ReviewProteomics2016
Advancing translational research with next-generation protein microarrays.
Review in Proteomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed, 28 citations in OpenAlex.
- Tapioca: a platform for predicting de novo protein-protein interactions in dynamic contexts.Nature methods · 2024Article
- Human antibody profiling technologies for autoimmune disease.Immunologic research · 2023Review
- QPCT regulation by CTCF leads to sunitinib resistance in renal cell carcinoma by promoting angiogenesis.International journal of oncology · 2021Article
- Tracking the Antibody Immunome in Sporadic Colorectal Cancer by Using Antigen Self-Assembled Protein Arrays.Cancers · 2021Article
- Autoantibodies in Early Detection of Breast Cancer.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020Article
- Cell-free protein synthesis andRSC advances · 2020Article
- Developments and Applications of Functional Protein Microarrays.Molecular & cellular proteomics : MCP · 2020Review
- DNA methylation-regulated QPCT promotes sunitinib resistance by increasing HRAS stability in renal cell carcinoma.Theranostics · 2019Article
- A high-throughput integrated microfluidics method enables tyrosine autophosphorylation discovery.Communications biology · 2019Article
- KILchip v1.0: A NovelFrontiers in immunology · 2018Article
- Identification of Antibody Targets for Tuberculosis Serology using High-Density Nucleic Acid Programmable Protein Arrays.Molecular & cellular proteomics : MCP · 2017Article
- AAgAtlas 1.0: a human autoantigen database.Nucleic acids research · 2017Article
- Multiplexed Nucleic Acid Programmable Protein Arrays.Theranostics · 2017Article
- Biosimilars in rheumatic diseases: structural and functional variability that may impact clinical and regulatory decisions.Clinical rheumatology · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
Protein microarrays are a high-throughput technology used increasingly in translational research, seeking to apply basic science findings to enhance human health. In addition to assessing protein levels, posttranslational modifications, and signaling pathways in patient samples, protein microarrays have aided in the identification of potential protein biomarkers of disease and infection. In this perspective, the different types of full-length protein microarrays that are used in translational research are reviewed. Specific studies employing these microarrays are presented to highlight their potential in finding solutions to real clinical problems. Finally, the criteria that should be considered when developing next-generation protein microarrays are provided.
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.