ReviewFrontiers in molecular biosciences2018
Mass Spectrometry-Based Proteomics to Unveil the Non-coding RNA World.
Review in Frontiers in molecular biosciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed, 19 citations in OpenAlex.
- Identification and expression profiling of microRNAs in leaf tissues ofPlant signaling & behavior · 2024Article
- The Emerging Role of Non-Coding RNAs (ncRNAs) in Plant Growth, Development, and Stress Response Signaling.Non-coding RNA · 2024Review
- Unveiling the role of PUS7-mediated pseudouridylation in host protein interactions specific for the SARS-CoV-2 RNA genome.Molecular therapy. Nucleic acids · 2023Article
- The screening, identification, design and clinical application of tumor-specific neoantigens for TCR-T cells.Molecular cancer · 2023Review
- Functional Relationships between Long Non-Coding RNAs and Estrogen Receptor Alpha: A New Frontier in Hormone-Responsive Breast Cancer Management.International journal of molecular sciences · 2023Review
- MStoCIRC: A powerful tool for downstream analysis of MS/MS data to predict translatable circRNAs.Frontiers in molecular biosciences · 2022Article
- Proximity-dependent biotinylation technologies for mapping RNA-protein interactions in live cells.Frontiers in molecular biosciences · 2022Review
- Modern epigenetics methods in biological research.Methods (San Diego, Calif.) · 2021Review
- The World of Stable Ribonucleoproteins and Its Mapping With Grad-Seq and Related Approaches.Frontiers in molecular biosciences · 2021Review
- Principles and innovative technologies for decrypting noncoding RNAs: from discovery and functional prediction to clinical application.Journal of hematology & oncology · 2020Review
- Quantitative Proteomics to Identify Nuclear RNA-Binding Proteins of Malat1.International journal of molecular sciences · 2020Article
- Influence of Genetic Variance on Biomarker Levels After Occupational Exposure to 1,6-Hexamethylene Diisocyanate Monomer and 1,6-Hexamethylene Diisocyanate Isocyanurate.Frontiers in genetics · 2020Article
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 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The interaction between non-coding RNAs (ncRNAs) and proteins is crucial for the stability, localization and function of the different classes of ncRNAs. Although ncRNAs, when embedded in various ribonucleoprotein (RNP) complexes, control the fundamental processes of gene expression, their biological functions and mechanisms of action are still largely unexplored. Mass Spectrometry (MS)-based proteomics has emerged as powerful tool to study the ncRNA world: on the one hand, by identifying the proteins interacting with distinct ncRNAs; on the other hand, by measuring the impact of ncRNAs on global protein levels. Here, we will first provide a concise overview on the basic principles of MS-based proteomics for systematic protein identification and quantification; then, we will recapitulate the main approaches that have been implemented for the screening of ncRNA interactors and the dissection of ncRNA-protein complex composition. Finally, we will describe examples of various proteomics strategies developed to characterize the effect of ncRNAs on gene expression, with a focus on the systematic identification of microRNA (miRNA) targets.
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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.