ReviewFrontiers in genetics2019
Machine Learning for Cancer Immunotherapies Based on Epitope Recognition by T Cell Receptors.
Review in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed, 43 citations in OpenAlex.
- Mitigating negative data bias to enhance TCR-epitope binding and residue interaction prediction.Briefings in bioinformatics · 2026Article
- Review
- Algorithm guided personalized T cell therapy: machine learning unlocks next generation TCR engineered immunotherapy.Pharmacological reports : PR · 2026Review
- The Art of Bioimmunogenomics (BIGs) 5.0 in CAR-T Cell Therapy for Lymphoma Management.Advanced pharmaceutical bulletin · 2024Review
- HeteroTCR: A heterogeneous graph neural network-based method for predicting peptide-TCR interaction.Communications biology · 2024Article
- NeoAgDT: optimization of personal neoantigen vaccine composition by digital twin simulation of a cancer cell population.Bioinformatics (Oxford, England) · 2024Article
- Neoantigen-targeted TCR-engineered T cell immunotherapy: current advances and challenges.Biomarker research · 2023Review
- Interpretable unsupervised learning enables accurate clustering with high-throughput imaging flow cytometry.Scientific reports · 2023Article
- Can we predict T cell specificity with digital biology and machine learning?Nature reviews. Immunology · 2023Review
- Antigen-specific and cross-reactive T cells in protection and disease.Immunological reviews · 2023Review
- Elaborating the potential of Artificial Intelligence in automated CAR-T cell manufacturing.Frontiers in molecular medicine · 2023Article
- DECODE: a computational pipeline to discover T cell receptor binding rules.Bioinformatics (Oxford, England) · 2022Article
- Viral immunogenic footprints conferring T cell cross-protection to SARS-CoV-2 and its variants.Frontiers in immunology · 2022Article
- Artificial intelligence applied in neoantigen identification facilitates personalized cancer immunotherapy.Frontiers in oncology · 2022Review
- Structural Prediction of Peptide-MHC Binding Modes.Methods in molecular biology (Clifton, N.J.) · 2022Review
- ATM-TCR: TCR-Epitope Binding Affinity Prediction Using a Multi-Head Self-Attention Model.Frontiers in immunology · 2022Article
- Machine Learning Approaches to TCR Repertoire Analysis.Frontiers in immunology · 2022Review
- Mechanistic diversity in MHC class I antigen recognition.The Biochemical journal · 2021Review
- Applying artificial intelligence for cancer immunotherapy.Acta pharmaceutica Sinica. B · 2021Review
- Targeting neoantigens for cancer immunotherapy.Biomarker research · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the last years, immunotherapies have shown tremendous success as treatments for multiple types of cancer. However, there are still many obstacles to overcome in order to increase response rates and identify effective therapies for every individual patient. Since there are many possibilities to boost a patient's immune response against a tumor and not all can be covered, this review is focused on T cell receptor-mediated therapies. CD8
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.