Handles creating, reading and updating teams.

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            "name": "BIG",
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        {
            "id": 21,
            "name": "PRABI-Lyon-Gerland",
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            "description": "Le PRABI-Gerland https://prabi.ibcp.fr localisé à l'IBCP développe les bases de données dans le domaine infectieux, les méthodes de prédiction et d'optimisation des structures 3D de protéines ainsi que les outils et services s'y rapportant. Dans le domaine des services la spécificité de la PF est la bioinformatique structurale (Modélisation moléculaire, prédiction de structure) introduite sur Lyon dès 1986 (il y a 25 ans avant même que le mot n'existe...). Dans ce domaine, l’activité proposée par le PRABI-Gerland s’appuie sur les expertises suivantes:\r\n Prédiction de structure de protéines [G. Deléage]\r\n Modélisation moléculaire [E. Bettler, G. Deléage, R. Terreux]\r\n Intégration de méthodes et serveurs Web [C. Combet, G Deléage]\r\n Serveur Web 3D [E. Bettler, G. Deléage]\r\n Drug design et QSAR (R. Terreux, J.A. Chemelle)\r\n \r\nMots clefs: Bioinformatique structurale, Prédiction de structure, Base de données structurales, Analyse de séquences, Modélisation moléculaire, docking moléculaire.\r\n \r\nPrincipaux sites web: https://prabi.ibcp.fr (site en cours de refonte)\r\n https://geno3d-prabi.ibcp.fr/\r\n https://npsa-prabi.ibcp.fr/\r\n http://sumo-pbil.ibcp.fr\r\n http://espript.ibcp.fr\r\n http://endscript.ibcp.fr\r\nMéthodes de prédiction des structures secondaires de protéines.\r\nPlusieurs méthodes originales ont été développées, Self Optimized Prediction Method (SOPM), génère automatiquement à partir de cette base de donnée, une \"sous-base\" rassemblant les 60 à 80 protéines les plus homologues ou appartenant à la même classe structurale que la protéine\r\nétudiée. En effet, des protéines homologues ont généralement une structure assez proche (30% d'identité indique une architecture semblable). Après une phase d'apprentissage automatique sur cette \"sous-base\", en particulier d'optimisation des paramètres, la prédiction de la structure de la protéine est réalisée. La version SOPMA tire bénéfice des alignements multiples. La méthode MLRC combine les réseaux de neurones avec la méthode SOPMA.\r\n [SOPMA] Self optimised Prediction Method (1995)\r\n [SOPM] Self optimised Prediction Method (1994)\r\n [DPM] Double prediction Method (1987)\r\n [MLRC] Multivariate Linear Regression Combination (1999)\r\n [AMPHIPASEEK] Prediction of membrane anchor helical peptides (2006)\r\n \r\nIntégration de methodes- WebicielsServeur NPS@\r\nLe PRABI Gerland a développé le premier serveur de mail Français pour la prédiction de structures secondaires de protéines (80 000 prédictions en tout). Ensuite ces méthodes ont été intégrées dans [NPS@ 2000]. Le serveur est actuellement dans sa version 3. Dans le cadre de RENABI-IFB, ce serveur généraliste de séquences couplé aux prédictions de structures sera mis à jour en termes d’ergonomie, d’interface et de conception. Mise à disposition d’outils et de services en ligne correspondant aux domaines d’expertise du laboratoire d’accueil de la PF.\r\n \r\nServeur Web ESPript/ENDscript\r\nA partir d’une protéine de structure connue (code ou fichier PDB), le serveur ENDscript produit, en quelques secondes et de manière automatisée, plusieurs illustrations téléchargeables dans des formats usuels (PostScript, PDF, PNG et TIFF) :\r\n1/ Une première figure, générée par le logiciel ESPript, présente la séquence de la protéine d’intérêt agrémentée de ses éléments de structure secondaire, de l’accessibilité au solvant et de l’hydropathie par résidu. Si disponibles, sont aussi représentés les contacts cristallographiques et non-cristallographiques protéine/protéine et/ou protéine/ligand ainsi que les résidus impliqués dans des ponts disulfures.\r\n2/ Une seconde figure ESPript montre, en plus des informations précédentes, un alignement multiple de séquences des protéines homologues coloré en fonction de la conservation des résidus et agrémenté des éléments de structure secondaire de ces dernières si leurs structures sont connues. \r\n3/ Deux représentations 3D interactives visualisables par le logiciel PyMOL : a) une représentation en ruban, colorée en fonction de la conservation de séquence. b) une représentation en tube dont le diamètre est proportionnel à la déviation structurale (rmsd) entre la protéine d’intérêt et les protéines homologues de structure connue. De plus, si disponible, peuvent être affichés : l’assemblage de l’unité biologique, les modèles RMN multiples, les ligands et les résidus en contact avec ces derniers.\r\nLe serveur ESPript permet, en complément d’ENDscript ou de manière autonome, de représenter des alignements multiples de séquences avec la possibilité d’ajouter des marqueurs définis par l’utilisateur de manière à produire des figures facilitant l’analyse ou dédiées aux communications scientifiques.\r\n \r\nModélisation moléculaire\r\nUn serveur Web de modélisation moléculaire automatique de structure 3D de protéines appelé geno3D est disponible depsuis 2002 qui permet aux biologistes et biochimistes d'obtenir un modèle 3D de qualité si la séquence \"query\" présente plus de 35% d'identité avec une protéine de structure 3D connue. Le principe de cette modélisation consiste à appliquer les techniques de modélisation sous contraintes à la protéine à modéliser (de type RMN) à partir d'un jeu de contraintes calculées sur l'empreinte structurale. Plusieurs empreintes sont utilisables, le ligand (si présent) est replacé dans les modèles, 10 modèles sont générés. Les résultats sont proposés sous la forme d’une archive récupérable et les résultats sont conservés 8 jours sur le serveur. Ce serveur génère 100 modèles/mois. Un système intégré de modélisation moléculaire (MAGOS ) à grande échelle de protéomes entiers a été utilisé pour des protéomes de virus (modeome3D) et de plantes (arabidome3D).\r\n \r\nDocking et sites 3D- chemo-informatique\r\nUne méthode bioinformatique SUMO a été développée permettant de détecter des sites 3D fonctionnels communs à plusieurs protéines. L’approche a fait l’objet d’un brevet déposé par le CNRS et d'un serveur Web pour rendre utilisable la méthode par la communauté académique.\r\nDans un travail récent, nous avons réévalué les paramètres et avons montré que la qualité de comparaison était améliorée tout comme la rapidité du calcul. Cette méthode a été appliquée pour établir une classification des antibiotiques à noyau ß lactame.",
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            "logo_url": "https://www.imgt.org/images/logo_IMGT.png",
            "description": "IMGT®, the international ImMunoGeneTics information system®, is the international reference in immunogenetics and immunoinformatics, created in 1989 at the University of Montpellier and the CNRS. IMGT® is a high-quality integrated knowledge resource specialized in the immunoglobulins (IG) or antibodies, T cell receptors (TR), major histocompatibility (MH) of human and other vertebrate species, and in the immunoglobulin superfamily (IgSF), MH superfamily (MhSF) and related proteins of the immune system (RPI) of vertebrates and invertebrates.",
            "expertise": [],
            "expertise_description": "The IMGT platform specializes in the nomenclature and classification of immunoglobulin genes and T cell receptors, facilitating research on the immune response. It offers databases and tools along three axes: genomics, the expressed repertoire, and proteins (including crystallographic structure).",
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            "homepage": "https://www.imgt.org/",
            "unitId": "",
            "address": "Faculté de Pharmacie, \r\n15 avenue Charles Flahault",
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            "country": "France",
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                    "id": 99,
                    "name": "University of Montpellier",
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            ],
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                "Immune repertoire analysis",
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            "tools": [
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                "IMGT_HighV-QUEST",
                "IMGT_mAb-DB",
                "IMGT-ONTOLOGY",
                "imgt_v-quest"
            ],
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            "id": 26,
            "name": "URGI",
            "logo_url": "https://entrepot.recherche.data.gouv.fr/logos/14/logoURGI_res300_1-69X1-19.png",
            "description": "URGI (Unit Resources Genomics-Info) is a scientific facility specialised in plant bioinformatics. \r\nWe publish and integrate genetic, phenomic and genomic data, mainly from plants, and analyse the dynamics of transposable elements in genomes and pangenomes.\r\n\r\nURGI is ISO 9001:2015 certified and part of the “Institut Français de Bioinformatique” (IFB), the French node of ELIXIR, the European bioinformatics infrastructure for the life sciences. It is also one of the four facilities that form BioinfOmics, INRAE’s bioinformatics research infrastructure.",
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                "http://edamontology.org/topic_3571",
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                "http://edamontology.org/topic_0780",
                "http://edamontology.org/topic_0091"
            ],
            "expertise_description": "Services:\r\n1. Advices and resources for data management and integration, based on the FAIR principles\r\n2. Development of federated portals to facilitate access and exploitation of global data (e.g. FAIDARE, WheatIS Data Discovery, RARe Data Discovery)\r\n3. Advanced analysis of genomic data using specialised tools, such as REPET",
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            "homepage": "https://urgi.versailles.inrae.fr/",
            "unitId": "URGI-US1164",
            "address": "INRAE Centre de Versailles\r\nRD10 - Route de Saint-Cyr\r\n78000 Versailles\r\nFrance",
            "city": "Versailles",
            "country": "France",
            "communities": [],
            "projects": [
                "https://catalogue.france-bioinformatique.fr/api/project/ELIXIR-CONVERGE/?format=api"
            ],
            "affiliatedWith": [
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                    "name": "Elixir",
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                    "id": 7,
                    "name": "France Génomique",
                    "url": "https://catalogue.france-bioinformatique.fr/api/organisation/France%20G%C3%A9nomique/?format=api"
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                    "name": "University Paris-Saclay",
                    "url": "https://catalogue.france-bioinformatique.fr/api/organisation/University%20Paris-Saclay/?format=api"
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                {
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                    "name": "INRAE",
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                    "id": 88,
                    "name": "BioinfOmics",
                    "url": "https://catalogue.france-bioinformatique.fr/api/organisation/BioinfOmics/?format=api"
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            ],
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                "",
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                "10.1186/s13100-019-0150-y",
                "10.1007/978-1-4939-6658-5_5",
                "10.1093/database/bat058",
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                "10.1371/journal.pone.0091929",
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            ],
            "fields": [
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        {
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            "name": "AuBi",
            "logo_url": "https://mesocentre.uca.fr/medias/photo/logoaubi-2019minus_1553844844490-jpg",
            "description": "AuBi is the bioinformatics platform of Clermont Auvergne University for life sciences (fundamental biology, microbiology, agronomy, environment, health and epidemiology). AuBi relies on the UCA Mesocentre to promote access to IT facilities for data analysis, storage, bioinformatics training and web service hosting for research. Significant expertise has been developed to support scientific projects in the field of large-scale sequence analysis in genomics, transcriptomics (RNAseq, ChiPseq, etc.) and epigenomic variations (BSseq), metagenomics, metatranscriptomics, metabolomics, molecular dynamics and imaging.",
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            "expertise_description": "AuBi provides bioinformatics tools and resources based on HPC and Cloud infrastructures with focus on omics and imaging data storage and analysis.",
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            "address": "Plateforme AuBi\r\nMésocentre Clermont Auvergne\r\nUniversité Clermont Auvergne\r\n7, avenue Blaise Pascal\r\nTSA 60026",
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            "country": "France",
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                "DOI:10.1186/s40168-025-02062-5",
                "DOI:10.1016/j.compmedimag.2025.102546",
                "DOI:10.1186/s40168-024-02027-0",
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