Yann Ponty

Dr. Yann Ponty


Research Focus & Metrics

Academic Career Length

23Years (2004-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 April 2009 in Bioinformatics
Verified
Journal Article
Open access
KDKévin Darty
Kévin Darty
ADAlain Denise
Alain Denise
YPYann Ponty
Yann Ponty
Description: VARNA is a tool for the automated drawing, visualization and annotation of the secondary structure of RNA, designed as a companion software for web servers and databases. Features: VARNA implements four drawing algorithms, supports input/output using the classic formats dbn, ct, bpseq and RNAML and exports the drawing as five picture formats, either pixel-based (JPEG, PNG) or vector-based (SVG, EPS and XFIG). It also allows manual modification and structural annotation of the resulting drawing using either an interactive point and click approach, within a web server or through command-line arguments. Availability: VARNA is a free software, released under the terms of the GPLv3.0 license and available at http://varna.lri.fr Contact: ponty@lri.fr Supplementary information: Supplementary data are available at Bioinformatics online.

1 May 2021 in Molecular Cell
Verified
Journal Article
Closed access
DWDehe Wang
Dehe Wang
AJAo Jiang
Ao Jiang
JFJiangpeng Feng
Jiangpeng Feng
GLGuangnan Li
Guangnan Li
DGDong Guo
Dong Guo
Yu ZhouYu Zhou
Yu Zhou

26 February 2016 in Bioinformatics
Verified
Journal Article
Open access
PDF file
EJEdwin Jacox
Edwin Jacox
CCCedric Chauve
Cedric Chauve
GSGergely J. Szöllősi
Gergely J. Szöllősi
YPYann Ponty
Yann Ponty
CSCeline Scornavacca
Celine Scornavacca
Summary: A gene tree-species tree reconciliation explains the evolution of a gene tree within the species tree given a model of gene-family evolution. We describe ecceTERA, a program that implements a generic parsimony reconciliation algorithm, which accounts for gene duplication, loss and transfer (DTL) as well as speciation, involving sampled and unsampled lineages, within undated, fully dated or partially dated species trees. The ecceTERA reconciliation model and algorithm generalize or improve upon most published DTL parsimony algorithms for binary species trees and binary gene trees. Moreover, ecceTERA can estimate accurate species-tree aware gene trees using amalgamation. Availability and implementation: ecceTERA is freely available under http://mbb.univ-montp2.fr/MBB/download_sources/16__ecceTERA and can be run online at http://mbb.univ-montp2.fr/MBB/subsection/softExec.php?soft=eccetera. Contact:celine.scornavacca@umontpellier.fr Supplementary information: Supplementary data are available at Bioinformatics online.

3 January 2017 in Briefings in Bioinformatics
Verified
Journal Article
Open access
ACAlexander Churkin
Alexander Churkin
MRMatan Drory Retwitzer
Matan Drory Retwitzer
VRVladimir Reinharz
Vladimir Reinharz
YPYann Ponty
Yann Ponty
JWJérôme Waldispühl
Jérôme Waldispühl
Danny BarashDanny Barash
Danny Barash
Computational programs for predicting RNA sequences with desired folding properties have been extensively developed and expanded in the past several years. Given a secondary structure, these programs aim to predict sequences that fold into a target minimum free energy secondary structure, while considering various constraints. This procedure is called inverse RNA folding. Inverse RNA folding has been traditionally used to design optimized RNAs with favorable properties, an application that is expected to grow considerably in the future in light of advances in the expanding new fields of synthetic biology and RNA nanostructures. Moreover, it was recently demonstrated that inverse RNA folding can successfully be used as a valuable preprocessing step in computational detection of novel noncoding RNAs. This review describes the most popular freeware programs that have been developed for such purposes, starting from RNAinverse that was devised when formulating the inverse RNA folding problem. The most recently published ones that consider RNA secondary structure as input are antaRNA, RNAiFold and incaRNAfbinv, each having different features that could be beneficial to specific biological problems in practice. The various programs also use distinct approaches, ranging from ant colony optimization to constraint programming, in addition to adaptive walk, simulated annealing and Boltzmann sampling. This review compares between the various programs and provides a simple description of the various possibilities that would benefit practitioners in selecting the most suitable program. It is geared for specific tasks requiring RNA design based on input secondary structure, with an outlook toward the future of RNA design programs.

19 June 2013 in Bioinformatics
Verified
Journal Article
Open access
PDF file
VRVladimir Reinharz
Vladimir Reinharz
YPYann Ponty
Yann Ponty
JWJérôme Waldispühl
Jérôme Waldispühl
Motivations: The design of RNA sequences folding into predefined secondary structures is a milestone for many synthetic biology and gene therapy studies. Most of the current software uses similar local search strategies (i.e. a random seed is progressively adapted to acquire the desired folding properties) and more importantly do not allow the user to control explicitly the nucleotide distribution such as the GC-content in their sequences. However, the latter is an important criterion for large-scale applications as it could presumably be used to design sequences with better transcription rates and/or structural plasticity. Results: In this article, we introduce IncaRNAtion, a novel algorithm to design RNA sequences folding into target secondary structures with a predefined nucleotide distribution. IncaRNAtion uses a global sampling approach and weighted sampling techniques. We show that our approach is fast (i.e. running time comparable or better than local search methods), seedless (we remove the bias of the seed in local search heuristics) and successfully generates high-quality sequences (i.e. thermodynamically stable) for any GC-content. To complete this study, we develop a hybrid method combining our global sampling approach with local search strategies. Remarkably, our glocal methodology overcomes both local and global approaches for sampling sequences with a specific GC-content and target structure. Availability: IncaRNAtion is available at csb.cs.mcgill.ca/incarnation/ Contact: jeromew@cs.mcgill.ca or yann.ponty@lix.polytechnique.fr Supplementary Information: Supplementary data are available at Bioinformatics online.

30 March 2006 in Bioinformatics
Verified
Journal Article
Open access
PDF file
YPYann Ponty
Yann Ponty
MTMichel Termier
Michel Termier
ADAlain Denise
Alain Denise
Summary: GenRGenS is a software tool dedicated to randomly generating genomic sequences and structures. It handles several classes of models useful for sequence analysis, such as Markov chains, hidden Markov models, weighted context-free grammars, regular expressions and PROSITE expressions. GenRGenS is the only program that can handle weighted context-free grammars, thus allowing the user to model and to generate structured objects (such as RNA secondary structures) of any given desired size. GenRGenS also allows the user to combine several of these different models at the same time. Availability: Source and executable files of GenRGenS (in Java) and the complete user's manual are freely available at Author Webpage Contact:dev.GenRGenS@lri.fr