Hub members Have many expertise, covering most of the fields in bioinformatics and biostatistics. You'll find below a non-exhaustive list of these expertise
Searched keyword : Data Visualization
Related people (10)
Developing and evaluating bioinformatic tools for: – next generation sequencing data – genome analysis & comparison Specialties:Genome & Transcriptome Bioinformatics
Data managementData VisualizationGenomicsNon coding RNASequence analysisTranscriptomicsGenome analysisBiostatisticsProgram developmentScientific computingData and text miningBiosensors and biomarkersEpidemiology and public health
- Identification of non-coding RNAs under the control of the PerR regulators(Nadia BENAROUDJ - Biology of Spirochetes) - In Progress
- Tissue-resident stromal cell heterogeneity(Lucie PEDUTO - Stroma, Inflammation and Tissue Repair) - In Progress
- Role of small non coding RNAs in the adaptive response to oxidative stress in pathogenic Leptospira(NADIA BENAROUDJ - Biology of Spirochetes) - In Progress
One of my projects consists in developing GRAVITY, a java tool based on Cytoscape to integrate genetic variants within protein-protein interaction networks to allow the visual and statistical interpretation of next-generation sequencing data, ultimately helping geneticists and clinicians to identify causal variants and better diagnose their patients. I’m also involved in several other projects in the lab, taking part in the design of pipelines for the processing and the analysis of genomics data, including SNP arrays, whole-exome and whole-genome sequencing data. This means being confronted to the big data problematic, the unit having to manage hundreds of terabytes of genomics data. Finally, I am now analysing these data in order to identify possible causes for autism, to help clinicians with their diagnosis but also to better understand the biological mechanisms at play in this complex disease. This is done through the project aiming at understanding the genetic architecture of autism in the Faroe Islands, and also with the newly starting IMI2 European project AIMS2-Trials.
AlgorithmicsData managementData VisualizationGenomicsMachine learningProteomicsGenome analysisBiostatisticsProgram developmentScientific computingApplication of mathematics in sciencesExploratory data analysisSofware development and engineeringData and text miningGenetics
I joined the Bioinformatics and Biostatistics Hub at Institut Pasteur in 2016 where I am currently developing pipelines related to NGS for the Biomics Pôle. I have an interdisciplinary research experience: after a PhD in Astronomy (gravitational wave data analysis), I joined several research institute to work in the fields of plant modelling (INRIA, Montpellier, 2008-2011), System Biology — in particular logical modelling (EMBL-EBI Cambridge, U.K., 2011-2015), and drug discovery (Sanger Institute, Cambridge, U.K.), 2015). On a daily basis, I use data analysis and machine learning techniques within high-quality software to tackle scientific problems.
AlgorithmicsData managementData VisualizationGenome assemblyGenomicsMachine learningModelingScientific computingDatabases and ontologiesSofware development and engineeringData and text miningIllumina HiSeqGraph theory and analysisIllumina MiSeq
Data VisualizationMachine learningStatistical inferenceBiostatisticsApplication of mathematics in sciencesDimensional reductionMultidimensional data analysis
- Assessing the role of gut microbiota in spondyloarthritis patients and impact of anti-TNF treament on its composition(Corinne RICHARD-MICELI - Immunoregulation) - Closed
- ICARE(Nicolas ROSINE - Immunoregulation) - In Progress
- Optimisation of freeze and conservation method of peripherical blood mononucleated cells(SORDOILLET VALLIER - Other) - Pending
Bernd Jagla received his PhD in bioinformatics (department of Biology, Chemistry, and Parmacy) from the Free University in Berlin, Germany in 1999. Before joining the Institut Pasteur, he worked for almost ten years in New York City, including as an associate research scientist in the Joint Centers for System Biology (Columbia University) and at the Columbia University Screening Center led by Dr J.E. Rothman. He joined the Institut Pasteur in 2009 to take charge of the bioinformatic needs at the Transcriptome et Epigenome platform, focusing on Next Generation Sequencing. As of 2016 he is member of the C3BI – HUB Team detached to the Human immunology center (CIH) and provides support for cytometry, next generation sequencing, and microarray data analysis. His areas of interest include the quality assurance and data analysis and visualization at the facility. He also has strong expertise in developing algorithms for function prediction from sequence data, image analysis, analysis of mass spectrometry data, workflow management systems. While at Pasteur he developed: KNIME extensions for Next Generation Sequencing (Link) Post Alignment Visualization and Characterization of High-Throughput Sequencing Experiments (Link) Post Alignment statistics of Illumina reads (Link)
AlgorithmicsChIP-seqData managementData VisualizationImage analysisMachine learningSequence analysisDatabaseGenome analysisBiostatisticsProgram developmentScientific computingData and text miningIllumina HiSeqGraphics and Image ProcessingIllumina MiSeqHigh Throughput ScreeningFlow cytometry/cell sortingPac Bio
After a PhD in Biology in 2011 on population genetics and phylogeography on amazing little amphipods (Crangonyx, Crymostygius) at the University of Reykjavik (Iceland), I pursued my interest in Bioinformatics and Evolutionary Biology in various post-docs in Spain (MNCN Madrid, UB Barcelona). During this time, I investigated transcriptomic landscapes for various non-model species (groups Conus, Junco and Caecilians) using de novo assemblies and participated in the development of TRUFA, a web platform for de novo RNA-seq analysis. In July 2016, I integrated the Revive Consortium and the Epigenetic Regulation unit at Pasteur Institute, where my main focus were transcriptomic and epigenetic analyses on various thematics using short and long reads technologies, with a special interest in alternative splicing events detection. I joined the Bioinformatics and Biostatistics Hub in January 2018. My latest interests are long reads technologies, alternative splicing and achieving reproducibility in Bioinformatics using workflow managers, container technologies and literate programming.
Data managementData VisualizationSequence analysisTranscriptomicsWeb developmentGenome analysisProgram developmentExploratory data analysisSofware development and engineeringGeneticsEvolutionRead mappingWorkflow and pipeline developmentPopulation geneticsMotifs and patterns detectionGrid and cloud computing
HumanInsect or arthropodOther animalAnopheles gambiae (African malaria mosquito)Mouse
- Build a software to decipher Gephyrin alternative transcripts obtained with long read sequencing(allemand ERIC - Epigenetic Regulation) - In Progress
- Transcriptomics of Anopheles – Plasmodium vivax interactions towards identification of malaria transmission blocking targets(Catherine BOURGOUIN - Functional Genetics of Infectious Diseases) - In Progress
- Mapping of Enhancers from transcriptome data(Christian MUCHARDT - Epigenetic Regulation) - In Progress
I have been involved in genomic projects for prokaryotic and human genetic studies (GWAS) since 1998. Currently, I am working on novel visualization techniques to explore large and highly complex data sets. I have develop a web based graphical user interface, called SynTView (http://genopole.pasteur.fr/SynTView/) to visualize biological features in comparative genomic studies. The tool allows interactive visualization of microbial genomes to investigate massive amounts of information efficiently. The software is characterized by the presentation of synthetic organisations of microbial genomes and the visualization of polymorphism data. I am extending this work into designing novel dynamic views for comparative analysis of viruses in emerging disease.
Data VisualizationDatabaseSofware development and engineeringComparative metagenomicsOrthology and paralogy analysis
- Analysis of Internal Deletions in EV71(Bjoern MEYER - Viral Populations and Pathogenesis) - Pending
- Chikungunya virus adaptation to a low temperature in a French population Ae. albopictus(Rachel BELLONE - Arboviruses and Insect Vectors) - Pending
- Single nucleotide polymorphisms and genome organization in members of the genus Yersinia(Javier PIZARRO-CERDA - Yersinia) - Pending
Data managementData VisualizationWeb developmentDatabaseProgram developmentDatabases and ontologiesSofware development and engineeringData integrationWorkflow and pipeline development
- Flemmingsome: A Midbody Remnant Proteome Database(Neetu GUPTA-ROSSI - Membrane Traffic and Cell Division) - Pending
- crispr.pasteur.fr(David BIKARD - Synthetic Biology) - Awaiting Publication
- The Flemmingsome: the proteome of intact cytokinetic midbodies(NEETU GUPTA-ROSSI - Membrane Traffic and Cell Division) - Awaiting Publication
In 2012 I completed my master degree at the MicroScope Platform located at Genoscope (the French National Sequencing Center). I was involved in a project aiming at the management of evolution projects which rely on the Next Generation Sequencing (NGS) technologies to try to decipher the dynamics of genomic changes as well as the molecular bases and the mechanisms underlying adaptative evolution of micro-organisms (Remigi et al. 2014). Since November 2014, I joined the Bioinformatics and Biostatistics HUB at Institut Pasteur. I participated to the creation and updates of the C3BI website. I joined the WINTER group where I’m in charge of web and interface development projects. I have completed an UX-Design training to add extra value to my front-end development skills. I design and develop bioinformatics tools and interfaces that are users oriented.
Data VisualizationWeb developmentDatabaseGenome analysisScientific computingDatabases and ontologiesSofware development and engineeringWorkflow and pipeline development
- An integrated software having a graphical user interface for the analysis of time-lapse images of bacterial microcolonies(Giulia MANINA - Microbial Individuality and Infection) - In Progress
- Development and design of new functionalities for MEMHDX, a web application dedicated to the statistical analysis and vizualization of large HDX-MS datasets.(Sebastien BRIER - Biological NMR Technological Platform) - In Progress
- Genetic and statistical analysis of data produced with the Collaborative Cross at the Institut Pasteur(Xavier MONTAGUTELLI - Mouse Genetics) - In Progress
A computer scientist by training, I am applying this knowledge to solve biological problems and am particularly interested in modelling of biological systems, knowledge inference, ontologies and data visualisation.
AlgorithmicsData VisualizationMetabolomicsModelingPathway AnalysisPhylogeneticsSystems BiologyTool DevelopmentDatabaseProgram developmentScientific computingDatabases and ontologiesApplication of mathematics in sciencesSofware development and engineeringData and text miningEvolutionData integrationGraph theory and analysisWorkflow and pipeline developmentDiscrete and numerical optimization
VirusHuman Immunodeficiency virus (HIV)
- Modeling mitochondrial metabolism dormant Cryptococcus neoformans(Benjamin HOMMEL - Molecular Mycology) - Closed
- Measles virus protein C interplay with cellular apoptotic pathways; applications for cancer treatment(Alice MEIGNIÉ - Viral Genomics and Vaccination) - Closed
- Diffusion des mutations de résistance du VIH : modèles et méthodes d’estimation(Olivier GASCUEL - Evolutionary Bioinformatics) - In Progress
Related projects (28)
Candida albicans is responsible for the majority of life-threatening fungal infections occurring in hospitalized patients and is also the most frequently isolated fungal commensal of humans. Microevolution of C. albicans isolates has been observed in a number of instances, being in particular characterized by loss-of-heterozygosity events. Yet, most studies that have investigated such microevolutions have not used whole-genome sequencing. In this project, we aim to characterize C. albicans microevolution at the genome-wide level. To this aim, we will take advantage of multiple isolates collected at the same time in healthy individuals and that share the same molecular type, thus providing information on the extent of genetic diversity of commensal isolates. We will also take advantage of series of isolates collected in patients with different forms of candidiasis and/or that have received antifungal therapy, thus providing information of the impact of pathogenic interaction and antifungal treatment on genome dynamics.
Across bacterial, archaeal and eukaryotic kingdoms, heat shock proteins (HSPs) are defined as a class of highly conserved chaperone proteins that are rapidly induced in response to temperature increase through dedicated heat shock transcription factors. While this transcriptional response governs cellular adaptation of fungal, plant and animal cells to thermic shock and other forms of stress, early-branching eukaryotes of the kinetoplastid order, including trypanosomatid parasites, lack classical mechanisms of transcriptional regulation and show largely constitutive expression of HSPs, thus raising important questions on the function of HSPs in the absence of stress and the regulation of their chaperone activity in response to environmental adversity. Understanding parasite-specific mechanisms of stress-response regulation is especially relevant for protozoan parasites of the genus Leishmania that are adapted for survival inside highly toxic phagolysosomes of host macrophages causing the various immuno-pathologies of leishmaniasis. To gain first insight into the role the heat shock repsonse for Leishmania differentiation and pathogenicity, we are studying the evolution and function of members of the HSP70 protein family combining bio-informatics and transgenics apporahces.
Mapping of research themes and fields of expertise available in the Institut Pasteur international Network
Using data extracted from Pubmed, we would like to develop a tool for systematic analysis of research themes and fields of expertise available in the Institut Pasteur International Network (IPIN). The tool would be available to the Pasteur community and could be questioned using search terms in Pubmed, identifying articles involving research teams from IPIN and displaying the name of authors, research units, and location in a visual format. We hope this tool would enable researchers to identify colleagues for sharing expertise and developing collaborations.
The aim of the project is to create a viewer that will help visualisation and correlation between genomic, transcriptomic, proteomic and metabolomic data generated by the comparison of amastigote and promastigote stages of the Leishmania donovani parasite.
Legionella pneumophila is from a genomic point of view a very diverse species, however, only few clones are responsible for over 50% of all human disease cases. Thus we aim to understand the evolution and emergence of these 5 major disease related clones. We have sequenced a large number L. pneumophila strains belonging to these clones and are undertaking comparative and phylogenetic genome analyses.
Genomic DNA is hierarchically packed within the living cells and genome duplication requires the concerted effort of many thousands of individual replication units. As such, to ensure the integrity of transmission of the genetic information, both eukaryotes and prokaryotes have evolved sophisticated mechanisms to monitor DNA replication. Some of these mechanisms aim to maintain both a temporal and a spatial organization of the replication program, leading to multiple replication time regions and the compartmentalization into replication foci, subnuclear sites which accumulate numerous DNA replication factors. It should be noted that Saccharomyces cerevisiae represents an exception to the standard eukaryotic strategy for genome duplication. Similar to bacteria, S. cerevisiae possess well-defined replication origin sequences that can fire at a very efficient rate during S phase, leading to a very homogenous pattern of DNA replication. A common mo del suggests that, once replication starts dynamic events take place since co-regulated replication forks, having similar replication timing, cluster within a discrete number of foci that show distinct patterns of nuclear localization over the S-phase. Once initiated, the DNA synthesis might be compromised if the replication fork encounters an RFB (Replication Fork Barrier) such as DNA lesions, tightly bound protein-DNA complexes etc. The RFBs are considered a potential source of genetic instability and may lead to many chromosomal rearrangements. As a consequence, eukaryotes employ a complex DNA damage response against RFBs, which aims to maintain the stability of the stalled forks and provides the time required to repair and resume replication. Recent observations suggest that the non-random organization of the nucleus affects where repair occurs. The aim of this project is to reach a better understanding of the influence of the nuclear spatial architecture and organization at replication fork blocks.
DNA topoisomerase IB (Topo IB) enzymes are ubiquitous in eukaryotes, where they represent the major DNA topoisomerase I activity. However, Topo IB sequences are also found in other phyla, such as archaea and bacteria, as well as viruses. Given the large amount of sequenced data available in public databases, this project aims to infer a robust Topo IB gene tree based on a representative set of homologous sequences gathered from a large taxonomic sample.
Les cyanobactéries sont des microorganismes qui prolifèrent dans de nombreux plans d’eau et perturbent leurs fonctionnements et leurs usages car elles sont capables de produire des toxines dangereuses pour la santé humaine et animale. Si la réglementation sanitaire est basée, pour l’instant, sur la surveillance d’une seule toxine, il est désormais connu que ces microorganismes sont capables d’en synthétiser un grand nombre qu’il conviendrait de mieux prendre en compte dans le futur. C’est pourquoi, dans le but de mieux connaître le potentiel toxique des cyanobactéries, ma thèse s'applique, par des études sur leur génome et par une approche de chimie, à caractériser les gènes impliqués dans la synthèse de ces métabolites ainsi que les métabolites produits par ces gènes, à déterminer sur des souches de culture et dans des échantillons naturels provenant de plans d’eau d’Ile de France quel est le potentiel de production de ces métabolites et à mieux comprendre les facteurs environnementaux qui favorisent cette production. Deux équipes de Paris (Pasteur et iEES) sont associées sur ce travail qui implique également des collaborations étrangères. S'il est désormais bien connu qu'une part importante du métabolisme des cyanobactéries qui sont des microorganismes photosynthétiques, est régulée en fonction des phases de lumière et d'obscurité, les connaissances disponibles sur la synthèse des métabolites secondaires sont en revanche beaucoup plus limitées. Ces métabolites ont pourtant un double intérêt puisque certains sont toxiques pour l'Homme alors que d'autres ont un intérêt pharmaceutique potentiel. Leur synthèse repose sur l'expression de clusters de gènes pouvant être de très grande taille (jusqu’à 100 kb par région).
Horizontal gene transfer (HGT) is a major driving force of bacterial diversification. For mycobacteria, a special type of HGT was described in Mycobacterium smegmatis which is linked to distributive conjugal transfer (Gray et al., PLoS Biology, 2013). In the current project we are trying to reproduce the results and explore the process.
Recently 6 strains of Leptospira kirschneri ser grippotyphosa have been sequenced, assembled and annotated. These strains possess 99% genome similarity, but their provenance, virulence and growth characteristics remains different. We would like analyze the SNP of each strain using the SynTView/SNPView tool.
We wish to offer to the community of microbial virologists a place where they can store and find results of host range determination for microbial viruses
Over the past three decades Listeria has become a model organism for host-pathogen interactions, leading to critical discoveries in a broad range of fields including virulence-factor regulation, cell biology, and bacterial pathophysiology. More recently, the number of Listeria “omics” data produced has increased exponentially, not only in term of number, but also in term of heterogeneity of data. There are now more than 40 published Listeria genomes, around 400 different transcriptomics data and 10 proteomics studies available. The capacity to analyze these data through a systems biology approach and generate tools for biologists to analyze these data themselves is a challenge for bioinformaticians. To tackle these challenges we are developing a web-based platform named Listeriomics which integrates different type of tools for “omics” data manipulation, the two most important being: 1) a genome viewer for displaying gene expression array, tiling array, and RNASeq data along with proteomics and genomics data. 2) An expression atlas, which is a query based tool which connects every genomics elements (genes, smallRNAs, antisenseRNAs) to the most relevant “omics” data. Our platform integrates already all genomics, and transcriptomics data ever published on Listeria and will thus allow biologists to analyze dynamically all these data, and bioinformaticians to have a central database for network analysis. Finally, it has been used already several times in our laboratory for different types of studies, including transcriptomics analysis in different biological conditions, and whole genome analysis of Listeria proteins N-termini. This project is funded by an ANR Investissement d'avenir: BACNET 10-BINF-02-01
Recent progress in sequencing and bioinformatics methods have given access to ancient DNA. This project aims at understanding the differential evolutionary pressure on the key proteins implicated in the nervous system.
Comparative analysis of the virulence plasmids of Shigella Spp. and entero-invasive Escherichia coli
Context. Bacteria of the genus Shigella and strains of entero-invasive Escherichia coli (EIEC) are responsible of bacillary dysentery (shigellosis) in humans. Although (very) closely related to E. coli, the genus Shigella is divided in four "species": S. boydii, S. dysenteriae, S. flexneri and S. sonnei. Most virulence determinants enabling these bacteria to enter into and disseminate within epithelial cells are encoded by a 200-kb virulence plasmid (VP). The first complete sequence of a VP (pWR100 from a S. flexneri strain of serotype 5a) was determined by our laboratory in 2000. The VP contains genes of different origins, as attested by their G+C content ranging from 30 to 60%, traces of four plasmids and a large numbers of various insertions sequences (IS) representing 30-40% of the total sequence (Buchrieser et al., 2000). In addition to IS sequences, the VP carries members of several multigene families (exhibiting over 90% identity). Such repeated sequences are potentially prone to recombination (allelic exchange, gene conversion) and deletion. Based on the analysis of three genes carried by the VP, it has been proposed that, depending of the species / phylogenetic group, there are two forms of the VP (pInvA & pInvB) that were acquired independently in different original E. coli strains. General questions. What are the architectures of the VP from different phylogenetic groups and how different are pInvA and pInvB ? Which genes are conserved in all VP and which genes are unique to some VP ? Did recombinations occur and, if so, where and when ? To answer these questions, a comparative analysis of the genetic organization and gene conservation among the VP from different phylogenetic groups of Shigella/EIEC has been undertaken using the available complete (or presented as such) sequences of 15 VP, including three members for each of five phylogenetic groups (S. boydii, S. dysenteriae 1, S. flexneri, S. sonnei and EIEC).
Measles virus protein C interplay with cellular apoptotic pathways; applications for cancer treatment
Measles virus protein C interplay with cellular apoptotic pathways; applications for cancer treatment.
In recent years, large genome-wide association studies (GWAS) have been successful in identifying thousands of significant genetic associations for multiple traits and diseases1. In the course of this endeavor, sample size has proven to be the key factor for identifying new variants. For example, GWAS of body mass index (BMI), now including up to 350,000 individuals from more than 100 cohorts, have been able to identify genetic variant that explain as low as 0.02% of BMI variance2. While standard approaches for detecting new genetic variants associated with traits and diseases will go on as sample size increases, multivariate analyses have been proposed as an alternative strategy for both improving detection of new variants and exploring the multidimensional components of complex traits and diseases. Intuitively, multivariate analysis can be used to improve detection of variants displaying a pleiotropic effect3 by accumulating moderate evidence of association across multiple traits and diseases. Several recent examples have been published about not only GWAS hit overlap across related traits4, but also of genome-wide shared genetic effect5. Multivariate analyses of GWAS have also proven useful to understand shared genetics between diseases5, and potential causal relationship between phenotypes using Mendelian randomization (MR)6. Importantly, most of existing multivariate methods are based on GWAS summary statistics, while approaches based on individual-level data have been seldom considered because of major practical and ethical issues. In the continuity of ongoing work on multi-phenotype analysis (Aschard et al 20147, Aschard et al 20158), we developed an effective and robust multivariate approach of GWAS summary statistics that addresses the major barriers of existing approaches, i.e. the presence of correlation between studies that would exists when GWAS analyzed share sample9-16. Our approach consists in a robust omnibus multivariate test of GWAS summary statis
Innate lymphoid cells (ILCs) are the most recently identified components of the innate immune system. ILCs colonize different tissue sites and react promptly to microenvironmental perturbations. Due to their high plasticity, ILCs can shape their functional output in response to local cues. As such, ILCs play roles under homeostatic conditions and in the context of infection, chronic inflammation, metabolic diseases and cancer. Diverse ILC subsets (NK cells, ILC2) have been shown to regulate the metabolic homeostasis. Metabolic states affect cellular functions and have been shown to play an important role in the regulation of adaptive immunity. In contrast, almost nothing is known about innate lymphocytes metabolism and the importance of energy regulation for ILC function. This project will study metabolic profiles in human ILC subsets under diverse environmental conditions. Enhancing or interfering with ILC activity could ultimately represent a novel useful therapy for chronic inflammatory diseases.
Chikungunya and Zika viruses have recently extended to previously disease free areas. In addition, their high mutations rates and fast replication lead to the emergence of new strains potentially able to disseminate in these new territories, through the apparition of novel characteristics. The African (MR-766) and American (PRVABC-59) Zika strains, and the La Reunion Island and Caribbean Chikungunya strains, were passaged several times in mammalian or mosquito cells only or alternatively in one and the other. In vivo experiments on mosquitoes compare the ability of these different strains to evolve and be transmitted. Furthermore, deep sequencing was performed in order to look for new minority variants in these different conditions for both viruses and strains. This work focuses on these two viruses’ genetic evolution to identify the mechanisms involved in transmission, and to predict the emergence of future variants.
CRISPR-Cas systems provide immunity to bacteria and archaea. One of the reasons these systems have attracted so much attention in the past few years is due to the discovery of nucleases among the Cas proteins that are guided by small RNAs to bind and degrade homologous DNA. The introduction of breaks in DNA that can be repaired either in a controlled or uncontrolled manner now is a widely used method to introduce mutations in genomes. We are interested in probing the CRISPR-Cas system efficiency for different targets.
The aim of the project is to develop a powerful software tool to integrate MS data for the visualization of the protein coverage and mapping of Post Translational Modifications (PTMs). Even if some to
Our goal is to have a bioinformatic tool that performs the 2 x 2 comparison of matrices of numbers in matrix batches. Each matrix corresponds to the use of gene fragments (V or J) to create a re-arran
Bacteriophages infect bacteria. One bacteriophage can infect several strains. Around the world, many labs have performed spot tests to determine the host range of bacteriophages but this information i
crispr.pasteur.fr is a website providing resources to visualize CRISPR screen data and design CRISPR experiments in bacteria
Members of the genus Yersinia include environmental as well as pathogenic bacteria. Pathogenic species (Y. pestis, Y. pseudotuberculosis and Y. enterocolitica) have historically been targets for resea
The chikungunya virus (CHIKV) is an emerging mosquito-borne virus which has widely spread around the world in the last two decades. The virus is transmitted between human hosts by Aedes mosquitoes, in
MacSyFinder is a framework to model and detect macromolecular systems in genomes using decision rules (gene content and architecture) and similarity searches (protein profiles). It was initially devel