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| 10:30 | Automatic exploration of the natural variability of RNA non-canonical geometric patterns with a parameterized sampling technique PRESENTER: Théo Boury ABSTRACT. --- |
| 10:50 | MDverse: Shedding Light on the Dark Matter of Molecular Dynamics Simulations PRESENTER: Pierre Poulain ABSTRACT. The rise of open science and the absence of a global dedicated data repository for molecular dynamics (MD) simulations has led to the accumulation of MD files in generalist data repositories, constituting the dark matter of MD - data that is technically accessible, but neither indexed, curated, or easily searchable. Leveraging an original search strategy, we found and indexed about 250,000 files and 2,000 datasets from Zenodo, Figshare and Open Science Framework. With a focus on files produced by the Gromacs MD software, we illustrate the potential offered by the mining of publicly available MD data. We identified systems with specific molecular composition and were able to characterize essential parameters of MD simulation, such as temperature and simulation length, and identify model resolution, such as all-atom and coarse-grain. Based on this analysis, we inferred metadata to propose a search engine prototype to explore collected MD data. To continue in this direction, we call on the community to pursue the effort of sharing MD data, and increase populating and standardizing metadata to reuse this valuable matter. |
| 11:10 | RNAdvisor: a comprehensive benchmarking tool for the measure and prediction of RNA structural model quality PRESENTER: Clement Bernard ABSTRACT. RNA is a complex macromolecule that plays central roles in the cell. While it is well known that its structure is directly related to its functions, understanding and predicting RNA structures is challenging. Assessing the real or predictive quality of a structure is also at stake with the complex 3D possible conformations of RNAs. Metrics have been developed to measure model quality while scoring functions aim at assigning quality to guide the discrimination of structures without a known and solved reference. Throughout the years, many metrics and scoring functions have been developed, and no unique assessment is used nowadays. Each developed assessment method has its specificity and might be complementary to understanding structure quality. Therefore, to evaluate RNA 3D structure predictions, it would be important to calculate different metrics and/or scoring functions. For this purpose, we developed RNAdvisor, a comprehensive automated software that integrates and enhances the accessibility of existing metrics and scoring functions. In this paper, we present our RNAdvisor tool, as well as state-of-the-art existing metrics, scoring functions and a set of benchmarks we conducted for evaluating them. Source code is freely available on the EvryRNA platform: https://evryrna.ibisc.univ- evry.fr. |
| 10:30 | CroCoDeEL: accurate detection of cross-sample contamination in metagenomic data PRESENTER: Guillaume Gautreau ABSTRACT. Metagenomic sequencing provides deep insights into microbial communities but is subject to various experimental biases such as cross-sample contamination where microbial contents from simultaneously processed samples are accidentally mixed. Although a critical issue that can potentially lead to erroneous conclusions, such contamination remains understudied. A few methods have already been proposed to detect it, although with multiple limitations, including the lack of sensitivity. Here, we introduce CroCoDeEL, a tool based on a supervised pre-trained model that identifies specific patterns in taxonomic profiles associated with cross-sample contamination. Benchmarks across three public cohorts comprehensively curated by the authors revealed that CroCoDeEL identifies with high accuracy not only the contaminated samples but also their respective contamination sources even as it occurs with low rates (<0.1%), allowing that the sequencing depth allows for it. Our work underlines the urgency to acknowledge and systematically address this phenomenon to ensure the robustness of studies based on metagenomic data. |
| 10:50 | Integration of metataxonomic datasets into microbial association networks highlights shared bacterial community dynamics in fermented vegetables PRESENTER: Romane Junker ABSTRACT. The management of food fermentation is still largely based on empirical knowledge, as the dynamics of microbial communities and the underlying metabolic networks that produce safe and nutritious products remain beyond our understanding. Although these closed ecosystems contain relatively few taxa, they have not yet been thoroughly characterized with respect to how their microbial communities interact and dynamically evolve. However, with the increased availability of metataxonomic datasets on different fermented vegetables, it is now possible to gain a comprehensive understanding of the microbial relationships that structure plant fermentation. In this study, we applied a network-based approach to integration of public metataxonomic 16S datasets targeting different fermented vegetables throughout time. Specifically, we aimed to explore, compare and combine public 16S datasets to identify shared associations between amplicon sequence variants (ASV) obtained from independent studies. The workflow includes steps for searching and selecting public time-series datasets and constructing association networks of ASVs based on co-abundance metrics. Networks for individual datasets are then integrated into a core network highlighting significant associations. Microbial communities are identified based on the comparison and clustering of ASV networks using the “stochastic block model” method. When we applied this method to 10 public datasets (including a total of 931 samples) targeting five varieties of vegetables with different sampling times, we found that it was able to shed light on the dynamics of vegetable fermentation by characterizing the processes of community succession among different bacterial assemblages. Within the growing body of research on the bacterial communities involved in the fermentation of vegetables, there is particular interest in discovering the species or consortia that drive different fermentation steps. This integrative analysis demonstrates that the reuse and integration of public microbiome datasets can provide new insights into a little-known biotope. Our most important finding is the recurrent but transient appearance, at the beginning of vegetable fermentation, of ASVs belonging to Enterobacterales and their associations with ASVs belonging to Lactobacillales. These findings could be applied in the design of new fermented products. |
| 11:10 | Pangenome graph construction from genome alignments with Minigraph-Cactus PRESENTER: Jean Monlong ABSTRACT. Pangenome references address biases of reference genomes by storing a representative set of diverse haplotypes and their alignment, usually as a graph. Alternate alleles determined by variant callers can be used to construct pangenome graphs, but advances in long-read sequencing are leading to widely available, high-quality phased assemblies. Constructing a pangenome graph directly from assemblies, as opposed to variant calls, leverages the graph’s ability to represent variation at different scales. Here we present the Minigraph-Cactus pangenome pipeline, which creates pangenomes directly from whole-genome alignments, and demonstrate its ability to scale to 90 human haplotypes from the Human Pangenome Reference Consortium. The method builds graphs containing all forms of genetic variation while allowing use of current mapping and genotyping tools. We measure the effect of the quality and completeness of reference genomes used for analysis within the pangenomes and show that using the CHM13 reference from the Telomere-to-Telomere Consortium improves the accuracy of our methods. We also demonstrate construction of a Drosophila melanogaster pangenome. |
| 10:30 | hdmax2, an R package to perform high dimension mediation analysis PRESENTER: Florence Pittion ABSTRACT. Mediation analysis plays a crucial role in epidemiology, unraveling the intricate pathways through which exposures exert influence on health outcomes. Recent advances in high-throughput sequencing techniques have generated growing interest in applying mediation analysis to explore the causal relationships between patient environmental exposures, molecular features (such as omics data) and various health outcomes. Mediation analysis handling high-dimensional mediators raise a number of statistical challenges. Despite the emergence of numerous methods designed to tackle these challenges, the majority are limited to continuous outcomes. Furthermore, these advanced statistical approaches have yet to find widespread adoption among epidemiologists and health data scientists in their day-to-day practices. To address this gap, we introduce an R package specifically tailored for high-dimensional mediation analysis using the max-squared method (HDMAX2). This tool aims to mitigate these obstacles by providing a practical solution for researchers and practitioners eager to explore intricate causal relationships in health data involving complex molecular features. Here we improve the HDMAX2 method, and expand its capabilities to accommodate multiple exposures and non-continuous variables. This improvement enables its application to a diverse array of mediation analysis scenarios, mirroring the complexity often encountered in healthcare data. To enhance accessibility for users with varying expertise, we release an R package called hdmax2. This package allows users to estimate the indirect effects of mediators, calculate the overall indirect effect of mediators, and facilitates the execution of high-dimensional mediation analysis. |
| 10:50 | Advancing Drug-Target Interactions Prediction: Leveraging a Large-Scale Dataset with a Rapid and Robust Chemogenomic Algorithm PRESENTER: Gwenn Guichaoua ABSTRACT. Predicting drug-target interactions (DTIs) is crucial for drug discovery, and heavily relies on supervised learning techniques. Supervised learning algorithms for DTI prediction use known DTIs to learn associations between molecule and protein features, allowing for the prediction of new interactions based on learned patterns. In this paper, we present a novel approach addressing two key challenges in DTI prediction: the availability of large, high-quality training datasets and the scalability of prediction methods. First, we introduce LCIdb, a curated, large-sized dataset of DTIs. Notably, LCIdb contains a much higher number of molecules than traditional benchmarks, expanding the coverage of the molecule space. Second, we propose Komet (Kronecker Optimized METhod), a DTI prediction pipeline designed for scalability without compromising performance. Komet leverages a three-step framework, incorporating efficient computation choices tailored for large datasets and involving the Nyström approximation. Specifically, Komet employs a Kronecker interaction module for (molecule, protein) pairs, which is sufficiently expressive and whose structure allows for reduced computational complexity. Our method is implemented in open-source software, leveraging GPU parallel computation for efficiency. We demonstrate the efficiency of our approach on various datasets, showing that Komet displays superior scalability and prediction performance compared to state-of-the-art deep learning approaches. Komet is available open source at https://komet.readthedocs.io and all datasets, including LCIdb, can be found at https://zenodo.org/records/10731713. |
| 11:10 | AttOmics: Attention-based architecture for diagnosis and prognosis from Omics data PRESENTER: Aurélien Beaude ABSTRACT. The development of high-throughput methods led to the production of large amounts of biomedical data, such as omics profiles. Precision medicine exploits these omics profiles with machine-learning models, especially the ones based on deep-learning approaches, to improve clinical decision-making. Molecular interactions governing cellular functions vary across patients. Computing patient-specific feature interactions with self-attention could improve the predictive performance. However, computing self-attention on high dimensional vectors, like omics profile, is hardware-limited as the memory requirements scale quadratically with the number of elements. We proposed AttOmics a new deep-learning architecture based on the self-attention mechanism. First, we decompose each omics profile into a set of groups, where each group contains related features. Groups are encoded with an encoder consisting of n blocks. In each block, group embeddings are computed by projecting each group with its own FCN, considering only intra-group interactions. Inter-group interactions are computed by applying the multi-head self-attention to the set of groups. By combining this data decomposition with the attention mechanism, we can accurately predict the type of cancer while reducing the number of parameters compared to an MLP with a similar dimension. The availability of omics data from cancer patients remains limited; with very small training databases, AttOmics outperformed classical deep learning approaches. The choice of grouping strategy impacted the performances. Visualizing the attention maps can provide new insights into the essential groups for a particular phenotype. |
#73 Frédéric Pont "Single-cell spatial explorer: easy exploration of spatial and multimodal transcriptomics"
#75 Hélène Chiapello, Thomas Denecker, Lucie Khamvongsa Charbonnier, Pierre Poulain, Denis Puthier, Olivier Sand, Morgane Thomas-Chollier and Claire Toffano-Nioche "Une matrice de compétences Unix pour l'apprentissage de la bioinformatique"
#80 Rose Marin, Pauline Barbet, Niklas Probul, Jan Baumbach, Julie Lê Hoang, Mathieu Almeida and Magali Berland "Exploration of machine learning recipes for gut microbiome based colorectal cancer diagnosis"
#102 Antoine Daussin, Pauline Barbet, Mathieu Almeida, Aurélie Caille, Claire Cherbuy, Nathalie Meunier, Nicolas Pons and Victoria Meslier "MetaNutriDB, a collection of public cohorts with curated metagenomic and nutritional data"
#104 Céline Bougel, Van Du Tran, Julien Boccard, Marie Tremblay-Franco and Florence Mehl "Multiblock Omics data fusion using the Consensus OPLS R package"
#106 Mathilde Sola, Oscar Gitton-Quent, Nicolas Maziers, Anne Hiol, Nicolas Dechamp, Mahendra Mariadassou, Emanuelle Le Chatelier, Mathilde Touvier, Pilar Galan, Patrick Veiga, Joel Dore, Melanie Deschasaux-Tanguy and Magali Berland "Disturbances in Gut Microbiota Characteristics Revealed in Non-Diabetics with Family History of T2D"
#109 Jean-Clément Gallardo, Florence Vinson, Marion Liotier, Ludovic Cottret and Fabien Jourdan "VizCore: A web component dedicated to graph visualisation"
#113 Paraskevi Kousteridou and Pierre Bertrand "Met'Connect: Bioinformatics necessary tool to explore Tumor Metabolism"
#114 Julien Guibert, Cecile Canlet, Marie Tremblay-Franco, Marine Letertre, Patrick Giraudeau, Marine Piou and Jean-Nicolas Dumez "Benchmarking of different software for 2D NMR spectra automatic integration for metabolomic approaches"
#115 Asmae Bachr, Aurélie Leduc, Vincent Meyer, Marc Delepine, Cédric Fund, Stéphane Meslage, Damien Delafoy, Florian Sandron, Zuzana Gerber and Jean-Franíçois Deleuze "Evaluation of short and long read technologies for variant identification"
#116 Thibaut Peyric, Anton Crombach and Thomas Guyet "Single-cell multi-omics data integration powered by PCA-like autoencoders"
#117 Océane Carpentier, Vincent Rocher, Sarah Djebali and Cervin Guyomar "Knowledge graph based integration of transcriptome sequencing data to explore miRNA mediated regulation"
#118 Anne-Laure Abraham, Guillaume Kon Kam King, Solène Pety, Anne-Carmen Sanchez, Helene Chiapello and Pierre Nicolas "Intra-species diversity in metagenomic datasets"
#119 Nicolas Mendiboure, Jerí´me Savocco, Agnés Dumont and Aurèle Piazza "Studying homology search with a ssDNA specific Hi-C methodology and stochastic modelling."
#120 Oneeb Nasir, Alyssa Imbert, Pierrick Roger, Thomas Burger, Yves Vandenbrouck, Marion Brandolini-Bunlon, Florence Castelli, Franck Giacomoni, Magali Rompais, Mohammed Selloum, Emmanuelle Mouton-Barbosa, Emeline Chu-Van, Charlotte Joly, Aurélie Hirschler, Sophie Leblanc, Tania Sorg, Sadia Ouzia, Claudine Medigue, Christophe Junot, Anne Gonzalez De Peredo, Christine Carapito, Estelle Pujos-Guillot, Yann Herault, Myriam Ferro, Franíçois Fenaille and Etienne Thévenot "ProMetIS 2.0: proteomics and metabolomics data analysis and integration, applied to the characterization of the Lat and Mx2 knockout phenotypes"
#121 Suzon Montmartin, Etienne Fafard-Couture, Morgane Govone, Jordan Hedjam, Fleur Bourdelais, Sébastien Durand, Michelle Scott and Virginie Marcel "De novo annotation of non-coding RNAs shaping ribosomal RNA epitranscriptomics in mice"
#122 Julie Lao, Raphaël Tackx, Pierre Marin, Amanda Dieuaide, Thomas Mignon, Bérénice Batut, Cléa Siguret, Romain Dallet, Kenzo-Hugo Hillion, Nadia Goué, Etienne Ruppé, Gildas Le Corguillé, Consortium Abromics, Philippe Glaser, Fabien Mareuil and Claudine Médigue "The ABRomics platform - a One Health Antimicrobial resistance analysis service"
#123 Nawad Hakim, Morgane Le Teuff and Véronique Adoue "Impact of RNA modifications in CD4 T cell differentiation and function"
#124 Esther Cros, Annaëlle Caillarec-Joly, Miriam Isabelle Brandt, Frédérique Viard, Patrick Durand, Cyril Noel and Sophie Arnaud-Haond "SAMBA-MarAbyss a metabarcode data analysis workflow for community ecology"
#125 Zoé Gerber, Tanja Pejovic and Marilyne Labrie "Bioinformatics study of the immune microenvironment rewiring induced by chemotherapy in ovarian cancer"
#126 Thomas Stosskopf, Galadriel Briere, Benjamin Loire and Anaïs Baudot "Leveraging Knowledge Graphs for Drug Repurposing in Rare Diseases"
#128 Marina Abakarova, Michael Rera and Elodie Laine "Assessing lethal missense mutations and polymorphism in Drosophila melanogaster with an evolutionary-informed model"
#129 Clémence Réda, Jill-Jênn Vie and Olaf Wolkenhauer "JELI: an interpretable embedding-learning recommender system for drug repurposing"
#131 Jérémy Rousseau, Lucie Bittner and Mathilde Carpentier "LAGOON-MCL: A pipeline to unlock the dark side of proteomic sequences"
#132 Baptiste Herlemont, Gregoire Aubert, Nadim Tayeh, Jonathan Kreplak, Judith Burstin, Isabelle Lejeune-Henaut and Marie-Laure Pilet-Nayel "Development of a Pipeline for Pan-genomic Gene Exploration: a case study on Pea (Pisum sativum L.)"
#134 Karine Massau, Alexandra Louis, Byte-Sea Consortium and Erwan Corre "BYTE-Sea: the digital infrastructure of ATLASea, the French marine genome sequencing programme."
#135 Maëlle Daunesse, Elise Parey, Diego Villar and Camille Berthelot "Phylogenetic modelling of gene expression shifts in the mole-rat clade"
#136 Justine Labory, Youssef Boulaimen, Jasmine Singh, Sylvie Bannwarth, Samira Ait-El-Mkadem Saadi, Véronique Paquis-Fluckinger and Silvia Bottini "VIOLA: Variant PrIOritization using LAtent space to improve mito-chondrial diseases diagnosis"
#139 Vincent Lombard, Elodie Drula, Marie-Line Garron, Matthieu Boulinguiez, Pedro Coutinho, Bernard Henrissat and Nicolas Terrapon "The Carbohydrate-Active EnZYme database: updates and plateform"
#140 Mélanie Polart-Donat, Cyril Bauland, Frédérique Bitton, Alain Charcosset, Jacques Lagnel, Delphine Madur, Laurence Moreau, Stéphane Nicolas, Elise Peluso and Yannick De Oliveira "ThaliaDB, a data management web tool for plant breeding and genetic diversity exploration"
#141 Antoine Laporte, Cédric Cassan and Sylvain Prigent "Comparing the evolution of the main biomass compounds of Pinot Noir berries from several Climats de Bourgogne"
#142 Xavier Grand, Emmanuel Combe, Armando Andres Roca Suarez, Guillaume Giraud, Massimiliano Cocca, Fabien Zoulim and Barbara Testoni "Development of high-performance hepatitis B virus Genome Browsers to enable collaborative research"
#143 Matteo Bettiati, Delphine Gey, Marc Dellinger, Pavla Debeljak and Lucie Bittner "RICOTA: Reference Independent COnsensus Transcript Assembler, a pipeline for processing transcriptomic long reads from non-model organisms"
#145 Amel Benarbia, Marina de Miguel Vega, William Marande, Isabelle Dufau, Caroline Callot and Nadine Gautier "Construction and analysis of a grapevine rootstock pangenome to identify genetic variations explaining drought adaptation phenotypes"
#146 Mathilde Rumeau, Robert Bossy, Clara Sauvion, Valentin Loux, Mouhamadou Ba, Christelle Knudsen, Sylvie Combes, Claire Nedellec and Louise Deleger "HoloOLIGO corpus, a manually annotated text dataset supporting schema-based relational information extraction for mammalian milk oligosaccharide diversity pattern comprehension"
#147 Petra Langendijk-Genevaux, Yves Quentin, Marie Bouvier, Béatrice Clouet D'Orval and Gwennaele Fichant "Phylogenomic analysis and evolutionary insights of SF2 archaeal RNA helicase families"
#148 Tomas Caetano, Peter Redder, Gwennaele Fichant and Roland Barriot "EMOTE-tk: an R library targeted to study the exact RNA ends at the nucleotide resolution"
#149 Amandine Cunty, Bruno Legendre, Anne-Laure Boutigny, Valerie Olivier and Déborah Merda "Genomic analyses of Xylella fastidiosa subspecies pauca ST53 detected in France revealed link between French and Italian strains"
#150 Anthony Bertrand, Bruno Charbit, Florian Dubois, Lluis Quintana-Murci, Violaine Saint-André and Darragh Duffy "Identification of transcriptional regulatory networks that control variable human immune responses."
#151 Dorine Merlat, Ricarda Lehmitz, Peter Decker, Arnaud Kress, Clément Schneider, Gemma Collins, Miklos Bí¡lint and Odile Lecompte "Annotation of Myriapoda genomes with a new tool: EXOGAP"
#152 Claire Delamare-Deboutteville, Chloé Cerutti, Tom Lesluyes, Luka Pavageau, Céline Mazzotti, Antoine Graffeuil, Coralie Franck, Jill Corre and Hervé Avet-Loiseau "Analysis of single-cell RNA-seq data for characterization of subclonal heterogeneity in multiple myeloma patients"
#153 Sofiane Sadat, Arnaud Ferré, Guillaume Kon Kam King and Sofia Lotfi "Can genome-based Large Language Models predict gene expression?"
#154 Fabien Mareuil, Alexandra Moine-Franel, Anuradha Kar, Michael Nilges, Constantin Bogdan Ciambur and Olivier Sperandio "Protein Interaction Explorer (PIE): A Web Platform for Exploring Protein-Protein Interactions"
#155 Martina Gallinaro, Vincenzo Alfano, Coline Kerbaj, Giulia Maccarone, Giovanni Malerba, Massimo Levrero and Massimiliano Cocca "Empowering bulk RNA-seq deconvolution algorithms by integrating multiple transcriptomics datasets"
#156 Ivan Wawrzyniak, Reginald Akossi, Emmanuelle Lerat, Frederic Delbac and Eric Peyretaillade "Genomic and transcriptomic landscape of the microsporidia parasite Anncaliia algerae"
.#157 Sébastien Gradit, Axel Cournac and Romain Koszul "HiC-BERG : Hi-C Biological Estimation of Repeated Elements in Genomes"
#158 Louis Carrel-Billiard, Elodie Laine and Hugues Richard "Exploring the Emergence of Alternative Protein Region Usage Throughout Evolution: Kinases as a Case Study"
#159 Marie-Christine Carpentier, Christel Llauro, Eric Lasserre, Marie Mirouze, Rod A. Wing and Olivier Panaud "Detection of transcriptomic structural variations in wild rice using Nanopore direct RNA sequencing"
#160 Julien Guidihounme, Simon De-Givry and Benjamin Linard "Simplified pangenome graph traversals with PSSM scoring : search for genomic differentials"
#161 Guillaume Laisney, David Benaben, Christophe Duperier, Matéo Boudet, Franck Giacomoni and Olivier Filangi "Metabolomic Semantic Datalake : A Scalable Approach to Managing Metabolomics Semantic Resources"
#162 José-Américo Nabuco Leva Ferreira de Freitas and Oliver Bischof "Dynamic modeling of the transcriptional regulatory network controlling cellular senescence"
#163 Antonin Colajanni, Raluca Uricaru, Patricia Thébault and Rodolphe Thiébaut "Characterizing circulating microbiota from public sequencing data: a comparison of the state-of-the-art methods"
#164 Juliette Soulier, Sandra Curras Alonso, Maxime Dubail, Chloé Lafouasse, Marine Lefevre, Mylène Bohec, Pierre Verrelle, Nicolas Girard, Agathe Segui-Givelet, Arturo Londono-Vallejo and Charles Fouillade "Radiotherapy triggers neo angiogenesis in human lungs"
#165 Louis Paré, Philippe Bordron, Laurent David, Maxime Mahé, Audrey Bihouée and Damien Eveillard "HUMESS: A tool to automatically reconstruct human metabolic models and improve transcriptomic data interpretation."
#166 Julien Raynal, Benoí®t Ballester, Laurent Brehelin and Charles-Henri Lecellier "Evaluation of machine learning predictions at genome scale"
#167 Emeline Bruyère, Romane Junker, Sandra Dérozier, Hélène Chiapello and Guillaume Gautreau "To the species level and beyond : a rationalized approach to study pangenomes"
#169 Sébastien Cabanac, Christophe Dunand and Catherine Mathé "Identify flood resistance mechanisms in plants using a local score approach applied to Genome-Environment Association"
#170 Mehdi Bourema, Lucas Auer and Marc Buée " FunGAAL - Fungal Gene Annotation: Accuracy and Limits"
#171 Marine Bergot, David Vallenet, Violette Da Cunha and Caroline Monteil "MetaCoCo : a tool to predict metabolic pathways in prokaryotes"
#172 Giann Karlo Aguirre-Samboní, Gwenaëlle Lemoine, Julio Molineros, Florian Massip and Chloé-Agathe Azencott "Psoriasis: A Case Study on Using Biological Networks for Gene Discovery"
#173 Valentin Loux, Mouhamadou Ba, Helene Chiapello, Christelle Hennequet-Antier, Mahendra Mariadassou, Véronique Martin, Cédric Midoux, Aaron Millan-Oropeza, Axel Nsabiyumva, Olivier Rué, Valérie Vidal, Mariène Wan and Sophie Schbath "The Migale bioinformatics core facility"
#175 Lucas Auer, Marc Buée, Annegret Kohler, Igor V. Grigoriev and Francis Martin "Metatranscriptomics sheds light on the links between the functional traits of fungal guilds and ecological processes in forest soil ecosystems"
#176 Adrien Mazuel, Pierre Milpied and Bertrand Escaliere "A pipeline for optimizing cell segmentation of probe-based single-cell spatial transcriptomics data"
#190 Yohan Hernandez-Courbevoie, Areski Flissi, Fabrice Bray and Hélène Touzet "PAMPA: Protein Analysis by Mass Spectrometry for Ancient Species"
#234 Karl Baltazart, Céline Poux and Hélène Touzet "Reconstruction of protein sequences for taxonomic recognition of fossil taxa"
#256 Guillaume Gautreau, Thomas Derrien and Camille Marchet "A workshop on Methods for Interfacing with Graphs of Genomic Sequences"
#258 Violaine Saint-André, Bruno Charbit, Anne Biton, Anthony Bertrand, Florian Dubois, Vincent Rouilly, Céline Possémé, Maxime Rotival, Jacob Bergstedt, Etienne Patin, Mathew Albert, Lluis Quintana-Murci and Darragh Duffy "Smoking changes adaptive immunity with persistent effects"
Demonstration of the following tools (15 minutes each):
- #99: "ToulligQC 2.6: fast and comprehensive quality control for Oxford Nanopore sequencing data" Ali Hamaroui, Salomé Brunon and Laurent Jourdren
- #181: "RFLOMICS: Interactive web application for multi-omics data analysis" Nadia Bessoltane, Delphine Charif, Audrey Hulot, Christine Paysant-Le-Roux and Gwendal Cueff
| 14:00 | Using data science to build a bridge from model systems to human disease |
SFBI : Société Française de Bioinformatique
- Présentation du bilan moral
- Présentation du bilan financier
- Résultats des votes du renouvellement du bureau
- Présentation des actions en cours et futurs projet
Présentatrices: Sandra Dérozier et Anna-Sophie Fiston Lavier.
Presentation of the following networks:
- Guided tour
- Urban challenge
- Karaoke
- Retrogaming
- Origami
Full description at: https://jobim2024.sciencesconf.org/page/social_events