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 : Web development
Related people (8)
Web developmentDatabases and ontologies
- Klebsiella MALDI-Typer(Sebastien BRIDEL - Biodiversity and Epidemiology of Bacterial Pathogens) - Closed
- BIGSdb-Pasteur web pages and design renewal(Federica PALMA - Biological Resource Center of Institut Pasteur (CRBIP)) - In Progress
- Récupération des données associées aux séquences de génomes de Klebsiella pneumoniae téléchargées du NCBI(Nicolas CABANEL - Ecology and Evolution of Antibiotics Resistance) - Closed
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) - Closed
- Transcriptomics of Anopheles – Plasmodium vivax interactions towards identification of malaria transmission blocking targets(Catherine BOURGOUIN - Functional Genetics of Infectious Diseases) - Closed
- Mapping of Enhancers from transcriptome data(Christian MUCHARDT - Epigenetic Regulation) - Closed
After a PhD in biochemistry of the rapeseed proteins, during which I developed my first automated scripts for handling data processing and analysis, I join Danone research facility center for developing multivariate models for the prediction of milk protein composition using infrared spectrometry.
As I was already developing my own informatics tools, I decided to join the course of informatic for biology of the Institut Pasteur in 2007. At the end of the course I was recruited by the Institute and integrate the unit of “génétique des interactions macromoléculaires” of Alain Jacquier. Within this group, I learn to handle sequencing data and I developed processing and analysis tools using python and R. I also create a genome browser and database system for storing, retrieving and visualizing microarray data. After 8 years within the Alain Jacquier’s lab, I join the Hub of bioinformatics and biostatistics as co-head of the team.
ClusteringData managementSequence analysisTranscriptomicsWeb developmentDatabaseGenome analysisProgram developmentScientific computingExploratory data analysisData and text miningIllumina HiSeqRead mappingLIMSIllumina MiSeqHigh Throughput ScreeningMultidimensional data analysisWorkflow and pipeline developmentRibosome profilingMotifs and patterns detection
- SHERLOCK4HAT - WP1.1(Brice ROTUREAU - Group: Trypanosome transmission) - Closed
- Remettre les servers Genolist comme LegioList, TuberclListe, Colibri etc en service(Carmen BUCHRIESER - Biology Of Intracellular Bacteria) - Closed
- Identification of eukaryotic 5'UTRs(Arnaud ECHARD - Membrane Traffic and Cell Division) - Closed
After a Master degree in Genome Analysis and Molecular Modeling at Denis Diderot University, I did a PhD in NMR / bioinformatics at Denis Diderot University, where I worked on the development and use of a software named DaDiModO which uses SAXS data and RDC/NMR data to calculate models of structural proteins. After a postdoc aiming to adapt ARIA software to allow execution on computing grid in the Structural Bioinformatic Team at Institut Pasteur in collaboration with IBCP, I joined CIB/DSI Team where I was responsible for the development of bioinformatics projects and the deployment, maintenance and evolution of the Pasteur Galaxy server. I joined the Hub/C3BI team in 2017 as research engineer where I’m involved in several projects such as structural bioinformatics, softwares and web development. I am also in charge of the maintenance of the Galaxy Pasteur instance.
Data managementGalaxyStructural bioinformaticsWeb developmentDatabaseProgram developmentScientific computingDatabases and ontologiesWorkflow and pipeline developmentGrid and cloud computing
- SatelliteFinder(Jorge SOUSA - Department of Genomes and Genetics,Microbial Evolutionary Genomics) - In Progress
- Development of a secure API for ARIAweb(Benjamin BARDIAUX - Structural Bioinformatics) - In Progress
- Development of a web server to calculate functional binding sites using Deep Learning(Olivier SPERANDIO - Structural Bioinformatics) - In Progress
Data managementData VisualizationWeb developmentDatabaseProgram developmentDatabases and ontologiesSofware development and engineeringData integrationWorkflow and pipeline development
- An online database of RNA-small molecules complexes for rational drug design(Massimiliano BONOMI - Structural Bioinformatics) - Closed
- Development of a contributor management webpage for iPPI-DB.(Olivier SPERANDIO - Structural Bioinformatics) - In Progress
- JASS 2 : Integrating functional annotation to a multi-trait GWAS web application(HANNA JULIENNE - Statistical Genetics) - In Progress
Graduated in “Structural Genomics and Bioinformatics”, I mainly worked during almost 6 years at the Genoscope (CEA) in the LABGeM team, within the microbial annotation platform MicroScope. I specifically focused on functional annotation and microbial metabolic pathways prediction and reconstruction, through pipeline implementation, database modeling and web interface development. Broadly, interactions in the MicroScope platform allowed me to tackle the whole annotation process: from genome assembly and gene prediction to network reconstruction. I also performed several comparative genomics analyses. As a member of the “Hub team”, I now take part to various projects, linked to HTS data, on different subjects (lncRNAs and stem cells, HIV integration and DNA structure, Ribosomal protein genes and genome evolution, Natural Antisense Transcripts in compact genomes…).
Data managementGenomicsSequence analysisWeb developmentDatabaseGenome analysisDatabases and ontologiesOrthology and paralogy analysisRead mappingSequence homology analysisGene prediction
- Virulence and natural anti-sense RNA in Entamoeba histolytica, the agent of human amoebiasis(Nancy GUILLEN - Bioimage Analysis,Biology of Host-parasite Interactions) - In Progress
- Setup of bioinformatic pipelines for paleo(meta)genomics(Nicolás RASCOVAN - Department of Genomes and Genetics) - In Progress
- Multiparametric immunophenotyping of whole blood in IFN-treated multiple sclerosis patients(Priyanka DEVI - Cytokine Signaling) - Closed
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
- User experience design for Oncodash(Dreo JOHANN - Systems Biology) - In Progress
- Monitoring tool for scientist who have received MAASCC career guidance(Marion GUESSOUM - Other) - Pending
- An online database of RNA-small molecules complexes for rational drug design(Massimiliano BONOMI - Structural Bioinformatics) - Closed
Related projects (30)
Development of a web application and new functionalities for the maintenance and curation of iPPI-DB
A new version of the iPPI-DB, a manually curated database that contains the structure, some physicochemical characteristics, the pharmacological data and the profile of the PPI targets of several hundred modulators of protein-protein interactions.
This new version will include:
- A maintenance application that facilitates and automates the updates of the database. The computation of the various physico-chemical properties of the modulators and chemical similarity screening on the Galaxy server of the Institut Pasteur.
- A new target-centric mode, based on the mapping of all druggable cavities at the core of PPI interfaces throughout the Protein Data Bank.
The ARIA (Ambiguous Restraints for Iterative Assignment) software, developed at the Structural Bioinformatics Unit, automatizes the treatment of NMR data and protein structure calculation by molecular dynamics simulation. To enhance the visibility of the software, it is necessary to develop a new web interface where users will be able to easily manage their data, perform calculations and analyze the results of the ARIA calculations.
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
Common and phylogenetically widespread coding for peptides by bacterial small RNAs – Follow up of a project regarding its journal review
Following a collaboration started a few years ago between a postdoc of the System Biology team (Robin Friedman) and Olivia Doppelt-Azeroual, a publication is in review in the journal Genome Biology. One of the reviewers made comments regarding the database and web interface implemented by Olivia at the time and after a brainstorm on the review, the first author (Robin) needs to make a few modifications on the database. This modification requires Olivia's intervention to update the database and adapt the web application accordingly, in order to display the right information: adding a column in the table with the concerned sRNA names.
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 purpose of this short project is to develop a database that can efficiently store millions of unique molecular compounds along with some of their already calculated properties. The database named BD-CheM should be able to deal with extensive sets of data: millions of compounds and several hundreds of molecular properties. The import of new data should deal with the detection of molecule uniqueness to prevent data redundancy and with multiple sources of molecular compounds to keep track of their origin. The motivation for this project is the imperious necessity for our group to properly store this precious chemical information and efficiently extract subsets of data with appropriate database queries. Such subsets are used by our group to carry out dedicated and tailored chemoinformatics analyses for different specific projects on and off campus.
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 tools already exist, such as peptigram and drawmap, they don’t fully fufill our expectations and are not completely appropriate for us. To develop this integrative tool, we propose to use proteomics datasets obtained for the analysis of modified histones as a pilot. This work will then be published and shared with the scientific community.
The central part of the intercellular bridge connecting the two daughter cells during cytokinesis is a highly dense structure named the Midbody first described by Flemming in 1891. Work in the past ten years revealed that the midbody is a platform that concentrates essential proteins involved in cytokinetic abscission. After abscission, the midbody is cut on both sides, thus generating a midbody remnant (named MBR). The MBR usually interacts with the cell surface of one of the two daughter cells, before being engulfed in a phagocytic-like manner. We also found that the MBR can be easily released from cells before their engulfment by calcium chelation. Of note, MBRs at the cell surface might act as pro-proliferative, signalling entities but the proteins involved and the mechanisms of MBR anchoring are unknown. A previous proteomic study of the midbody conducted by Skop purified intercellular bridges from cell lysates recovered after cell synchronization, microtubule stabilization and detergent treatment. This pioneer proteomic study, although informative, did not allow the recovery of many key known proteins of the midbody. Here, we set up an experimental protocol to purify intact, detergent-free MBRs in order to have the full proteome of this organelle. Quantitative, label-free proteomics enabled us to identify 529 proteins enriched at least 2 times as compared to whole cell lysates, that we named the “Flemmingsome”. Besides known and well-established proteins of the midbody (MKLP1, MgcRacGAP, AuroraB, INCENP, MKLP2, Rab8, Rab11, Rab35, Citron Kinase, ESCRTs…), we identified new and promising candidates potentially involved in cytokinetic abscission. In addition, we identified 27 transmembrane proteins that are excellent candidates for mediating interactions between the MBR and the receiving daughter cells after cytokinetic abscission. We are also currently exploring whether newly identified candidates could participate in the signalling mediated by the MBRs. We would thus like to create a website that recapitulates the findings of our screen. The proteins discovered represent new candidates for the understanding of cytokinesis and tumorigenesis. This should be instrumental in the field as the previous websites are not updated (Microkits, Uniprot) and do not focus on this particular step of cytokinesis.
- The Institut Pasteur genomic taxonomy database of microbial strains (“Pasteur MLST”) is a free, publicly-accessible resource that hosts nucleotide sequence-based definitions of microbial strains, along with information on bacterial isolates (provenance data) and their genomic sequences. The Pasteur MLST database provides universal nomenclatures that are largely adopted for important pathogens (Klebsiella, Listeria, …), and represent a unifying language on strains for microbial population biology. - Unified strain taxonomies facilitate the coordinated international surveillance of bacterial pathogens. Several hundred research laboratories and public health agencies worldwide have deposited novel strain types, sequences and provenance data on their bacterial isolates. - Pasteur MLST is powered by the Open source GPL3 BIGSdb web application developed at Oxford University (Keith Jolley & Martin Maiden). (http://bigsdb.pasteur.fr ). Its evolution in terms of functionality is tightly linked to the developments of the software at Oxford U. Its evolution in terms of contents is managed by dedicated international teams of curators for each bacterial pathogenic species, coordinated by the PasteurMLST team. - The genomic taxonomies hosted at Pasteur MLST represent unique, authoritative resources that are highly valued by the community, as testified by the routine use of Pasteur MLST strain tags (e.g., K. pneumoniae ST258) in the scientific literature. Several labs (National Reference Centers or Units) of Institut Pasteur are coordinating the curation of genomic taxonomies (Klebsiella, Listeria, Corynebacteria, Bordetella, Leptospira, Yersinia, ...). The aim of the project is to obtain support from the C3BI HUB for the maintenance of the BIGSdb instance at Pasteur: deployment, upgrades, installation of API functionality developed by our partner, coping with future IT evolutions, ...
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 is not accessible because there is no tool to process and store it. Developing such a tool will be useful for the phage community but also for the entire community of virologists.
crispr.pasteur.fr is a website providing resources to visualize CRISPR screen data and design CRISPR experiments in bacteria
DISCO-Bac (http://disco-bac.web.pasteur.fr/), a Web server, is a part of a recent publication https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-017-3932-y (Co-authored by former Hub member Olivia Doppelt-Azoueral, who conceived and implemented the DISCO-BAC database and its sophisticated interface). The main result of the paper is to show the widespread existence small peptides across prokaryotes, the predictions being accessible, along with context information, through DISCO-BAC. We have been informed by DSI that "The app is curretly hosted in the wrong zone (for legacy reasons) and you'll have to reinstall it on another VM." The 2017 paper has already been cited 6 times in 2018: https://scholar.google.fr/scholar?cites=4133998924229445176&as_sdt=2005&sciodt=0,5&hl=en, and we believe that its content is only adequately visible through an interface such as DISCO-Bac (on which Olivia has done a great job).
The servers like LegioList are used by my group and many groups around the world working on Legionella pathogenesis since its establishment in 2004. This server has provided us with an important reserach tool and valuable information for research and is providing Institut Pasteur with international visibility
Development and design of new functionalities for MEMHDX, a web application dedicated to the statistical analysis and vizualization of large HDX-MS datasets.
Hydrogen Deuterium eXchange followed by Mass Spectrometry (HDX-MS) is a recognized biophysical tool in structural biology capable of probing protein/ligand interactions, conformational changes, and protein folding and dynamics. Over the last decade, major improvements in the technology have been made (i.e., refrigerated UHPLC system, mass spectrometers with enhance resolution and sensitivity…) allowing the structural analysis of highly challenging biological systems. The characterization of such biological systems results in very complex HDX-MS datasets for which specific analytical software are needed. In this context, our group and the C3Bi have developed “MEMHDX” (Mixed-Effects Model for HDX experiments) to aid in the rapid statistical validation and the visualization of large HDX-MS datasets. This web application is freely accessible to the HDX-MS scientific community at the project home page http://memhdx.c3bi.pasteur.fr The current version of the application allows for the comparison of two unique conditions using only one unique charge state. This limitation has been pointed out by several MEMHDX users. The current project aims at designing and implementing new functionalities in MEMHDX to enhance its analytical capabilities. The possibilities for users to compare multiple HDX-MS conditions using multiple charge states will be introduced within the web application and the visualization tool provided by MEMHDX will be modified accordingly.
The central part of the intercellular bridge connecting the two daughter cells during cytokinesis is a highly dense structure named the Midbody first described by Flemming in 1891. We set up an experimental protocol to purify intact, detergent-free MBRs in order to have the full proteome of this organelle. Quantitative, label-free proteomics enabled us to identify MBR proteins, that we named the “Flemmingsome”, and 489 of them were found enriched as compared to whole cell lysates, thus named \\\"Enriched Flemmingsome\\\" (Addi et al. manuscript submitted). Proteins composing the Enriched Flemmingsome were individually browsed with their Protein and Gene names for their function in cytokinesis or midbody localization on PubMed and the reference indicated on the flemmingsome website. This project aims at keeping this database up-to-date with the literature.
An integrated software having a graphical user interface for the analysis of time-lapse images of bacterial microcolonies
In our laboratory we focus on the single-cell biology of tuberculosis. Phenotypic variation helps bacterial cells to endure stressful environmental conditions, and is one of the possible causes of antibiotic persistence and chronic infections. We have recently demonstrated that phenotypic variation is indeed associated with a different response to a class of antimicrobials, in particular in subpopulations of mycobacteria experiencing different levels of DNA damage. Therefore, targeting phenotypic variation may prove to be a successful strategy to weaken the population and to make it more susceptible to antimicrobials. To probe and target phenotypic variation in mycobacteria, we use time-lapse microfluidic microscopy and spatiotemporal analysis of individual cells and microcolonies. We have recently completed a screening for compounds that target phenotypic variation, generating a large dataset of image sequences. Here we aim to develop an automated and user-friendly software for the analysis of image sequences of bacterial microcolonies. This analysis platform will serve to study not only the physiology of mycobacteria but also of other bacterial species. In conclusion, this analytical tool could be very useful for the microbiology community dealing with live single-cell imaging.
Institut Pasteur and institut Imagine will coordinate a french collection for genome-wide association study of COVID suceptibility and severity. This collection will contribute to the ongoing major international efforts addressing this question (https://www.covid19hg.com), but it will also be a major platform for a range of other national and international collaborations addressing host biology questions, and for integrative approaches including host genomics data (metabolomic, transcriptomic…), epidemiologic data, and virus data. The project is to develop and publish a webpage presenting the collection.
Le projet a pour objectif de développer une page web pour présenter les travaux de modélisation de la pandémie de la COVID-19 au grand public.
JASS is a python package that handles the computation of the joint statistics over sets of selected GWAS results, and the interactive exploration of the results through a web interface (https://jass.pasteur.fr/index.html). The functionalities of the current web interface include: the interactive visualization of multi-trait GWAS results, the sharing of results through a permanent link and generation of static summary plots. This work and its accompanying tools has been described in a publication (Julienne et al, 2020). However, the web interface present several shortcomings that may impede its wider adoption throughout the scientific community. Key additional information could help contextualize the multi-trait GWAS results such as the gene positions or the linkage disequilibrium with the lead SNPs. The interface ergonomics is overall perfectible as we would like to allow for user with a specific biological question to launch computation and visualize results only on their region of interest.
The project aims to develop a website providing information related to BIGSdb-Pasteur, https://bigsdb.pasteur.fr/, and harmonize its web design with Pasteur website
Déploiement sur l'infra-structure de l'Institut Pasteur du LIMS permettant la gestion de la collection “ORFeome humain” à partir d'une base de code open-source contenant deux projets (une API et une interface web). Cet outil informatique permet la gestion de la collection ainsi que des sous-collections qui en découlent, il permet également d'effectuer des recherches multi-critères et d'éditer des listes de cherry-picking dans un format directement utilisable sur la plateforme robotique TECAN. Il s'agit donc d'un interface bioinformatique indispensable à l'utilisation de cette collection de gènes humains.
Klebsiella pathogens affect human and animal health and are widely distributed in the environment. Among these, the Klebsiella pneumoniae species complex, which includes seven phylogroups, is an important cause of community and hospital infections. The Klebsiella oxytoca species complex also causes hospital infections and antibiotic-associated haemorrhagic colitis. The unsuitability of currently used clinical microbiology methods to distinguish species within each of these species’ complexes leads to high rates of misidentifications that are masking the true clinical significance and potential epidemiological specificities of individual species. Through this project, we will propose a single website for Klebsiella species identification by the mean of MALDI-TOF mass spectrometry. This website will host two tools. One is Klebsiella MALDI TypeR, which was built at Pasteur based on the automatic detection of defined biomarkers. The other one is based on machine learning, with a classifier based on a random forest algorithm trained on hundreds to thousands of spectra. The latter was developed in Melbourne University.
We have recently developed and published our last version of iPPI-DB (https://ippidb.pasteur.fr/), our database of protein-protein interactions modulators. Thanks to the group of Hervé Ménager, the database is now hosted at Institut Pasteur and is completely remodeled, with a new web interface. As for many other databases, its success and interest for the community rely on the constant input of new data. For this, we also designed a contributor mode that allows anyone to add published data from the literature using the iPPI-DB interface directly. In order to manage properly the visibility of our contributors, we would need to add a contributor management webpage. As contributors are asked to log in using their ORCID ID, the idea is to use such an ID to depict the individual contributions of each contributor. It could first acquire some data from the ORCID website, and also nicely summarize the publications that each contributor has entered in iPPI-DB. The goal is evidently to convince more and more people to help us maintain iPPI-DB. As now,
We have developed a computer tool, named InDeep, that relies on 3D fully convolutional neural networks to predict functional binding sites at the surface of proteins. These functional binding sites can take two forms, either a epitope binding site (location of a protein-protein interaction), or a druggable binding site (location for the binding of a future drug). Presently, the tool is already used on campus in several structural biology and drug discovery projects to support the identification of chemical probes with therapeutic purposes. This includes SARS-CoV2 projects in collaboration with Fabrice Agou, Félix Rey and Marc Delarue. In its present form, InDeep relies on GPU calculations and has to be used within a Linux Shell in command line and although a pymol plugin has been also developed, it requires some prerequired installations. This impedes its usage by the largest audience especially by the community for whom it was designed, namely biologists and chemists. The purpose of this project would be to design a web interface assisted by a GPU cluster on campus to allow the use of InDeep even for non-computer specialists. This would also be the opportunity to add intuitive functionalities (3D structure visualization, metrics, cross-references to well established databases) to assist the user in his/her attempt to identify pertinent functional binding sites.
Last year, we have developed the ARIAweb server for automated NMR structure calculation. The server was well received by the community (200+ users and ~1400 jobs performed) as of today. ARIAweb offers an interface for data conversion and interactive setup of ARIA calculations. Somme years ago, developers of NMR related software agreed on a new standard for storage of NMR data used in structure calculation, called NEF (NMR Exchange Format). The Structural Bioinformatics, as developer of ARIA committed to adhere to this new standard. A version of ARIA has been developed to read and write NEF files that will allow easy exchange of data and construction pipelines between various NMR software, all using the same NEF format. Since ARIAweb is the only online service for structure calculation from NMR data, we would like to allow other software/servers using NEF to interc-communicate more easily with ARIAweb. The purpose of this project is to develop an application programming interface (API) within the Django framework of ARIAweb to allow for i) user authentication, ii) upload of NEF file along with few parameters in JSON format, iii) submission of job and status tracking and iv) retrieval of results. This API will make ARIAweb a new central hub for other NMR applications (such as the CCPN software suite, https://www.ccpn.ac.uk/v3-software/about).
The majority of approved drugs target proteins, which are encoded in a very small fraction of the human genome. When a pathology is associated with so-called undruggable proteins, an alternative strategy should be sought. In the last twenty years, non-coding RNA molecules have been shown to perform a variety of crucial biological functions, including regulating gene expression, protecting chromosomes from foreign nucleic acids, and guiding telomers synthesis. In this context, targeting either mRNA molecules that are translated into undruggable protein targets or biologically relevant non-coding RNA molecules with small molecules is emerging as a promising therapeutical approach in pathologies such as cancer, viral infections, and neurodegenerative disorders. However, the number of approved drugs that target RNA molecules is still very limited and the existing examples have mostly been found by costly and time-consuming screening experiments. In this project, we aim at building a computational framework to guide the rational design of drugs targeting RNA. To this end, we created a database containing all the experimentally-determined structures of RNA-small molecule complexes deposited in the PDB database. The entries containing drug-like compounds were selected and annotated based on the different biological entities interacting with the ligands. Our database, freely accessible via a web interface, will facilitate i) mapping the chemical space of the small molecules known to bind RNA, ii) understanding the nature of the interactions that drive ligand/RNA recognition, and iii) benchmarking existing tools for in silico protein drug design with RNA targets.
Oncodash is an open-source software developed within the DECIDER H2020 project, which aims at improving clinical decisions via integrating multiple data to overcome chemotherapy resistance in high-grade serous ovarian cancer. The corresponding DECIDER workpackage is led by Johann Dreo and Benno Schwikowski. The current state of the software can be checked at: https://github.com/oncodash/oncodash
Bacteriophage-bacteria interactions are key drivers of microbial populations. They are affected by phage satellites, which may facilitate, hinder or even block phage reproduction. These elements have been known for decades and shown to carry numerous defense systems, antibiotic resistance genes, and virulence factors. Yet, only recently it has become apparent that they are very diverse and numerous. Further understanding of their diversity and distribution has been hampered by the lack of a computational tool to identify them in genomes. `We developed SatelliteFinder, a modular and easily updatable tool to identify satellites in bacterial genomes automatically.