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This tool consists of two independent steps: one for denoising using one of the 5 integrated filters (Bilateral Filter, Anisotropic Diffusion Filter (ADF), Curvature Flow Filter (CFF), SUSAN and Non Local Means (NLM)), and another for the ANTs N4 and another for the ANT's N4 bias correction filter. 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HULAFE", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "casopon", "additionDate": "2025-05-29T08:55:46.088021Z", "lastUpdate": "2025-12-09T10:49:57.094252Z", "editPermission": { "type": "group", "authors": [ "pedromiguel_martinez_HULAFE" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Mapping-based Genome Size Estimation", "description": "Mapping-based Genome Size Estimation (MGSE) predicts the size of a genome based on a (short) read mapping to an existing genome assembly. Low complexity sequences are often collapsed in a genome assembly thus the assembly size is smaller than the genome size. 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The categorisation includes the type of sequence (e.g. spin echo, gradient echo), the weighting (e.g. T1W, T2W, DCE, ...), the presence of fat suppression and the detection of non-relevant / junk series (e.g. localizers, calibrations, screenshots...).", "homepage": "https://harbor.eucaim.cancerimage.eu/harbor/projects/4/repositories/ml_model_for_mr_series_categorisation/artifacts-tab", "biotoolsID": "ml_model_for_mr_series_categorisation", "biotoolsCURIE": "biotools:ml_model_for_mr_series_categorisation", "version": [ "1.1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2990", "term": "Classification" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3548", "term": "DICOM format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] } ], "note": null, "cmd": "docker run -it --rm --name my-container \\\n -v \"<input_path>:/input\" \\\n -v \"<output_path>:/output\" \\\n harbor.eucaim.cancerimage.eu/processing-tools/ml_model_for_mr_series_categorisation:<version> \\\n --config-string \"{'output_name': 'classification_results.json'}\"" } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3316", "term": "Computer science" }, { "uri": "http://edamontology.org/topic_3077", "term": "Data acquisition" }, { "uri": "http://edamontology.org/topic_3071", "term": "Data management" } ], "operatingSystem": [ "Windows", "Linux", "Mac" ], "language": [ "Python" ], "license": "CC-BY-NC-ND-4.0", "collectionID": [ "EUCAIM" ], "maturity": "Mature", "cost": "Free of charge (with restrictions)", "accessibility": "Open access (with restrictions)", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://harbor.eucaim.cancerimage.eu/harbor/projects/4/repositories/ml_model_for_mr_series_categorisation/artifacts-tab", "type": [ "Software catalogue" ], "note": null }, { "url": "https://www.linkedin.com/company/grupo-de-investigaci%C3%B3n-biom%C3%A9dica-en-imagen/", "type": [ "Social media" ], "note": null } ], "download": [], "documentation": [ { "url": "https://drive.google.com/file/d/1lIUixmLItQXOyBPIXL_AzPg_jlqDKwNE/view?usp=drive_link", "type": [ "User manual" ], "note": null }, { "url": "https://drive.google.com/file/d/1jF44iszmmiHd2paD8-YhFhW2uQJ0QBAZ/view?usp=drive_link", "type": [ "Terms of use" ], "note": null } ], "publication": [ { "doi": "10.1186/s40537-025-01086-w", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Automatic magnetic resonance imaging series labelling for large repositories", "abstract": "", "date": "2025-12-01T00:00:00Z", "citationCount": 0, "authors": [], "journal": "Journal of Big Data" } } ], "credit": [ { "name": "GIBI230 - HULAFE", "email": "gibi230@iislafe.es", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Armando Gomis-Maya", "email": "armago@alumni.uv.es", "url": null, "orcidid": "https://orcid.org/0000-0002-9527-8093", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Pedro-Miguel Martinez-Girones", "email": "pedromiguel_martinez@iislafe.es", "url": null, "orcidid": "https://orcid.org/0000-0002-9506-9451", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Support" ], "note": null }, { "name": "Carina Soler-Pons", "email": "carina_soler@iislafe.es", "url": null, "orcidid": "https://orcid.org/0009-0000-2991-1391", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Support" ], "note": null }, { "name": "Leonor Cerda-Alberich", "email": "leonor_cerda@iislafe.es", "url": null, "orcidid": "https://orcid.org/0000-0002-5567-4278", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null }, { "name": "Luis Marti-Bonmati", "email": "luis_marti@iislafe.es", "url": null, "orcidid": "https://orcid.org/0000-0002-8234-010X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null } ], "owner": "pedromiguel_martinez_HULAFE", "additionDate": "2025-11-25T09:58:37.569343Z", "lastUpdate": "2025-12-03T15:35:26.140884Z", "editPermission": { "type": "group", "authors": [ "casopon" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "AutoProSeq - automatic classification of sequence types for prostate mpMRI", "description": "XGBoost-based automatic classification of sequence types for prostate mpMRI into T2W, DWI, ADC, DCE and others (any other sequence type) using metadata alone. 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This command will print a CSV with 5 columns: i) patient_id, ii) study_uid, iii) series_uid, iv) classification from the XGBoost model, v) classification after heuristics-based corrections.\nThe sequence classification is performed between T2W, DWI, ADC, DCE or others. The provided <dicom-recursion> refers to the number of folders until a DICOM series is found. So if the provided input is a patient folder with nested studies with nested series, the level of DICOM recursion should be 2. If the provided input is a directory with patient folders, the level of DICOM recursion should be 3.", "cmd": "docker run -v <dir-with-dicom>:/data harbor.eucaim.cancerimage.eu/processing-tools/champ-autoproseq --dicom_recursion <dicom-recursion> --input_paths /data" } ], "toolType": [ "Web API", "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3063", "term": "Medical informatics" } ], "operatingSystem": [ "Linux" ], "language": [ "Python" ], "license": "MIT", "collectionID": [ "EUCAIM" ], "maturity": "Emerging", "cost": "Free of charge (with restrictions)", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/CCIG-Champalimaud/metadata-classification", "type": [ "Repository" ], "note": "Repository containing code, README and additional usage information for this tool." } ], "download": [], "documentation": [ { "url": "https://github.com/CCIG-Champalimaud/metadata-classification", "type": [ "Other" ], "note": "Repository containing the code, README and additional information on how to run the tool. If used as an API (when integrated with Orthanc or DICOM-web), the documentation is available upon launching the API at <api-url>/docs." } ], "publication": [ { "doi": "10.1186/s13244-025-01938-2", "pmid": "40146375", "pmcid": "PMC12187622", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Automatic sequence identification in multicentric prostate multiparametric MRI datasets for clinical machine-learning", "abstract": "", "date": "2025-12-01T00:00:00Z", "citationCount": 1, "authors": [], "journal": "Insights into Imaging" } } ], "credit": [ { "name": "José Guilherme de Almeida", "email": "jose.almeida@research.fchampalimaud.org", "url": "https://josegcpa.net", "orcidid": "https://orcid.org/0000-0002-1887-0157", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Maintainer" ], "note": null }, { "name": "Nikolaos Papanikolaou", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-3298-2072", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Contributor" ], "note": null } ], "owner": "josegcpa", "additionDate": "2025-12-02T17:37:57.215347Z", "lastUpdate": "2025-12-03T09:27:04.489071Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "AggreProt", "description": "AggreProt is a web server to predict and engineer protein aggregation. The tool provides a per-residue numerical aggregation propensity value and an overall protein aggregation propensity profile. Along with the protein solvent accessibility area and its transmembrane propensity, AggreProt predictions aid the users on designing soluble proteins.", "homepage": "https://loschmidt.chemi.muni.cz/aggreprot/", "biotoolsID": "aggreprot", "biotoolsCURIE": "biotools:aggreprot", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [], "toolType": [ "Web service" ], "topic": [ { "uri": "http://edamontology.org/topic_3510", "term": "Protein sites, features and motifs" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Java", "JavaScript" ], "license": "Proprietary", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [ "Tools" ], "elixirNode": [ "Czech Republic" ], "elixirCommunity": [ "Proteomics" ], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/nar/gkae420", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "AggreProt: A web server for predicting and engineering aggregation prone regions in proteins", "abstract": "", "date": "2024-07-05T00:00:00Z", "citationCount": 17, "authors": [], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "Joan Planas-Iglesias", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "David Bednar", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Jiri Damborsky", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Simeon Borko", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "m.musil", "additionDate": "2025-12-02T12:03:53.282983Z", "lastUpdate": "2025-12-02T12:03:53.285771Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "APE", "description": "APE (the Automated Pipeline Explorer) as a command-line tool and API for automated composition of scientific workflows. APE is easily configured to a new application domain by providing it with a domain ontology and semantically annotated tools. It can then be used to synthesize purpose-specific workflows based on a specification of the available workflow inputs, desired outputs and possibly additional constraints.", "homepage": "https://github.com/sanctuuary/APE/", "biotoolsID": "ape", "biotoolsCURIE": "biotools:ape", "version": [ "2.1.7" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3429", "term": "Generation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0949", "term": "Workflow metadata" }, "format": [ { "uri": "http://edamontology.org/format_3464", "term": "JSON" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0949", "term": "Workflow metadata" }, "format": [ { "uri": "http://edamontology.org/format_3604", "term": "SVG" }, { "uri": "http://edamontology.org/format_3857", "term": "CWL" }, { "uri": "http://edamontology.org/format_3603", "term": "PNG" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Library", "Web API", "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0769", "term": "Workflows" }, { "uri": "http://edamontology.org/topic_0089", "term": "Ontology and terminology" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [ "Mac", "Windows", "Linux" ], "language": [ "Java" ], "license": "Apache-2.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/sanctuuary/ape", "type": [ "Repository" ], "note": null } ], "download": [ { "url": "https://mvnrepository.com/artifact/io.github.sanctuuary/APE/2.1.7", "type": "Software package", "note": "Download APE java library or the CLI", "version": "2.1.7" } ], "documentation": [ { "url": "https://ape-framework.readthedocs.io/", "type": [ "API documentation" ], "note": null } ], "publication": [ { "doi": null, "pmid": null, "pmcid": "PMC7304703", "type": [ "Primary" ], "version": null, "note": null, "metadata": null }, { "doi": "10.1021/acs.jproteome.0c00983", "pmid": "33720735", "pmcid": "PMC8041394", "type": [ "Benchmarking study" ], "version": null, "note": null, "metadata": { "title": "APE in the Wild: Automated Exploration of Proteomics Workflows in the bio.tools Registry", "abstract": "", "date": "2021-04-02T00:00:00Z", "citationCount": 7, "authors": [], "journal": "Journal of Proteome Research" } } ], "credit": [ { "name": "Vedran Kasalica", "email": "vedran.kasalica@health-ri.nl", "url": null, "orcidid": "https://orcid.org/0000-0002-0097-1056", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Anna-Lena Lamprecht", "email": "anna-lena.lamprecht@uni-potsdam.de", "url": null, "orcidid": "https://orcid.org/0000-0003-1953-5606", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "VKasalica", "additionDate": "2021-01-18T10:10:48Z", "lastUpdate": "2025-12-01T13:47:56.062392Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "HBAT", "description": "HBAT (Hydrogen Bond Analysis Tool) is a package to automate the analysis of potential hydrogen bonds and similar type of weak interactions in macromolecular structures, available in Protein Data Bank (PDB) file format. HBAT uses a geometric approach to identify molecular interactions by analysing distance and angular criteria.\n\nHBAT 1.1 was released in 2007 as closed source Windows binary and continue to be available via SourceForge. \n\nHBAT 2.0 was introduced in 2025 and a completed rewrite of original implementation with cross-platform support. HBAT 2.0 is open sourced under MIT License.", "homepage": "https://hbat.abhishek-tiwari.com", "biotoolsID": "hbat", "biotoolsCURIE": "biotools:hbat", "version": [ "2.x", "1.1, 1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2406", "term": "Protein structure analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1549", "term": "Protein hydrogen bonds" }, "format": [] } ], "note": null, "cmd": "hbat input.pdb" } ], "toolType": [ "Command-line tool", "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_2814", "term": "Protein structure analysis" }, { "uri": "http://edamontology.org/topic_0078", "term": "Proteins" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Perl", "Python" ], "license": "MIT", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/abhishektiwari/hbat", "type": [ "Repository", "Issue tracker" ], "note": null }, { "url": "http://www.mybiosoftware.com/hbat-1-1-hydrogen-bond-analysis-tool.html", "type": [ "Software catalogue" ], "note": null } ], "download": [ { "url": "https://pypi.org/project/hbat/", "type": "Software package", "note": "Cross-platform PyPI Python Package", "version": "2.x" }, { "url": "https://github.com/abhishektiwari/hbat/releases", "type": "Binaries", "note": "Mac and Linux Binaries including AppImage, .deb, standalone executables.", "version": "2.x" }, { "url": "https://sourceforge.net/projects/hbat/", "type": "Binaries", "note": "Windows Binaries download from SourceForge", "version": "1.0, 1.1" } ], "documentation": [ { "url": "https://hbat.abhishek-tiwari.com", "type": [ "General", "API documentation", "Citation instructions", "Command-line options", "Installation instructions", "Quick start guide" ], "note": null } ], "publication": [ { "doi": "10.3233/ISI-2007-00337", "pmid": "18467777", "pmcid": null, "type": [ "Primary" ], "version": null, "note": "Peer-reviewed paper for HBAT 1.0", "metadata": null }, { "doi": "10.5281/zenodo.17645321", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": "Preprint for HBAT 2.x software", "metadata": null } ], "credit": [ { "name": "Abhishek Tiwari", "email": null, "url": "https://www.abhishek-tiwari.com", "orcidid": "https://orcid.org/0000-0003-2222-2395", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "abhishektiwari", "additionDate": "2017-08-03T18:45:53Z", "lastUpdate": "2025-11-29T17:30:01.186940Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Prostate zone segmentation tool", "description": "This tool automatically segments the the prostate into two zones: the central and transition zones (TZ+CZ) and the peripheral zone (PZ). It takes as input a T2-weighted image and produces a segmentation in the same input format.\n\nThree datasets were used to train this model: ProstateX (n=152), Prostate158 (n=119) and ProstateNet (the ProCAncer-I dataset; n=532). We used the T2-weighted images available in each dataset and trained a standard three-class nnU-Net model with three classes: background, peripheral zone and the combination of the transition and central zones as annotated by radiologists. Using 149 cases from the three previously noted datasets, this model achieved DSC=0.81 (95% CI=[0.59, 0.92]) for PZ and 0.87 (95% CI=[0.60, 0.96]) for CZ+TZ. In a clinical validation using ProCAncer-I data, this model achieved, for PZ and TZ+CZ, DSC=0.65 and DSC=0.77, respectively, comparable to the observed between-radiologist DSC for a subset of cases (DSC=0.61 and DSC=0.73, respectively).", "homepage": "https://harbor.eucaim.cancerimage.eu/harbor/projects/4/repositories/champ-prostate-zone-segmentation", "biotoolsID": "prostate_zone_segmentation_tool", "biotoolsCURIE": "biotools:prostate_zone_segmentation_tool", "version": [], "otherID": [], "relation": [ { "biotoolsID": "nnunet", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3553", "term": "Image annotation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3442", "term": "MRI image" }, "format": [ { "uri": "http://edamontology.org/format_3549", "term": "nii" }, { "uri": "http://edamontology.org/format_3548", "term": "DICOM format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3549", "term": "nii" }, { "uri": "http://edamontology.org/format_3548", "term": "DICOM format" } ] } ], "note": "Image annotation for individual DICOM and Nifti images: Please note that it is easier to mount the input and output paths path and keep `--study_path` always as `/data/input` and `--output_dir` always as `/data/output`. This way only `--series_folders` requires any change. `--series_folders` can refer both to a Nifti file (if the input is Nifti) or the a DICOM series folder.\n\nIf the input is DICOM, `--is_dicom` should be used.", "cmd": "docker run --shm-size=1gb -v $(pwd)/example:/data/input:ro -v $(pwd)/test_output:/data/output:rw --gpus=\"all\" test-eucaim:latest nnunet-predict --study_path /data/input --series_folders <series-folder> --output_dir /data/output" }, { "operation": [ { "uri": "http://edamontology.org/operation_3553", "term": "Image annotation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3442", "term": "MRI image" }, "format": [ { "uri": "http://edamontology.org/format_3549", "term": "nii" }, { "uri": "http://edamontology.org/format_3548", "term": "DICOM format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_3442", "term": "MRI image" }, "format": [ { "uri": "http://edamontology.org/format_3549", "term": "nii" }, { "uri": "http://edamontology.org/format_3548", "term": "DICOM format" } ] } ], "note": "Batch image annotation for DICOM and Nifti images using dataset JSON and data directory supports two methods: using a dataset JSON and using a data directory. \n\nThe dataset JSON-based method relies on having a dataset JSON which has a list of dictionaries that follow this structure: `{\"study_path\": str, \"series_folders\": [[str]], \"output_dir\": str}`. These are analogous to the previous modes. Be mindful that paths should be specified accordingly for the Docker file-system. The dataset JSON should be specified using `--data_json`.\n\nThe data directory-based method relies on having a directory structured as patient/study/series, where each series follows an nnU-Net-like convention (i.e. `<series_id>_0000`, `<series_id>_0001`, etc.). In this case, it should be `<series-id>_0000`. The data directory should be specified using `--data_dir` and requires the specification of an `--output_dir`.\n\nIf the input is DICOM, `--is_dicom` should be specified.", "cmd": "docker run --shm-size=1gb -v $(pwd)/example_dataset:/data/input:ro -v $(pwd)/test_output:/data/output:rw --gpus=\"all\" test-eucaim:latest nnunet-predict-batch {{--data_json /data/input/<dataset_json>.json|--data_dir /data/input --output_dir /data/output}}" } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3063", "term": "Medical informatics" } ], "operatingSystem": [ "Linux" ], "language": [ "Python" ], "license": "CC-BY-NC-4.0", "collectionID": [ "EUCAIM" ], "maturity": "Emerging", "cost": "Free of charge (with restrictions)", "accessibility": "Open access (with restrictions)", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/josegcpa/nnunet_serve", "type": [ "Repository" ], "note": "This is the nnunet_serve repository, containing the generic nnU-Net building and serving functionalities used by the Computational Clinical Imaging Group at Champalimaud Foundation. This should also be used as documentation." }, { "url": "https://docs.google.com/spreadsheets/d/1bcdhs9Xg2MxAH0WDGz08SjEVMFr3e-TP/edit?usp=sharing&ouid=111102743696297094705&rtpof=true&sd=true", "type": [ "Other" ], "note": "The EUCAIM model card for this model, containing details on model training, data and libraries." } ], "download": [], "documentation": [ { "url": "https://github.com/josegcpa/nnunet_serve", "type": [ "API documentation" ], "note": "This is the repository containing all of the code together with a comprehensive README for deployment and examplar files." } ], "publication": [ { "doi": "10.1016/j.compbiomed.2024.108216", "pmid": "38442555", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Analysis of domain shift in whole prostate gland, zonal and lesions segmentation and detection, using multicentric retrospective data", "abstract": "", "date": "2024-03-01T00:00:00Z", "citationCount": 9, "authors": [], "journal": "Computers in Biology and Medicine" } } ], "credit": [ { "name": "José Guilherme de Almeida", "email": "jose.almeida@research.fchampalimaud.org", "url": "https://josegcpa.net", "orcidid": "https://orcid.org/0000-0002-1887-0157", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Developer", "Documentor", "Maintainer" ], "note": null }, { "name": "Nickolas Papanikolaou", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-3298-2072", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Support" ], "note": null }, { "name": "Nuno Rodrigues", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null } ], "owner": "josegcpa", "additionDate": "2025-11-07T18:15:49.962044Z", "lastUpdate": "2025-11-28T12:18:55.232382Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "South Green Genome Hubs", "description": "The South Green Genome Hub is a suite of crop-specific community portals to manage genomic datasets with focus on tropical and Mediterranean plants. Currently developed on Banana, Cacao, Coffee, Grass, Rice, Vanilla, Citrus and Sugarcane, genome hubs provide access to multiple datasets (e.g. assemblies, gene product information, metabolic pathways, gene families, transcriptomics and genetic markers).", "homepage": "https://banana-genome-hub.southgreen.fr/", "biotoolsID": "South_Green_Genome_Hubs", "biotoolsCURIE": "biotools:South_Green_Genome_Hubs", "version": [], "otherID": [], "relation": [ { "biotoolsID": "tripal", "type": "uses" }, { "biotoolsID": "banana_genome_hub", "type": "includes" }, { "biotoolsID": "coffee_genome_hub", "type": "includes" }, { "biotoolsID": "cocoa_genome_hub", "type": "includes" }, { "biotoolsID": "rice_genome_hub", "type": "includes" }, { "biotoolsID": "sugarcane_genome_hub", "type": "includes" }, { "biotoolsID": "southgreen", "type": "includedIn" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3208", "term": "Genome visualisation" }, { "uri": "http://edamontology.org/operation_0338", "term": "Sequence database search" }, { "uri": "http://edamontology.org/operation_2403", "term": "Sequence analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0968", "term": "Keyword" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2044", "term": "Sequence" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_3810", "term": "Agricultural science" }, { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" }, { "uri": "http://edamontology.org/topic_3308", "term": "Transcriptomics" }, { "uri": "http://edamontology.org/topic_0797", "term": "Comparative genomics" }, { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" } ], "operatingSystem": [], "language": [ "JavaScript", "PHP" ], "license": "GPL-2.0", 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"date": "2015-01-28T00:00:00Z", "citationCount": 52, "authors": [], "journal": "Nucleic Acids Research" } }, { "doi": "10.1093/hr/uhac221", "pmid": "36479579", "pmcid": "PMC9720444", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The banana genome hub: a community database for genomics in the Musaceae", "abstract": "", "date": "2022-01-01T00:00:00Z", "citationCount": 29, "authors": [], "journal": "Horticulture Research" } }, { "doi": "10.1016/j.xplc.2022.100330", "pmid": "35617961", "pmcid": "PMC9482989", "type": [ "Usage" ], "version": null, "note": null, "metadata": { "title": "A chromosome-level, haplotype-phased Vanilla planifolia genome highlights the challenge of partial endoreplication for accurate whole-genome assembly", "abstract": "", "date": "2022-09-12T00:00:00Z", "citationCount": 26, "authors": [], "journal": "Plant Communications" } } ], "credit": [ { "name": "Gaetan Droc", "email": "droc@cirad.fr", "url": null, "orcidid": 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"uri": "http://edamontology.org/topic_0749", "term": "Transcription factors and regulatory sites" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "R" ], "license": "Unlicense", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/Shoombuatong2527/acpred", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/chaninlab/acpred-webserver", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.3390/MOLECULES24101973", "pmid": "31121946", "pmcid": "PMC6571645", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "ACPred: A computational tool for the prediction and analysis of anticancer peptides", "abstract": "© 2019 MDPI AG. All rights reserved.Anticancer peptides (ACPs) have emerged as a new class of therapeutic agent for cancer treatment due to their lower toxicity as well as greater efficacy, selectivity and specificity when compared to conventional small molecule drugs. However, the experimental identification of ACPs still remains a time-consuming and expensive endeavor. Therefore, it is desirable to develop and improve upon existing computational models for predicting and characterizing ACPs. In this study, we present a bioinformatics tool called the ACPred, which is an interpretable tool for the prediction and characterization of the anticancer activities of peptides. ACPred was developed by utilizing powerful machine learning models (support vector machine and random forest) and various classes of peptide features. It was observed by a jackknife cross-validation test that ACPred can achieve an overall accuracy of 95.61% in identifying ACPs. In addition, analysis revealed the following distinguishing characteristics that ACPs possess: (i) hydrophobic residue enhances the cationic properties of α-helical ACPs resulting in better cell penetration; (ii) the amphipathic nature of the α-helical structure plays a crucial role in its mechanism of cytotoxicity; and (iii) the formation of disulfide bridges on β-sheets is vital for structural maintenance which correlates with its ability to kill cancer cells. Finally, for the convenience of experimental scientists, the ACPred web server was established and made freely available online.", "date": "2019-01-01T00:00:00Z", "citationCount": 42, "authors": [ { "name": "Schaduangrat N." }, { "name": "Nantasenamat C." }, { "name": "Prachayasittikul V." }, { "name": "Shoombuatong W." } ], "journal": "Molecules" } } ], "credit": [ { "name": "Watshara Shoombuatong", "email": "watshara.sho@mahidol.ac.th", "url": null, "orcidid": "https://orcid.org/0000-0002-3394-8709", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "hans", "additionDate": "2019-08-09T13:07:09Z", "lastUpdate": "2025-11-17T12:41:12.905009Z", "editPermission": { "type": "group", "authors": [ "ningning" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "protein-quest", "description": "Python package to search/retrieve/filter proteins and protein structures.", "homepage": "http://www.bonvinlab.org/protein-quest/", "biotoolsID": "protein-quest", "biotoolsCURIE": "biotools:protein-quest", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" } ], "operatingSystem": [ "Windows", "Linux", "Mac" ], "language": [ "Python" ], "license": "Apache-2.0", "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/haddocking/protein-quest", "type": [ "Repository" ], "note": null }, { "url": "https://github.com/haddocking/protein-quest/issues", "type": [ "Issue tracker" ], "note": null } ], "download": [ { "url": "https://pypi.org/project/protein-quest", "type": "Software package", "note": null, "version": null } ], "documentation": [ { "url": "http://www.bonvinlab.org/protein-quest/", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.5281/zenodo.16941288", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": null } ], "credit": [], "owner": "sverhoeven", "additionDate": "2025-11-17T10:03:13.644804Z", "lastUpdate": "2025-11-17T10:05:01.348125Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MetFamily", "description": "Web application designed for the identification of regulated metabolite families. This is possible on the basis of metabolite profiles for a set of MS¹ features as well as one MS/MS spectrum for each MS¹ feature. Group-discriminating MS¹ features are identified using a PCA of metabolite profiles and metabolite families are identified using a HCA of MS/MS spectra. 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