Benjamin Linard
University of Strasbourg
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Featured researches published by Benjamin Linard.
PLOS ONE | 2011
Julie D. Thompson; Benjamin Linard; Odile Lecompte; Olivier Poch
Multiple comparison or alignmentof protein sequences has become a fundamental tool in many different domains in modern molecular biology, from evolutionary studies to prediction of 2D/3D structure, molecular function and inter-molecular interactions etc. By placing the sequence in the framework of the overall family, multiple alignments can be used to identify conserved features and to highlight differences or specificities. In this paper, we describe a comprehensive evaluation of many of the most popular methods for multiple sequence alignment (MSA), based on a new benchmark test set. The benchmark is designed to represent typical problems encountered when aligning the large protein sequence sets that result from todays high throughput biotechnologies. We show that alignmentmethods have significantly progressed and can now identify most of the shared sequence features that determine the broad molecular function(s) of a protein family, even for divergent sequences. However,we have identified a number of important challenges. First, the locally conserved regions, that reflect functional specificities or that modulate a proteins function in a given cellular context,are less well aligned. Second, motifs in natively disordered regions are often misaligned. Third, the badly predicted or fragmentary protein sequences, which make up a large proportion of todays databases, lead to a significant number of alignment errors. Based on this study, we demonstrate that the existing MSA methods can be exploited in combination to improve alignment accuracy, although novel approaches will still be needed to fully explore the most difficult regions. We then propose knowledge-enabled, dynamic solutions that will hopefully pave the way to enhanced alignment construction and exploitation in future evolutionary systems biology studies.
Bioinformatics | 2012
Christophe Dessimoz; Toni Gabaldón; David S. Roos; Erik L. L. Sonnhammer; Javier Herrero; Adrian M. Altenhoff; Rolf Apweiler; Michael Ashburner; Judith A. Blake; Brigitte Boeckmann; Alan Bridge; Elspeth Bruford; Mike Cherry; Matthieu Conte; Durand Dannie; Ruchira S. Datta; Jean-Baka Domelevo Entfellner; Ingo Ebersberger; Michael Y. Galperin; Jacob M. Joseph; Tina Koestler; Evgenia V. Kriventseva; Odile Lecompte; Jack Leunissen; Suzanna E. Lewis; Benjamin Linard; Michael S. Livstone; Hui-Chun Lu; María Martín; Raja Mazumder
The identification of orthologs—genes pairs descended from a common ancestor through speciation, rather than duplication—has emerged as an essential component of many bioinformatics applications, ranging from the annotation of new genomes to experimental target prioritization. Yet, the development and application of orthology inference methods is hampered by the lack of consensus on source proteomes, file formats and benchmarks. The second ‘Quest for Orthologs’ meeting brought together stakeholders from various communities to address these challenges. We report on achievements and outcomes of this meeting, focusing on topics of particular relevance to the research community at large. The Quest for Orthologs consortium is an open community that welcomes contributions from all researchers interested in orthology research and applications. Contact: [email protected]
Nucleic Acids Research | 2012
Tien-Dao Luu; Alin Rusu; Vincent Walter; Benjamin Linard; Laetitia Poidevin; Raymond Ripp; Luc Moulinier; Jean Muller; Wolfgang Raffelsberger; Nicolas Wicker; Odile Lecompte; Julie D. Thompson; Olivier Poch; Hoan Nguyen
A major challenge in the post-genomic era is a better understanding of how human genetic alterations involved in disease affect the gene products. The KD4v (Comprehensible Knowledge Discovery System for Missense Variant) server allows to characterize and predict the phenotypic effects (deleterious/neutral) of missense variants. The server provides a set of rules learned by Induction Logic Programming (ILP) on a set of missense variants described by conservation, physico-chemical, functional and 3D structure predicates. These rules are interpretable by non-expert humans and are used to accurately predict the deleterious/neutral status of an unknown mutation. The web server is available at http://decrypthon.igbmc.fr/kd4v.
Nature Methods | 2016
Adrian M. Altenhoff; Brigitte Boeckmann; Salvador Capella-Gutiérrez; Daniel A. Dalquen; Todd DeLuca; Kristoffer Forslund; Jaime Huerta-Cepas; Benjamin Linard; Cecile Pereira; Leszek P. Pryszcz; Fabian Schreiber; Alan Wilter Sousa da Silva; Damian Szklarczyk; Clément-Marie Train; Peer Bork; Odile Lecompte; Christian von Mering; Ioannis Xenarios; Kimmen Sjölander; Lars Juhl Jensen; María Martín; Matthieu Muffato; Toni Gabaldón; Suzanna E. Lewis; Paul D. Thomas; Erik L. L. Sonnhammer; Christophe Dessimoz
Achieving high accuracy in orthology inference is essential for many comparative, evolutionary and functional genomic analyses, yet the true evolutionary history of genes is generally unknown and orthologs are used for very different applications across phyla, requiring different precision–recall trade-offs. As a result, it is difficult to assess the performance of orthology inference methods. Here, we present a community effort to establish standards and an automated web-based service to facilitate orthology benchmarking. Using this service, we characterize 15 well-established inference methods and resources on a battery of 20 different benchmarks. Standardized benchmarking provides a way for users to identify the most effective methods for the problem at hand, sets a minimum requirement for new tools and resources, and guides the development of more accurate orthology inference methods.
BMC Bioinformatics | 2011
Benjamin Linard; Julie D. Thompson; Olivier Poch; Odile Lecompte
BackgroundThe accurate determination of orthology and inparalogy relationships is essential for comparative sequence analysis, functional gene annotation and evolutionary studies. Various methods have been developed based on either simple blast all-versus-all pairwise comparisons and/or time-consuming phylogenetic tree analyses.ResultsWe have developed OrthoInspector, a new software system incorporating an original algorithm for the rapid detection of orthology and inparalogy relations between different species. In comparisons with existing methods, OrthoInspector improves detection sensitivity, with a minimal loss of specificity. In addition, several visualization tools have been developed to facilitate in-depth studies based on these predictions. The software has been used to study the orthology/in-paralogy relationships for a large set of 940,855 protein sequences from 59 different eukaryotic species.ConclusionOrthoInspector is a new software system for orthology/paralogy analysis. It is made available as an independent software suite that can be downloaded and installed for local use. Command line querying facilitates the integration of the software in high throughput processing pipelines and a graphical interface provides easy, intuitive access to results for the non-expert.
Epilepsia | 2010
Benjamin Linard; Arielle Ferrandon; Estelle Koning; Astrid Nehlig; Emmanuel Raffo
Purpose: Although the number of antiepileptic drugs (AEDs) is increasing, none displays neuroprotective or antiepileptogenic properties that could prevent status epilepticus (SE)–induced drug‐resistant epilepsy. Ketogenic diet (KD) and calorie restriction (CR) are proposed as alternative treatments in epilepsy. Our goal was to assess the neuroprotective or antiepileptogenic effect of these diets in a well‐characterized model of mesial temporal lobe epilepsy following initial SE induced by lithium‐pilocarpine in adult rats.
BMC Genomics | 2012
Francisco Prosdocimi; Benjamin Linard; Pierre Pontarotti; Olivier Poch; Julie D. Thompson
BackgroundThe data from high throughput genomics technologies provide unique opportunities for studies of complex biological systems, but also pose many new challenges. The shift to the genome scale in evolutionary biology, for example, has led to many interesting, but often controversial studies. It has been suggested that part of the conflict may be due to errors in the initial sequences. Most gene sequences are predicted by bioinformatics programs and a number of quality issues have been raised, concerning DNA sequencing errors or badly predicted coding regions, particularly in eukaryotes.ResultsWe investigated the impact of these errors on evolutionary studies and specifically on the identification of important genetic events. We focused on the detection of asymmetric evolution after duplication, which has been the subject of controversy recently. Using the human genome as a reference, we established a reliable set of 688 duplicated genes in 13 complete vertebrate genomes, where significantly different evolutionary rates are observed. We estimated the rates at which protein sequence errors occur and are accumulated in the higher-level analyses. We showed that the majority of the detected events (57%) are in fact artifacts due to the putative erroneous sequences and that these artifacts are sufficient to mask the true functional significance of the events.ConclusionsInitial errors are accumulated throughout the evolutionary analysis, generating artificially high rates of event predictions and leading to substantial uncertainty in the conclusions. This study emphasizes the urgent need for error detection and quality control strategies in order to efficiently extract knowledge from the new genome data.
Genomics | 2013
Florence Bedez; Benjamin Linard; Xavier Brochet; Raymond Ripp; Julie D. Thompson; Dino Moras; Odile Lecompte; Olivier Poch
TFIIH is a eukaryotic complex composed of two subcomplexes, the CAK (Cdk activating kinase) and the core-TFIIH. The core-TFIIH, composed of seven subunits (XPB, XPD, P62, P52, P44, P34, and P8), plays a crucial role in transcription and repair. Here, we performed an extended sequence analysis to establish the accurate phylogenetic distribution of the core-TFIIH in 63 eukaryotic organisms. In spite of the high conservation of the seven subunits at the sequence and genomic levels, the non-enzymatic P8, P34, P52 and P62 are absent from one or a few unicellular species. To gain insight into their respective roles, we undertook a comparative genomic analysis of the whole proteome to identify the gene sets sharing similar presence/absence patterns. While little information was inferred for P8 and P62, our studies confirm the known role of P52 in repair and suggest for the first time the implication of the core TFIIH in mRNA splicing via P34.
Bioinformatics | 2015
Benjamin Linard; Alexis Allot; Raphaël Schneider; Can Morel; Raymond Ripp; Marc Bigler; Julie D. Thompson; Olivier Poch; Odile Lecompte
SUMMARY We previously developed OrthoInspector, a package incorporating an original algorithm for the detection of orthology and inparalogy relations between different species. We have added new functionalities to the package. While its original algorithm was not modified, performing similar orthology predictions, we facilitated the prediction of very large databases (thousands of proteomes), refurbished its graphical interface, added new visualization tools for comparative genomics/protein family analysis and facilitated its deployment in a network environment. Finally, we have released three online databases of precomputed orthology relationships. AVAILABILITY Package and databases are freely available at http://lbgi.fr/orthoinspector with all major browsers supported. CONTACT [email protected] SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Evolutionary Bioinformatics | 2012
Benjamin Linard; Ngoc Hoan Nguyen; Francisco Prosdocimi; Olivier Poch; Julie D. Thompson
Evolutionary systems biology aims to uncover the general trends and principles governing the evolution of biological networks. An essential part of this process is the reconstruction and analysis of the evolutionary histories of these complex, dynamic networks. Unfortunately, the methodologies for representing and exploiting such complex evolutionary histories in large scale studies are currently limited. Here, we propose a new formalism, called EvoluCode (Evolutionary barCode), which allows the integration of different evolutionary parameters (eg, sequence conservation, orthology, synteny …) in a unifying format and facilitates the multilevel analysis and visualization of complex evolutionary histories at the genome scale. The advantages of the approach are demonstrated by constructing barcodes representing the evolution of the complete human proteome. Two large-scale studies are then described: (i) the mapping and visualization of the barcodes on the human chromosomes and (ii) automatic clustering of the barcodes to highlight protein subsets sharing similar evolutionary histories and their functional analysis. The methodologies developed here open the way to the efficient application of other data mining and knowledge extraction techniques in evolutionary systems biology studies. A database containing all EvoluCode data is available at: http://lbgi.igbmc.fr/barcodes.