Demo Data from EDBT 2026 / reviewers in the wild / expert
Laurent Guéguen
dblp:51/5931
· DBLP profile ↗
6ranked-venue papers
1as first author
0since 2021 · last 2020
0000-0001-7838-791XORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 5 · 1 first-authorArtificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
3 papers |
Bioinformatics and computational biology · 100% | |
| Artificial intelligence
1 paper |
3D vision · 100% |
Topics — the 10 heaviest of 11, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › phylogenetics
gene tree reconciliation |
0.4 | 1 | 2020 | Treerecs: an integrated phylogenetic tool, from sequences to reconciliations · Bioinform. 2020 |
Bioinformatics and computational biology
phylogenetics |
0.4 | 1 | 2020 | Treerecs: an integrated phylogenetic tool, from sequences to reconciliations · Bioinform. 2020 |
Bioinformatics and computational biology › statistical genetics › genetic mapping
genetic map analysis |
0.1 | 1 | 2007 | MareyMap: an R-based tool with graphical interface for estimating recombination rates · Bioinform. 2007 |
Bioinformatics and computational biology
genomics |
0.1 | 1 | 2007 | MareyMap: an R-based tool with graphical interface for estimating recombination rates · Bioinform. 2007 |
Bioinformatics and computational biology › population genetics › recombination
recombination rate estimation |
0.1 | 1 | 2007 | MareyMap: an R-based tool with graphical interface for estimating recombination rates · Bioinform. 2007 |
Bioinformatics and computational biology
sequence analysis |
0.1 | 1 | 2005 | Sarment: Python modules for HMM analysis and partitioning of sequences · Bioinform. 2005 |
Bioinformatics and computational biology › sequence analysis › sequence annotation
sequence segmentation |
0.1 | 1 | 2005 | Sarment: Python modules for HMM analysis and partitioning of sequences · Bioinform. 2005 |
Computer vision › 3D vision › stereo vision
binocular stereo |
0.0 | 1 | 1994 | Genetic Algorithms applied to Binocular Stereovision · ECCV (2) 1994 |
Computer vision › 3D vision
stereo vision |
0.0 | 1 | 1994 | Genetic Algorithms applied to Binocular Stereovision · ECCV (2) 1994 |
Mathematical optimization
evolutionary computation |
0.0 | 1 | 1994 | Genetic Algorithms applied to Binocular Stereovision · ECCV (2) 1994 |
Methods — techniques the papers use, named apart from their topics
duplication-loss reconciliation · 0.4maximal predictive partitioning · 0.1hidden markov model · 0.1interpolation methods · 0.1genetic algorithm · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Treerecs: an integrated phylogenetic tool, from sequences to reconciliationsabstractMOTIVATION: Gene and species tree reconciliation methods are used to interpret gene trees, root them and correct uncertainties that are due to scarcity of signal in multiple sequence alignments. So far, reconciliation tools have not been integrated in standard phylogenetic software and they either lack performance on certain functions, or usability for biologists. RESULTS: We present Treerecs, a phylogenetic software based on duplication-loss reconciliation. Treerecs is simple to install and to use. It is fast and versatile, has a graphic output, and can be used along with methods for phylogenetic inference on multiple alignments like PLL and Seaview. AVAILABILITY AND IMPLEMENTATION: Treerecs is open-source. Its source code (C++, AGPLv3) and manuals are available from https://project.inria.fr/treerecs/. Nicolas Comte, Benoit Morel, Damir Hasic, Laurent Guéguen, Bastien Boussau, Vincent Daubin, Simon Penel, Céline Scornavacca, Manolo Gouy, Alexandros Stamatakis, Eric Tannier, David P. Parsons |
Bioinform. | 4 |
| 2015 | Moments of genome evolution by Double Cut-and-JoinabstractWe study statistical estimators of the number of genomic events separating two genomes under a Double Cut-and Join (DCJ) rearrangement model, by a method of moment estimation. We first propose an exact, closed, analytically invertible formula for the expected number of breakpoints after a given number of DCJs. This improves over the heuristic, recursive and computationally slower previously proposed one. Then we explore the analogies of genome evolution by DCJ with evolution of binary sequences under substitutions, permutations under transpositions, and random graphs. Each of these are presented in the literature with intuitive justifications, and are used to import results from better known fields. We formalize the relations by proving a correspondence between moments in sequence and genome evolution, provided substitutions appear four by four in the corresponding model. Eventually we prove a bounded error on two estimators of the number of cycles in the breakpoint graph after a given number of rearrangements, by an analogy with cycles in permutations and components in random graphs. Priscila Biller, Laurent Guéguen, Eric Tannier |
BMC Bioinform. | 2 |
| 2015 | Probabilistic modeling of the evolution of gene synteny within reconciled phylogeniesabstractMost models of genome evolution concern either genetic sequences, gene content or gene order. They sometimes integrate two of the three levels, but rarely the three of them. Probabilistic models of gene order evolution usually have to assume constant gene content or adopt a presence/absence coding of gene neighborhoods which is blind to complex events modifying gene content. We propose a probabilistic evolutionary model for gene neighborhoods, allowing genes to be inserted, duplicated or lost. It uses reconciled phylogenies, which integrate sequence and gene content evolution. We are then able to optimize parameters such as phylogeny branch lengths, or probabilistic laws depicting the diversity of susceptibility of syntenic regions to rearrangements. We reconstruct a structure for ancestral genomes by optimizing a likelihood, keeping track of all evolutionary events at the level of gene content and gene synteny. Ancestral syntenies are associated with a probability of presence. We implemented the model with the restriction that at most one gene duplication separates two gene speciations in reconciled gene trees. We reconstruct ancestral syntenies on a set of 12 drosophila genomes, and compare the evolutionary rates along the branches and along the sites. We compare with a parsimony method and find a significant number of results not supported by the posterior probability. The model is implemented in the Bio++ library. It thus benefits from and enriches the classical models and methods for molecular evolution. Magali Semeria, Eric Tannier, Laurent Guéguen |
BMC Bioinform. | 3 |
| 2007 | MareyMap: an R-based tool with graphical interface for estimating recombination ratesabstractUNLABELLED: Comparing genetic and physical maps (the so-called Marey map approach) is still the most widely used approach to estimate genome-wide recombination rates. Remarkably, there is no available bioinformatics tool specifically devoted to Marey map approach. Here, we developed such a tool called MareyMap based on GNU R and Tcl/Tk. MareyMap offers a user-friendly graphical interface and includes useful features, such as data cleaning process, sophisticated interpolation methods to estimate local rates, possibility of complex queries, various range of import-export files. Moreover, MareyMap comes with ready-to-use maps for human, Drosophila, Caenorhabditis elegans and Arabidopsis. MareyMap has been made so that it can be easily upgraded with new data and interpolation methods. AVAILABILITY: http://pbil.univ-lyon1.fr/software/mareymap/. Clément Rezvoy, Delphine Charif, Laurent Guéguen, Gabriel A. B. Marais |
Bioinform. | 3 |
| 2005 | Sarment: Python modules for HMM analysis and partitioning of sequencesabstractSummary: Sarment is a package of Python modules for easy building and manipulation of sequence segmentations. It provides efficient implementation of usual algorithms for hidden Markov Model computation, as well as for maximal predictive partitioning. Owing to its very large variety of criteria for computing segmentations, Sarment can handle many kinds of models. Because of object-oriented programming, the results of the segmentation are very easy tomanipulate. Availability: Sarment is available on Linux, UNIX and MacOS X operating systems. It is under GPL license. There are binaries for python2.3 or python2.4, as well as sources, in the website http://pbil.univ-lyon1.fr/software/sarment Contact: [email protected] Laurent Guéguen |
Bioinform. | 1 |
| 1994 | Genetic Algorithms applied to Binocular Stereovision
Régis Vaillant, Laurent Guéguen |
ECCV (2) | 2 |