The Computational Biology Institute (IBC) organizes scientific conferences open to the entire scientific community of Montpellier.
These conferences are conceived as a meeting point for the multidisciplinary exchange of ideas at the interface between biology, health, agriculture, environment, computer science, mathematics and physics. They aim to regularly cover themes encountered in the five axes of the Institute through presentation of a particular question or research subject.
The talks are intended for a broad and multidisciplinary audience.They are in French or English, as appropriate, and are held on a monthly basis at the IBC (see map) on Friday afternoons from 14h to 15h30, including time for discussion, which may extend over a coffee in a friendly atmosphere.
Feel free to advertise widely the announcement of these plenary sessions.
Next scheduled dates : 9th March 2018
Investigating microbial ecosystems: a computational journey from co-occurrence to metabolic networks
Damien Eveillard - Computational Biology group - Lab. Sciences du Numériques Nantes, Université de Nantes
25th May 2018 at 2pm - IBC Bât 5 room 2.022
Leena Salmela - Dpt of Computer Science, University of Helsinki, Finland.
Friday 13th April 2018 - 2 pm - IBC (Campus St Priest Bat 5 room 2.022)
One of the last steps in a genome assembly project is filling the gaps between consecutive contigs in the scaffolds. The gap filling problem generally asks for an s-t path in an assembly graph whose length matches the gap length estimate. This problem is known to be NP-hard in general. Here we derive a simpler dynamic programming solution than already known, pseudo-polynomial in the maximum value of the input range.
Although several methods have addressed the gap filling problem, only few have focused on strategies for dealing with multiple gap filling solutions and for guaranteeing reliable results. Such strategies include reporting only unique solutions, or exhaustively enumerating all filling solutions and heuristically creating their consensus. We present a new method for reliable gap filling: filling gaps with those sub-paths common to all gap filling solutions.
We implemented our algorithm in a tool called Gap2Seq and compared our exact gap-filling solution experimentally to popular gap-filling tools. Our experiments show that on bacterial and conservative human assemblies we can fill more gaps than previous tools with a similar precision.
A related seminar will be given on the 6th of April 2018 at 2pm the LIRMM (same building) by Riku Walve also from Helsinki University. (see http://www.lirmm.fr/recherche/equipes/mab/seminaires-de-bioinformatique).
Friday 24th November 2017 at 2 pm, IBC Campus St Priest BAT5-01.124
Prof. Dr. Tobias MarschallMax-Planck-Institut für Informatik
Algorithms for Computational Genomics
Humans and many other species are diploid. Every individual inherits two versions of each autosomal chromosome, called haplotypes, one from its mother and one from its father. Moving from (sequences of) genotypes to haplotypes is known as phasing or haplotyping. The knowledge of haplotypes is critical for addressing a variety of important questions in fundamental and clinical research. In this talk, I will highlight both algorithmic and experimental aspects of reconstructing haplotypes, with a special emphasis on recent technological advancements and their impact on the computational problems to be solved. I will briefly touch on population-based and pedigree-based phasing method, but will mostly focus on direct experimental methods that allow to reconstruct haplotypes for single individuals. Haplotype reconstruction from sequencing reads is most commonly formalized as the Minimum Error Correction (MEC) problem. Recent advances on fixed-parameter tractable (FPT) algorithm allow us to (quickly) solve practically relevant instances of this NP-hard problem optimally. I will present experimental results from five different platforms (PacBio, Oxford Nanopore, Hi-C, StrandSeq, and 10X Genomics) and highlight how combinations of these technologies allow to accurately reconstruct dense chromosome-length human haplotypes at manageable costs.
Friday 9th Mars 2018 at 2 pm, IBC Campus St Priest BAT5-03.124
Dr. Daniel Gautheret
Institute for Integrative Biology of the Cell
Universite Paris-Sud - CNRS -CEA
Computational pipelines for NGS data analysis involve mutiple hypotheses and simplifications leading to an important loss of information. For instance, a major limiting factor is the mapping step where NGS reads are aligned to a reference genome or transcriptome. In RNA-seq analysis, relying on a reference transcriptome amounts to ignoring novel genes, alternative transcripts and transcripts from repeats or with high levels of mutation or editing. Hundreds of dedicated software have been developed to bypass these limitations and retrieve specific event types, with highly diverging results.
We have developed a method for RNA-seq data analysis, DE-kupl (1), in which NGS data is analysed at the level of raw sequence using k-mers (i.e. subsequences of length k, with typically k=31) followed by differential expression analysis. Only k-mers that are differentially represented between two sets of libraries are extracted and analyzed. Therefore all biological variation present in the original NGS dataset is theroretically collected, with no prior hypothesis about their origin.
We will show how DE-kupl can be applied to various experimental settings and present our plans for future developments, including application to the discovery of novel biomarkers based on cliniciallly annotated DNA-seq or RNA-seq data.
(1) Audoux J, Philippe N, Chikhi R, Salson M, Gallopin M, Gabriel M, Le Coz J, Commes T, Gautheret D. (2017) DE-kupl: Exhaustive capture of biological variation in RNA-seq data through k-mer decomposition. Genome Biol. 18: 243.
BioDICée team, CNRS, ISEM, Montpellier
Friday 6th October 2017 at 2 pm, IBC Campus St Priest BAT5-01.124
Reini F. Luco
Institute of Human Genetics, UPR 1142, CNRS, Montpellier, France
Friday 19th May 2017 at 2 pm, IBC Campus St Priest BAT5-01.124