali , Nathalie Pernelle , Davide Buscaldi , Fragkiskos D. Malliaros

Graph Neural Networks are powerful models for learning from graph-structured data, yet their effectiveness is often limited by two critical challenges: over-squashing, where information from distant nodes is excessively compressed, and…

Machine Learning · Computer Science 2026-05-04 Hugo Attali , Davide Buscaldi , Nathalie Pernelle , Fragkiskos D. Malliaros
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