ArticleBioinformatics (Oxford, England)2016
FRED 2: an immunoinformatics framework for Python.
Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- AI-driven neoantigen identification: a comprehensive review from somatic variant calling to T cell recognition.Journal of translational medicine · 2026Review
- AI-powered mapping of tumor immunity for optimized mRNA vaccine engineering.Frontiers in oncology · 2026Review
- Benchmarking of T cell receptor-epitope predictors with ePytope-TCR.Cell genomics · 2025Article
- Computational methods and data resources for predicting tumor neoantigens.Briefings in bioinformatics · 2025Review
- Artificial intelligence and neoantigens: paving the path for precision cancer immunotherapy.Frontiers in immunology · 2024Review
- Germline-mediated immunoediting sculpts breast cancer subtypes and metastatic proclivity.bioRxiv : the preprint server for biology · 2023Article
- Tumor microenvironment: barrier or opportunity towards effective cancer therapy.Journal of biomedical science · 2022Review
- Artificial intelligence applied in neoantigen identification facilitates personalized cancer immunotherapy.Frontiers in oncology · 2022Review
- Joint epitope selection and spacer design for string-of-beads vaccines.Bioinformatics (Oxford, England) · 2020Article
- Main Strategies for the Identification of Neoantigens.Cancers · 2020Review
- Graph-theoretical formulation of the generalized epitope-based vaccine design problem.PLoS computational biology · 2020Article
- Identification of HCMV-derived T cell epitopes in seropositive individuals through viral deletion models.The Journal of experimental medicine · 2020Article
- pVACtools: A Computational Toolkit to Identify and Visualize Cancer Neoantigens.Cancer immunology research · 2020Article
- Review
- Multi-omics discovery of exome-derived neoantigens in hepatocellular carcinoma.Genome medicine · 2019Article
- Machine Learning for Cancer Immunotherapies Based on Epitope Recognition by T Cell Receptors.Frontiers in genetics · 2019Review
- Article
- The role of neoantigen in immune checkpoint blockade therapy.Experimental hematology & oncology · 2018Review
- MuPeXI: prediction of neo-epitopes from tumor sequencing data.Cancer immunology, immunotherapy : CII · 2017Article
- ImmunoNodes - graphical development of complex immunoinformatics workflows.BMC bioinformatics · 2017Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
unlabelledImmunoinformatics approaches are widely used in a variety of applications from basic immunological to applied biomedical research. Complex data integration is inevitable in immunological research and usually requires comprehensive pipelines including multiple tools and data sources. Non-standard input and output formats of immunoinformatics tools make the development of such applications difficult. Here we present FRED 2, an open-source immunoinformatics framework offering easy and unified access to methods for epitope prediction and other immunoinformatics applications. FRED 2 is implemented in Python and designed to be extendable and flexible to allow rapid prototyping of complex applications. AVAILABILITY AND IMPLEMENTATION: FRED 2 is available at http://fred-2.github.io CONTACT: schubert@informatik.uni-tuebingen.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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