ArticleNucleic acids research2020
BIOMEX: an interactive workflow for (single cell) omics data interpretation and visualization.
Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.
What it found
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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.
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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.
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Who cites it
44 citing papers in PubMed.
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- Identification of NOTCH2 as a prognostic marker for cholangiocarcinoma.Discover oncology · 2025Article
- In vitro models to mimic tumor endothelial cell-mediated immune cell reprogramming in lung adenocarcinoma.Journal of experimental & clinical cancer research : CR · 2025Article
- AP-1 Is an Initial Convergent Transcriptional Response in Lymphatic Endothelium to VEGF-C or TNFα.Microcirculation (New York, N.Y. : 1994) · 2025Article
- Single cell transcriptomics of human kidney organoid endothelium reveals vessel growth processes and arterial maturation upon transplantation.NPJ Regenerative medicine · 2025Article
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- The pentose phosphate pathway controls oxidative protein folding and prevents ferroptosis in chondrocytes.Nature metabolism · 2025Article
- Molecular Landscape of Bladder Cancer: Key Genes, Transcription Factors, and Drug Interactions.International journal of molecular sciences · 2024Article
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- Integrative proteomic and metabolomic elucidation of cardiomyopathy with in vivo and in vitro models and clinical samples.Molecular therapy : the journal of the American Society of Gene Therapy · 2024Review
- Coactivator-independent vitamin D receptor signaling causes severe rickets in mice, that is not prevented by a diet high in calcium, phosphate, and lactose.Bone research · 2024Article
- Unveiling the Mechanisms Underlying the Immunotherapeutic Potential of Gene-miRNA and Drugs in Head and Neck Cancer.Pharmaceuticals (Basel, Switzerland) · 2024Article
- Site-specific regulation of Th2 differentiation within lymph node microenvironments.The Journal of experimental medicine · 2024Article
- Genomic data integration tutorial, a plant case study.BMC genomics · 2024Article
- Interplay between oncolytic measles virus, macrophages and cancer cells induces a proinflammatory tumor microenvironment.Oncoimmunology · 2024Article
- Hematopoietic stem cells undergo a lymphoid to myeloid switch in early stages of emergency granulopoiesis.The EMBO journal · 2023Article
- Ursa: A Comprehensive Multiomics Toolbox for High-Throughput Single-Cell Analysis.Molecular biology and evolution · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The amount of biological data, generated with (single cell) omics technologies, is rapidly increasing, thereby exacerbating bottlenecks in the data analysis and interpretation of omics experiments. Data mining platforms that facilitate non-bioinformatician experimental scientists to analyze a wide range of experimental designs and data types can alleviate such bottlenecks, aiding in the exploration of (newly generated or publicly available) omics datasets. Here, we present BIOMEX, a browser-based software, designed to facilitate the Biological Interpretation Of Multi-omics EXperiments by bench scientists. BIOMEX integrates state-of-the-art statistical tools and field-tested algorithms into a flexible but well-defined workflow that accommodates metabolomics, transcriptomics, proteomics, mass cytometry and single cell data from different platforms and organisms. The BIOMEX workflow is accompanied by a manual and video tutorials that provide the necessary background to navigate the interface and get acquainted with the employed methods. BIOMEX guides the user through omics-tailored analyses, such as data pretreatment and normalization, dimensionality reduction, differential and enrichment analysis, pathway mapping, clustering, marker analysis, trajectory inference, meta-analysis and others. BIOMEX is fully interactive, allowing users to easily change parameters and generate customized plots exportable as high-quality publication-ready figures. BIOMEX is open source and freely available at https://www.vibcancer.be/software-tools/biomex.
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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.