Non-coding RNA research explores RNA molecules that do not encode proteins but regulate gene expression, chromatin state, RNA stability, translation, signaling pathways, and disease-associated molecular programs.
Non-coding RNAs are central regulators of cellular identity, gene expression, development, and disease. They include long non-coding RNAs, microRNAs, circular RNAs, small regulatory RNAs, and other RNA species that influence transcriptional, post-transcriptional, and epigenetic regulation.
At PanorOmics, non-coding RNA is presented as a major transcriptomic research area: a regulatory layer connecting genome function, epigenomics, RNA expression, cancer biology, biomarker discovery, and precision medicine.
Studying lncRNAs that regulate chromatin organization, transcription, RNA processing, signaling pathways, and disease-associated gene regulation.
Analyzing microRNAs that control post-transcriptional gene expression by targeting messenger RNAs and shaping regulatory networks.
Investigating circular RNAs as stable regulatory molecules involved in gene expression control, RNA binding, and disease biology.
Using non-coding RNA signatures to support disease classification, prognosis, therapeutic response prediction, and precision medicine research.
Sequencing-based transcriptome profiling used to detect and quantify coding and non-coding RNA species across biological samples.
Specialized sequencing of small RNA molecules such as microRNAs, piRNAs, and other short regulatory RNAs.
Ribo-depleted RNA sequencing that captures a broader range of coding and non-coding transcripts beyond polyadenylated RNA.
Single-cell transcriptomics used to study non-coding RNA expression patterns across individual cells and cell states.
Targeted validation and quantification of specific non-coding RNAs in research and clinical biomarker studies.
Measures lncRNA expression patterns and their association with biological regulation, disease states, and molecular pathways.
Quantifies microRNAs involved in post-transcriptional regulation, disease biology, and biomarker discovery.
Identifies circular RNAs formed through back-splicing and evaluates their regulatory and biomarker potential.
Profiles short regulatory RNA species involved in gene silencing, genome defense, and post-transcriptional control.
Models interactions among lncRNAs, circular RNAs, microRNAs, and mRNAs within regulatory RNA networks.
Uses non-coding RNA patterns to classify disease, predict outcomes, and support translational biomarker research.
Related transcriptomic approaches such as RNA expression, RNA sequencing, and alternative splicing are explored across the Transcriptomics Research Center.
The discovery of lin-4 revealed that small non-coding RNAs can regulate gene expression.
The discovery of let-7 and broader microRNA conservation established microRNAs as important regulators across species.
Large-scale transcriptomic studies revealed that many non-coding transcripts participate in gene regulation, chromatin control, and disease biology.
Circular RNAs emerged as stable regulatory RNA molecules with roles in gene expression control, RNA binding, and biomarker discovery.
ceRNA models connected lncRNAs, circular RNAs, microRNAs, and mRNAs into broader post-transcriptional regulatory networks.
Single-cell transcriptomics began revealing cell-type-specific non-coding RNA expression patterns and regulatory programs.
AI increasingly supports non-coding RNA annotation, target prediction, regulatory network modeling, and biomarker discovery.
Continue exploring the Transcriptomics Research Center.
Continue exploring the Transcriptomics Research Center.
Continue exploring the Transcriptomics Research Center.