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https://github.com/Biocomputing-Research-Group/IDIA", "biotoolsID": "idia", "biotoolsCURIE": "biotools:idia", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3646", "term": "Peptide database search" }, { "uri": "http://edamontology.org/operation_3767", "term": "Protein identification" }, { "uri": "http://edamontology.org/operation_3695", "term": "Filtering" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrum" }, "format": [ { "uri": "http://edamontology.org/format_3654", "term": "mzXML" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrum" }, "format": [ { "uri": "http://edamontology.org/format_3651", "term": "MGF" }, { "uri": "http://edamontology.org/format_3244", "term": "mzML" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Java" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1109/BIBM55620.2022.9994873", "pmid": "37034305", "pmcid": "PMC10077956", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "IDIA: An Integrative Signal Extractor for Data-Independent Acquisition Proteomics", "abstract": "In proteomics, data-independent acquisition (DIA)has been shown to provide less biased and more reproducible results than data-dependent acquisition. Recently, many researchers have developed a series of methods to identify peptides and proteins by using spectrum libraries for DIA data. However, spectrum libraries are not always available for novel organisms or microbial communities. To detect peptides and proteins without a spectrum library, we developed IDIA, a library-free method using DIA data to generate pseudo-spectra that can be searched using conventional sequence database searching software. IDIA integrates two isotopic trace detection strategies and employs B-spline and Gaussian filters to help extract high-quality pseudo-spectra from the complex DIA data. The experimental results on human and yeast data demonstrated that our approach remarkably produced more peptide and protein identifications than the two state-of-the-art library-free methods, i.e., DIA-Umpire and Group-DIA. IDIA is freely available under the GNU GPL license at https://github.com/Biocomputing-Research-Group/IDIA.", "date": "2022-01-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Li J." }, { "name": "Pan C." }, { "name": "Guo X." } ], "journal": "Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022" } } ], "credit": [ { "name": "Xuan Guo", "email": "xuan.guo@unt.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2023-09-25T20:53:22.903009Z", "lastUpdate": "2023-09-25T20:53:22.905395Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "PROTHON", "description": "A local order parameter-based method for efficient comparison of protein ensembles.", "homepage": "https://github.com/PlotkinLab/Prothon", "biotoolsID": "prothon", "biotoolsCURIE": "biotools:prothon", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2997", "term": "Protein comparison" }, { "uri": "http://edamontology.org/operation_2476", "term": "Molecular dynamics" }, { "uri": "http://edamontology.org/operation_3891", "term": "Essential dynamics" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3870", "term": "Trajectory data" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3872", "term": "Topology data" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0888", "term": "Structure similarity score" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0176", "term": "Molecular dynamics" }, { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" }, { "uri": "http://edamontology.org/topic_0078", "term": "Proteins" }, { "uri": "http://edamontology.org/topic_0593", "term": "NMR" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1021/acs.jcim.3c00145", "pmid": "37178169", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "PROTHON: A Local Order Parameter-Based Method for Efficient Comparison of Protein Ensembles", "abstract": "The comparison of protein conformational ensembles is of central importance in structural biology. However, there are few computational methods for ensemble comparison, and those that are readily available, such as ENCORE, utilize methods that are sufficiently computationally expensive to be prohibitive for large ensembles. Here, a new method is presented for efficient representation and comparison of protein conformational ensembles. The method is based on the representation of a protein ensemble as a vector of probability distribution functions (pdfs), with each pdf representing the distribution of a local structural property such as the number of contacts between Cβ atoms. Dissimilarity between two conformational ensembles is quantified by the Jensen-Shannon distance between the corresponding set of probability distribution functions. The method is validated for conformational ensembles generated by molecular dynamics simulations of ubiquitin, as well as experimentally derived conformational ensembles of a 130 amino acid truncated form of human tau protein. In the ubiquitin ensemble data set, the method was up to 88 times faster than the existing ENCORE software, while simultaneously utilizing 48 times fewer computing cores. We make the method available as a Python package, called PROTHON, and provide a GitHub page with the Python source code at https://github.com/PlotkinLab/Prothon.", "date": "2023-06-12T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Aina A." }, { "name": "Hsueh S.C.C." }, { "name": "Plotkin S.S." } ], "journal": "Journal of Chemical Information and Modeling" } } ], "credit": [ { "name": "Steven S. Plotkin", "email": "steve@phas.ubc.ca", "url": null, "orcidid": "https://orcid.org/0000-0001-8998-877X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2023-09-25T19:18:38.412908Z", "lastUpdate": "2023-09-25T19:18:38.415458Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "high" }, { "name": "NEREL-BIO", "description": "Biomedical corpus for nested named entity recognition.", "homepage": "https://github.com/nerel-ds/NEREL-BIO", "biotoolsID": "nerel_bio", "biotoolsCURIE": "biotools:nerel_bio", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3280", "term": "Named-entity and concept recognition" }, { "uri": "http://edamontology.org/operation_3778", "term": "Text annotation" }, { "uri": "http://edamontology.org/operation_3625", "term": "Relation extraction" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Ontology" ], "topic": [ { "uri": "http://edamontology.org/topic_0089", "term": "Ontology and terminology" }, { "uri": "http://edamontology.org/topic_0218", "term": "Natural language processing" }, { "uri": "http://edamontology.org/topic_3067", "term": "Anatomy" }, { "uri": "http://edamontology.org/topic_3452", "term": "Tomography" }, { "uri": "http://edamontology.org/topic_3053", "term": "Genetics" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/BIOINFORMATICS/BTAD161", "pmid": "37004189", "pmcid": "PMC10129873", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "NEREL-BIO: A dataset of biomedical abstracts annotated with nested named entities", "abstract": "Motivation: This article describes NEREL-BIO-an annotation scheme and corpus of PubMed abstracts in Russian and smaller number of abstracts in English. NEREL-BIO extends the general domain dataset NEREL by introducing domain-specific entity types. NEREL-BIO annotation scheme covers both general and biomedical domains making it suitable for domain transfer experiments. NEREL-BIO provides annotation for nested named entities as an extension of the scheme employed for NEREL. Nested named entities may cross entity boundaries to connect to shorter entities nested within longer entities, making them harder to detect. Results: NEREL-BIO contains annotations for 700+ Russian and 100+ English abstracts. All English PubMed annotations have corresponding Russian counterparts. Thus, NEREL-BIO comprises the following specific features: Annotation of nested named entities, it can be used as a benchmark for cross-domain (NEREL → NEREL-BIO) and cross-language (English → Russian) transfer. We experiment with both transformer-based sequence models and machine reading comprehension models and report their results.", "date": "2023-04-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Loukachevitch N." }, { "name": "Manandhar S." }, { "name": "Baral E." }, { "name": "Rozhkov I." }, { "name": "Braslavski P." }, { "name": "Ivanov V." }, { "name": "Batura T." }, { "name": "Tutubalina E." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Elena Tutubalina", "email": "tutubalinaev@gmail.com", "url": null, "orcidid": "https://orcid.org/0000-0001-7936-0284", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2023-09-25T18:51:15.713904Z", "lastUpdate": "2023-09-25T18:51:15.716490Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "mBONITA", "description": "Multi-omics boolean omics network invariant-time analysis.", "homepage": "https://github.com/Thakar-Lab/mBONITA", "biotoolsID": "mbonita", "biotoolsCURIE": "biotools:mbonita", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3928", "term": "Pathway analysis" }, { "uri": "http://edamontology.org/operation_3927", "term": "Network analysis" }, { "uri": "http://edamontology.org/operation_3501", "term": "Enrichment analysis" }, { "uri": "http://edamontology.org/operation_3436", "term": "Aggregation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/topic_3308", "term": "Transcriptomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "C", "Python" ], "license": "MIT", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1021/ACS.JPROTEOME.2C00730", "pmid": "37000949", "pmcid": "PMC10167691", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Executable Network Models of Integrated Multiomics Data", "abstract": "Multiomics profiling provides a holistic picture of a condition being examined and captures the complexity of signaling events, beginning from the original cause (environmental or genetic), to downstream functional changes at multiple molecular layers. Pathway enrichment analysis has been used with multiomics data sets to characterize signaling mechanisms. However, technical and biological variability between these layered data limit an integrative computational analyses. We present a Boolean network-based method, multiomics Boolean Omics Network Invariant-Time Analysis (mBONITA), to integrate omics data sets that quantify multiple molecular layers. mBONITA utilizes prior knowledge networks to perform topology-based pathway analysis. In addition, mBONITA identifies genes that are consistently modulated across molecular measurements by combining observed fold-changes and variance, with a measure of node (i.e., gene or protein) influence over signaling, and a measure of the strength of evidence for that gene across data sets. We used mBONITA to integrate multiomics data sets from RAMOS B cells treated with the immunosuppressant drug cyclosporine A under varying O2 tensions to identify pathways involved in hypoxia-mediated chemotaxis. We compare mBONITA’s performance with 6 other pathway analysis methods designed for multiomics data and show that mBONITA identifies a set of pathways with evidence of modulation across all omics layers. mBONITA is freely available at https://github.com/Thakar-Lab/mBONITA.", "date": "2023-05-05T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Palshikar M.G." }, { "name": "Min X." }, { "name": "Crystal A." }, { "name": "Meng J." }, { "name": "Hilchey S.P." }, { "name": "Zand M.S." }, { "name": "Thakar J." } ], "journal": "Journal of Proteome Research" } } ], "credit": [ { "name": "Juilee Thakar", "email": "Juilee_Thakar@URMC.rochester.edu", "url": null, "orcidid": "https://orcid.org/0000-0003-4479-4183", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2023-09-25T18:35:03.752451Z", "lastUpdate": "2023-09-25T18:35:03.755242Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "DeepSTABp", "description": "An AI based web tool to predict the melting temperature (Tm) of proteins based on their amino acid sequence and various growth conditions.", "homepage": "https://csb-deepstabp.bio.rptu.de", "biotoolsID": "deepstabp", "biotoolsCURIE": "biotools:deepstabp", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3096", "term": "Editing" }, { "uri": "http://edamontology.org/operation_0331", "term": "Variant effect prediction" }, { "uri": "http://edamontology.org/operation_3092", "term": "Protein feature detection" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2976", "term": "Protein sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" }, { "uri": "http://edamontology.org/format_1964", "term": "plain text format (unformatted)" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0897", "term": "Protein property" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_0130", "term": "Protein folding, stability and design" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/topic_0601", "term": "Protein modifications" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python", "JavaScript" ], "license": "MIT", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/CSBiology/deepStabP", "type": [ "Repository" ], "note": null }, { "url": "https://git.nfdi4plants.org/f_jung/deepstabp", "type": [ "Other" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.3390/IJMS24087444", "pmid": "37108605", "pmcid": "PMC10138888", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "DeepSTABp: A Deep Learning Approach for the Prediction of Thermal Protein Stability", "abstract": "Proteins are essential macromolecules that carry out a plethora of biological functions. The thermal stability of proteins is an important property that affects their function and determines their suitability for various applications. However, current experimental approaches, primarily thermal proteome profiling, are expensive, labor-intensive, and have limited proteome and species coverage. To close the gap between available experimental data and sequence information, a novel protein thermal stability predictor called DeepSTABp has been developed. DeepSTABp uses a transformer-based protein language model for sequence embedding and state-of-the-art feature extraction in combination with other deep learning techniques for end-to-end protein melting temperature prediction. DeepSTABp can predict the thermal stability of a wide range of proteins, making it a powerful and efficient tool for large-scale prediction. The model captures the structural and biological properties that impact protein stability, and it allows for the identification of the structural features that contribute to protein stability. DeepSTABp is available to the public via a user-friendly web interface, making it accessible to researchers in various fields.", "date": "2023-04-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Jung F." }, { "name": "Frey K." }, { "name": "Zimmer D." }, { "name": "Muhlhaus T." } ], "journal": "International Journal of Molecular Sciences" } } ], "credit": [ { "name": "Timo Mühlhaus", "email": "timo.muehlhaus@rptu.de", "url": null, "orcidid": "https://orcid.org/0000-0003-3925-6778", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2023-09-25T17:54:30.731190Z", "lastUpdate": "2023-09-25T17:54:30.733846Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "PXStools", "description": "R package of tools for conducting exposure-wide analysis and deriving polyexposure risk scores.", "homepage": "https://github.com/yixuanh/PXStools", "biotoolsID": "pxstools", "biotoolsCURIE": "biotools:pxstools", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3659", "term": "Regression analysis" }, { "uri": "http://edamontology.org/operation_3436", "term": "Aggregation" }, { "uri": "http://edamontology.org/operation_3435", "term": "Standardisation and normalisation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" }, { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" }, { "uri": "http://edamontology.org/topic_3517", "term": "GWAS study" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "R" ], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/IJE/DYAC216", "pmid": null, "pmcid": "PMC10114106", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Software Application Profile: PXStools—an R package of tools for conducting exposure-wide analysis and deriving polyexposure risk scores", "abstract": "Motivation: Investigating the aggregate burden of environmental factors on human traits and diseases requires consideration of the entire ‘exposome’. However, current studies primarily focus on a single exposure or a handful of exposures at a time, without considering how multiple exposures may be simultaneously associated with each other or with the phenotype. Polyexposure risk scores (PXS) have been shown to predict and stratify risk for disease beyond or complementary to genetic and clinical risk. PXStools provides an analytical package to standardize exposome-wide studies as well as derive and validate polyexposure risk scores. Implementation: PXStools is a package for the statistical R. General features: The package allows users to (i) conduct exposure-wide association studies; (ii) derive and validate polyexposure risk scores with and without accounting for exposure interactions, using new approaches in regression modelling (hierarchical lasso);(iii) compare goodness of fit between models with and without multiple exposures; and (iv) visualize results. A data frame with a unique identifier, phenotype and exposures is needed as the only input. Various customizations are allowed including data preprocessing (removing missing or unwanted responses), covariates adjustment, multiple hypothesis correction and model specification (linear, logistic, survival).", "date": "2023-04-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "He Y." }, { "name": "Patel C.J." } ], "journal": "International Journal of Epidemiology" } } ], "credit": [ { "name": "Chirag J Patel", "email": "chirag_patel@hms.harvard.edu", "url": null, "orcidid": "https://orcid.org/0000-0002-8756-8525", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2023-09-25T17:15:56.465153Z", "lastUpdate": "2023-09-25T17:15:56.467728Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "GRaNPA", "description": "R package for assessing the biological relevance of any TF-Gene GRNs using a machine learning framework to predict cell-type specific differential expression.", "homepage": "https://git.embl.de/grp-zaugg/GRaNPA", "biotoolsID": "granpa", "biotoolsCURIE": "biotools:granpa", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_1781", "term": "Gene regulatory network analysis" }, { "uri": "http://edamontology.org/operation_2437", "term": "Gene regulatory network prediction" }, { "uri": "http://edamontology.org/operation_3928", "term": "Pathway analysis" }, { "uri": "http://edamontology.org/operation_3891", "term": "Essential dynamics" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" }, { "uri": "http://edamontology.org/topic_0749", "term": "Transcription factors and regulatory sites" }, { "uri": "http://edamontology.org/topic_3295", "term": "Epigenetics" }, { "uri": "http://edamontology.org/topic_3170", "term": "RNA-Seq" }, { "uri": "http://edamontology.org/topic_0204", "term": "Gene regulation" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "R" ], "license": "Artistic-2.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://grp-zaugg.embl-community.io/GRaNPA", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.15252/MSB.202311627", "pmid": "37073532", "pmcid": "PMC10258561", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "GRaNIE and GRaNPA: inference and evaluation of enhancer-mediated gene regulatory networks", "abstract": "Enhancers play a vital role in gene regulation and are critical in mediating the impact of noncoding genetic variants associated with complex traits. Enhancer activity is a cell-type-specific process regulated by transcription factors (TFs), epigenetic mechanisms and genetic variants. Despite the strong mechanistic link between TFs and enhancers, we currently lack a framework for jointly analysing them in cell-type-specific gene regulatory networks (GRN). Equally important, we lack an unbiased way of assessing the biological significance of inferred GRNs since no complete ground truth exists. To address these gaps, we present GRaNIE (Gene Regulatory Network Inference including Enhancers) and GRaNPA (Gene Regulatory Network Performance Analysis). GRaNIE (https://git.embl.de/grp-zaugg/GR aNIE) builds enhancer-mediated GRNs based on covariation of chromatin accessibility and RNA-seq across samples (e.g. individuals), while GRaNPA (https://git.embl.de/grp-zaugg/GRaNPA) assesses the performance of GRNs for predicting cell-type-specific differential expression. We demonstrate their power by investigating gene regulatory mechanisms underlying the response of macrophages to infection, cancer and common genetic traits including autoimmune diseases. Finally, our methods identify the TF PURA as a putative regulator of pro-inflammatory macrophage polarisation.", "date": "2023-06-12T00:00:00Z", "citationCount": 3, "authors": [ { "name": "Kamal A." }, { "name": "Arnold C." }, { "name": "Claringbould A." }, { "name": "Moussa R." }, { "name": "Servaas N.H." }, { "name": "Kholmatov M." }, { "name": "Daga N." }, { "name": "Nogina D." }, { "name": "Mueller-Dott S." }, { "name": "Reyes-Palomares A." }, { "name": "Palla G." }, { "name": "Sigalova O." }, { "name": "Bunina D." }, { "name": "Pabst C." }, { "name": "Zaugg J.B." } ], "journal": "Molecular Systems Biology" } } ], "credit": [ { "name": "Judith B Zaugg", "email": "judith.zaugg@embl.de", "url": null, "orcidid": "https://orcid.org/0000-0001-8324-4040", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2023-09-25T17:04:35.235693Z", "lastUpdate": "2023-09-25T17:04:35.238281Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "high" }, { "name": "GRaNIE", "description": "R package for reconstruction cell type specific gene regulatory networks including enhancers using chromatin accessibility and RNA-seq data.", "homepage": "https://git.embl.de/grp-zaugg/GRaNIE", "biotoolsID": "granie", "biotoolsCURIE": "biotools:granie", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_1781", "term": "Gene regulatory network analysis" }, { "uri": "http://edamontology.org/operation_2437", "term": "Gene regulatory network prediction" }, { "uri": "http://edamontology.org/operation_0438", "term": "Transcriptional regulatory element prediction" }, { "uri": "http://edamontology.org/operation_3891", "term": "Essential dynamics" }, { "uri": "http://edamontology.org/operation_3695", "term": "Filtering" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" }, { "uri": "http://edamontology.org/topic_0749", "term": "Transcription factors and regulatory sites" }, { "uri": "http://edamontology.org/topic_3295", "term": "Epigenetics" }, { "uri": "http://edamontology.org/topic_3170", "term": "RNA-Seq" }, { "uri": "http://edamontology.org/topic_0204", "term": "Gene regulation" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "R" ], "license": "Artistic-2.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://bioconductor.org/packages/GRaNIE", "type": [ "Repository" ], "note": null }, { "url": "https://apps.embl.de/grn/", "type": [ "Other" ], "note": null } ], "download": [], "documentation": [ { "url": "https://grp-zaugg.embl-community.io/GRaNIE/", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.15252/MSB.202311627", "pmid": "37073532", "pmcid": "PMC10258561", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "GRaNIE and GRaNPA: inference and evaluation of enhancer-mediated gene regulatory networks", "abstract": "Enhancers play a vital role in gene regulation and are critical in mediating the impact of noncoding genetic variants associated with complex traits. Enhancer activity is a cell-type-specific process regulated by transcription factors (TFs), epigenetic mechanisms and genetic variants. Despite the strong mechanistic link between TFs and enhancers, we currently lack a framework for jointly analysing them in cell-type-specific gene regulatory networks (GRN). Equally important, we lack an unbiased way of assessing the biological significance of inferred GRNs since no complete ground truth exists. To address these gaps, we present GRaNIE (Gene Regulatory Network Inference including Enhancers) and GRaNPA (Gene Regulatory Network Performance Analysis). GRaNIE (https://git.embl.de/grp-zaugg/GR aNIE) builds enhancer-mediated GRNs based on covariation of chromatin accessibility and RNA-seq across samples (e.g. individuals), while GRaNPA (https://git.embl.de/grp-zaugg/GRaNPA) assesses the performance of GRNs for predicting cell-type-specific differential expression. We demonstrate their power by investigating gene regulatory mechanisms underlying the response of macrophages to infection, cancer and common genetic traits including autoimmune diseases. Finally, our methods identify the TF PURA as a putative regulator of pro-inflammatory macrophage polarisation.", "date": "2023-06-12T00:00:00Z", "citationCount": 3, "authors": [ { "name": "Kamal A." }, { "name": "Arnold C." }, { "name": "Claringbould A." }, { "name": "Moussa R." }, { "name": "Servaas N.H." }, { "name": "Kholmatov M." }, { "name": "Daga N." }, { "name": "Nogina D." }, { "name": "Mueller-Dott S." }, { "name": "Reyes-Palomares A." }, { "name": "Palla G." }, { "name": "Sigalova O." }, { "name": "Bunina D." }, { "name": "Pabst C." }, { "name": "Zaugg J.B." } ], "journal": "Molecular Systems Biology" } } ], "credit": [ { "name": "Judith B Zaugg", "email": "judith.zaugg@embl.de", "url": null, "orcidid": "https://orcid.org/0000-0001-8324-4040", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2023-09-25T16:56:32.452403Z", "lastUpdate": "2023-09-25T16:56:32.454867Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "high" }, { "name": "ANISEED", "description": "ANISEED is the main model organism database for the worldwide community of scientists working on tunicates (sister-group of vertebrates). It integrates for each species: \ni) a main knowledge base with extended functional, gene expression, phenotyping, anatomical and phylogenetic information; \nii) A multispecies genomic browser; \niii) a Genomicus gene synteny browser.", "homepage": "https://www.aniseed.fr", "biotoolsID": "ANISEED", "biotoolsCURIE": "biotools:ANISEED", "version": [ "2019" ], "otherID": [ { "value": "DOI:10.1093/nar/gkx1108", "type": "doi", "version": "2017" }, { "value": "DOI:10.1093/nar/gkv966", "type": "doi", "version": "2015" }, { "value": "DOI:10.1101/gr.108175.110", "type": "doi", "version": "2010" }, { "value": "DOI:10.1016/j.cub.2005.12.044", "type": "doi", "version": "2006" } ], "relation": [ { "biotoolsID": "interpro", "type": "uses" }, { "biotoolsID": "blast", "type": "uses" }, { "biotoolsID": "genomicus-tunicates", "type": "uses" }, { "biotoolsID": "ciona_robusta_anatomy_and_development_ontology", "type": "uses" }, { "biotoolsID": "ciona_robusta_anatomy_and_development_ontology", "type": 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sequence analysis" }, { "uri": "http://edamontology.org/operation_2495", "term": "Expression analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2042", "term": "Evidence" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2042", "term": "Evidence" }, "format": [ { "uri": "http://edamontology.org/format_2332", "term": "XML" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Ontology", "Web API", "Web application", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_2229", "term": "Cell biology" }, { "uri": "http://edamontology.org/topic_3064", "term": "Developmental biology" }, { "uri": "http://edamontology.org/topic_0084", "term": "Phylogeny" }, { "uri": "http://edamontology.org/topic_0089", "term": "Ontology and terminology" }, { "uri": "http://edamontology.org/topic_0219", "term": "Data submission, annotation and curation" }, { "uri": "http://edamontology.org/topic_3065", "term": "Embryology" }, { "uri": "http://edamontology.org/topic_3383", "term": "Biological imaging" }, { "uri": "http://edamontology.org/topic_3679", "term": "Animal study" }, { "uri": "http://edamontology.org/topic_0085", "term": "Functional genomics" }, { "uri": "http://edamontology.org/topic_3308", "term": "Transcriptomics" }, { "uri": "http://edamontology.org/topic_0194", "term": "Phylogenomics" } ], "operatingSystem": [ "Linux" ], "language": [ "PHP", "JavaScript", "Python" ], "license": "GPL-3.0", "collectionID": [ "elixir-fr-sdp-2019" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools", "Data", "Interoperability" ], "elixirNode": [ "France" ], "elixirCommunity": [], "link": [ { "url": "https://www.aniseed.fr", "type": [ "Service" ], "note": null }, { "url": "https://twitter.com/Aniseed_DB", "type": [ "Social media" ], "note": "Twitter for ANISEED" }, { "url": "https://www.facebook.com/TunicateCommunity", "type": [ "Social media" ], "note": "Facebook for ANISEED" }, { "url": "https://morphonet.org/", "type": [ "Service" ], "note": null } ], "download": [ { "url": "https://www.aniseed.fr/aniseed/download/download_data", "type": "Biological data", "note": null, "version": "2019" } ], "documentation": [ { "url": "https://www.aniseed.fr/api", "type": [ "API documentation" ], "note": null }, { "url": "https://www.aniseed.fr/aniseed/default/privacyPolicy", "type": [ "Contributions policy" ], "note": null }, { "url": "https://www.aniseed.fr/aniseed/default/termOfUse", "type": [ "Terms of use" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkx1108", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": "2017", "note": null, "metadata": { "title": "ANISEED 2017: Extending the integrated ascidian database to the exploration and evolutionary comparison of genome-scale datasets", "abstract": "ANISEED (www.aniseed.cnrs.fr) is the main model organism database for tunicates, the sister-group of vertebrates. This release gives access to annotated genomes, gene expression patterns, and anatomical descriptions for nine ascidian species. It provides increased integration with external molecular and taxonomy databases, better support for epigenomics datasets, in particular RNA-seq, ChIP-seq and SELEX-seq, and features novel interactive interfaces for existing and novel datatypes. In particular, the cross-species navigation and comparison is enhanced through a novel taxonomy section describing each represented species and through the implementation of interactive phylogenetic gene trees for 60% of tunicate genes. The gene expression section displays the results of RNA-seq experiments for the three major model species of solitary ascidians. Gene expression is controlled by the binding of transcription factors to cis-regulatory sequences. A high-resolution description of the DNA-binding specificity for 131 Ciona robusta (formerly C. intestinalis type A) transcription factors by SELEX-seq is provided and used to map candidate binding sites across the Ciona robusta and Phallusia mammillata genomes. Finally, use of a WashU Epigenome browser enhances genome navigation, while a Genomicus server was set up to explore microsynteny relationships within tunicates and with vertebrates, Amphioxus, echinoderms and hemichordates.", "date": "2018-01-01T00:00:00Z", "citationCount": 62, "authors": [ { "name": "Brozovic M." }, { "name": "Dantec C." }, { "name": "Dardaillon J." }, { "name": "Dauga D." }, { "name": "Faure E." }, { "name": "Gineste M." }, { "name": "Louis A." }, { "name": "Naville M." }, { "name": "Nitta K.R." }, { "name": "Piette J." }, { "name": "Reeves W." }, { "name": "Scornavacca C." }, { "name": "Simion P." }, { "name": "Vincentelli R." }, { "name": "Bellec M." }, { "name": "Aicha S.B." }, { "name": "Fagotto M." }, { "name": "Gueroult-Bellone M." }, { "name": "Haeussler M." }, { "name": "Jacox E." }, { "name": "Lowe E.K." }, { "name": "Mendez M." }, { "name": "Roberge A." }, { "name": "Stolfi A." }, { "name": "Yokomori R." }, { "name": "Brown C.T." }, { "name": "Cambillau C." }, { "name": "Christiaen L." }, { "name": "Delsuc F." }, { "name": "Douzery E." }, { "name": "Dumollard R." }, { "name": "Kusakabe T." }, { "name": "Nakai K." }, { "name": "Nishida H." }, { "name": "Satou Y." }, { "name": "Swalla B." }, { "name": "Veeman M." }, { "name": "Volff J.-N." }, { "name": "Lemaire P." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/nar/gkv966", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": "2015", "note": null, "metadata": { "title": "ANISEED 2015: A digital framework for the comparative developmental biology of ascidians", "abstract": "Ascidians belong to the tunicates, the sister group of vertebrates and are recognized model organisms in the field of embryonic development, regeneration and stem cells. ANISEED is the main information system in the field of ascidian developmental biology. This article reports the development of the system since its initial publication in 2010. Over the past five years, we refactored the system from an initial custom schema to an extended version of the Chado schema and redesigned all user and back end interfaces. This new architecture was used to improve and enrich the description of Ciona intestinalisembryonic development, based on an improved genome assembly and gene model set, refined functional gene annotation, and anatomical ontologies, and a new collection of full ORF cDNAs. The genomes of nine ascidian species have been sequenced since the release of the C. intestinalisgenome. In ANISEED 2015, all nine new ascidian species can be explored via dedicated genome browsers, and searched by Blast. In addition, ANISEED provides full functional gene annotation, anatomical ontologies and some gene expression data for the six species with highest quality genomes. ANISEED is publicly available at: http://www.aniseed.cnrs.fr.", "date": "2016-01-01T00:00:00Z", "citationCount": 53, "authors": [ { "name": "Brozovic M." }, { "name": "Martin C." }, { "name": "Dantec C." }, { "name": "Dauga D." }, { "name": "Mendez M." }, { "name": "Simion P." }, { "name": "Percher M." }, { "name": "Laporte B." }, { "name": "Scornavacca C." }, { "name": "Di Gregorio A." }, { "name": "Fujiwara S." }, { "name": "Gineste M." }, { "name": "Lowe E.K." }, { "name": "Piette J." }, { "name": "Racioppi C." }, { "name": "Ristoratore F." }, { "name": "Sasakura Y." }, { "name": "Takatori N." }, { "name": "Brown T.C." }, { "name": "Delsuc F." }, { "name": "Douzery E." }, { "name": "Gissi C." }, { "name": "McDougall A." }, { "name": "Nishida H." }, { "name": "Sawada H." }, { "name": "Swalla B.J." }, { "name": "Yasuo H." }, { "name": "Lemaire P." } ], "journal": "Nucleic Acids Research" } }, { "doi": "10.1101/gr.108175.110", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": "2010", "note": null, "metadata": { "title": "The ANISEED database: Digital representation, formalization, and elucidation of a chordate developmental program", "abstract": "Developmental biology aims to understand how the dynamics of embryonic shapes and organ functions are encoded in linear DNA molecules. Thanks to recent progress in genomics and imaging technologies, systemic approaches are now used in parallel with small-scale studies to establish links between genomic information and phenotypes, often described at the subcellular level. Current model organism databases, however, do not integrate heterogeneous data sets at different scales into a global view of the developmental program. Here, we present a novel, generic digital system, NISEED, and its implementation, ANISEED, to ascidians, which are invertebrate chordates suitable for developmental systems biology approaches. ANISEED hosts an unprecedented combination of anatomical and molecular data on ascidian development. This includes the first detailed anatomical ontologies for these embryos, and quantitative geometrical descriptions of developing cells obtained from reconstructed three-dimensional (3D) embryos up to the gastrula stages. Fully annotated gene model sets are linked to 30,000 high-resolution spatial gene expression patterns in wild-type and experimentally manipulated conditions and to 528 experimentally validated cis-regulatory regions imported from specialized databases or extracted from 160 literature articles. This highly structured data set can be explored via a Developmental Browser, a Genome Browser, and a 3D Virtual Embryo module. We show how integration of heterogeneous data in ANISEED can provide a system-level understanding of the developmental program through the automatic inference of gene regulatory interactions, the identification of inducing signals, and the discovery and explanation of novel asymmetric divisions. © 2010 by Cold Spring Harbor Laboratory Press.", "date": "2010-01-01T00:00:00Z", "citationCount": 90, "authors": [ { "name": "Tassy O." }, { "name": "Dauga D." }, { "name": "Daian F." }, { "name": "Sobral D." }, { "name": "Robin F." }, { "name": "Khoueiry P." }, { "name": "Salgado D." }, { "name": "Fox V." }, { "name": "Caillol D." }, { "name": "Schiappa R." }, { "name": "Laporte B." }, { "name": "Rios A." }, { "name": "Luxardi G." }, { "name": "Kusakabe T." }, { "name": "Joly J.-S." }, { "name": "Darras S." }, { "name": "Christiaen L." }, { "name": "Contensin M." }, { "name": "Auger H." }, { "name": "Lamy C." }, { "name": "Hudson C." }, { "name": "Rothbacher U." }, { "name": "Gilchrist M.J." }, { "name": "Makabe K.W." }, { "name": "Hotta K." }, { "name": "Fujiwara S." }, { "name": "Satoh N." }, { "name": "Satou Y." }, { "name": "Lemaire P." } ], "journal": "Genome Research" } }, { "doi": "10.1016/j.cub.2005.12.044", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": "2006", "note": null, "metadata": { "title": "A quantitative approach to the study of cell shapes and interactions during early chordate embryogenesis", "abstract": "Background: The prospects of deciphering the genetic program underlying embryonic development were recently boosted by the generation of large sets of precisely organized quantitative molecular data. In contrast, although the precise arrangement, interactions, and shapes of cells are crucial for the fulfilment of this program, their description remains coarse and qualitative. To bridge this gap, we developed a generic software, 3D Virtual Embryo, to quantify the geometry and interactions of cells in interactive three-dimensional embryo models. We applied this approach to early ascidian embryos, chosen because of their simplicity and their phylogenetic proximity to vertebrates. Results: We generated a collection of 19 interactive ascidian embryos between the 2- and 44-cell stages. We characterized the evolution with time, and in different cell lineages, of the volume of cells and of eight mathematical descriptors of their geometry, and we measured the surface of contact between neighboring blastomeres. These analyses first revealed that early embryonic blastomeres adopt a surprising variety of shapes, which appeared to be under strict and dynamic developmental control. Second, we found novel asymmetric cell divisions in the posterior vegetal lineages, which gave birth to sister cells with different fates. Third, during neural induction, differences in the area of contact between individual competent animal cells and inducing vegetal blastomeres appeared important to select the induced cells. Conclusions: In addition to novel insight into both cell-autonomous and inductive processes controlling early ascidian development, we establish a generic conceptual framework for the quantitative analysis of embryo geometry that can be applied to other model organisms. ©2006 Elsevier Ltd All rights reserved.", "date": "2006-02-21T00:00:00Z", "citationCount": 116, "authors": [ { "name": "Tassy O." }, { "name": "Daian F." }, { "name": "Hudson C." }, { "name": "Bertrand V." }, { "name": "Lemaire P." } ], "journal": "Current Biology" } }, { "doi": "10.1093/nar/gkz955", "pmid": null, "pmcid": null, "type": [], "version": "2019", "note": null, "metadata": { "title": "ANISEED 2019: 4D exploration of genetic data for an extended range of tunicates", "abstract": "ANISEED (https://www.aniseed.cnrs.fr) is the main model organism database for the worldwide community of scientists working on tunicates, the vertebrate sister-group. Information provided for each species includes functionally-annotated gene and transcript models with orthology relationships within tunicates, and with echinoderms, cephalochordates and vertebrates. Beyond genes the system describes other genetic elements, including repeated elements and cis-regulatory modules. Gene expression profiles for several thousand genes are formalized in both wild-type and experimentally-manipulated conditions, using formal anatomical ontologies. These data can be explored through three complementary types of browsers, each offering a different view-point. A developmental browser summarizes the information in a gene- or territory-centric manner. Advanced genomic browsers integrate the genetic features surrounding genes or gene sets within a species. A Genomicus synteny browser explores the conservation of local gene order across deuterostome. This new release covers an extended taxonomic range of 14 species, including for the first time a non-ascidian species, the appendicularian Oikopleura dioica. Functional annotations, provided for each species, were enhanced through a combination of manual curation of gene models and the development of an improved orthology detection pipeline. 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To support this big-data revolution, we develop a concept of generic web-based morphodynamic browser to interactively visualize complex image datasets, with applications in research and education. MorphoNet handles a broad range of natural or simulated morphological data, onto which quantitative geometric or genetic data can be projected.", "date": "2019-12-01T00:00:00Z", "citationCount": 26, "authors": [ { "name": "Leggio B." }, { "name": "Laussu J." }, { "name": "Carlier A." }, { "name": "Godin C." }, { "name": "Lemaire P." }, { "name": "Faure E." } ], "journal": "Nature Communications" } }, { "doi": "10.1093/nar/gkz955", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "ANISEED 2019: 4D exploration of genetic data for an extended range of tunicates", "abstract": "ANISEED (https://www.aniseed.cnrs.fr) is the main model organism database for the worldwide community of scientists working on tunicates, the vertebrate sister-group. Information provided for each species includes functionally-annotated gene and transcript models with orthology relationships within tunicates, and with echinoderms, cephalochordates and vertebrates. Beyond genes the system describes other genetic elements, including repeated elements and cis-regulatory modules. Gene expression profiles for several thousand genes are formalized in both wild-type and experimentally-manipulated conditions, using formal anatomical ontologies. These data can be explored through three complementary types of browsers, each offering a different view-point. A developmental browser summarizes the information in a gene- or territory-centric manner. Advanced genomic browsers integrate the genetic features surrounding genes or gene sets within a species. A Genomicus synteny browser explores the conservation of local gene order across deuterostome. 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