Non-coding RNA analysis — miRNAs (miRBase, miRDB targets), lncRNAs (LNCipedia, RNAcentral), circRNAs, snoRNAs, and other ncRNA classes. Distinct mechanisms per class — miRNAs repress mRNA; lncRNAs scaffold/decoy/enhance. Use for ncRNA function prediction, miRNA-target prediction, lncRNA functional annotation, and ncRNA-disease association queries.
Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.
Quelldateien prüfen
Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Ein direkter Befehl überspringt den Prüf-Prompt. Prüfen Sie die Quelle, bevor Sie ihn ausführen.
Non-coding RNA analysis — miRNAs (miRBase, miRDB targets), lncRNAs (LNCipedia, RNAcentral), circRNAs, snoRNAs, and other ncRNA classes. Distinct mechanisms per class — miRNAs repress mRNA; lncRNAs scaffold/decoy/enhance. Use for ncRNA function prediction, miRNA-target prediction, lncRNA functional annotation, and ncRNA-disease association queries.
disable-model-invocation
true
Non-Coding RNA Analysis
Pipeline for identifying, annotating, and interpreting non-coding RNAs and their biological roles. Covers microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and other ncRNA classes.
Key principles:
Class determines function — miRNAs repress mRNA translation; lncRNAs have diverse mechanisms (scaffolds, guides, decoys, enhancers); rRNAs/tRNAs are structural
Targets matter more than the ncRNA itself — for miRNAs, the regulated mRNA targets determine the phenotype
Expression context is critical — ncRNAs are highly tissue/cell-type specific
Conservation indicates function — deeply conserved ncRNAs (miR-let-7, MALAT1) have well-established roles
Type-based reasoning — look up, don't guess:
Non-coding RNA function depends on type: miRNA silences target mRNAs (look up targets in miRTarBase/TargetScan), lncRNA has diverse functions (scaffolding, guiding, decoying — check literature for the specific lncRNA), circRNA may sponge miRNAs.
For any ncRNA query: first identify the class from the name/sequence, then select the appropriate evidence source. Do not assume function based on name alone — a gene named "LINC" may have a characterized mechanism, or none at all. Always search PubMed for the specific ncRNA before interpreting. For miRNAs, validated targets (T1) from miRTarBase outweigh any computational prediction — a predicted target with no experimental support is a hypothesis, not a finding. For lncRNAs, mechanism is almost always determined by experimental studies; use with the lncRNA name + "mechanism" or "function" to find relevant evidence. For circRNAs, miRNA sponging is the most common proposed mechanism but is frequently over-claimed — look for CLIP-seq or reporter assay evidence before asserting it.
PubMed_search_articles
When to Use
"What are the targets of miR-21?"
"Find lncRNAs associated with breast cancer"
"Is this lncRNA conserved across species?"
"What miRNAs regulate TP53?"
"Annotate these non-coding RNA IDs"
"Which miRNAs are biomarkers for [disease]?"
Not this skill: For mRNA expression analysis, use tooluniverse-rnaseq-deseq2. For CRISPR screens, use tooluniverse-crispr-screen-analysis.
Core Tools
Tool
Use For
miRBase_search_mirna
Search miRNAs by name, accession, or sequence
miRBase_get_mirna
Detailed miRNA info (sequence, genomic location, family)
miRBase_get_mirna
Mature miRNA sequences and annotations
PubMed_search_articles
Search for validated miRNA targets in literature (e.g., "miR-21 target validation")
LNCipedia_search_lncrna
Search lncRNAs by name, gene symbol, or transcript ID
LNCipedia_get_lncrna
Detailed lncRNA transcript info (sequence, structure, conservation)
LNCipedia_get_lncrna_xrefs
lncRNA gene info with all transcript variants
LNCipedia_search_ncrna_by_type
List all transcripts for a lncRNA gene
LNCipedia_get_lncrna_publications
lncRNA sequence (FASTA format)
RNAcentral_search
Search all ncRNA types across databases
RNAcentral_get_by_accession
Detailed ncRNA annotations from 40+ databases
Rfam_get_family
RNA family details (structure, alignment, species distribution)
piRNA (26-31 nt, RNAcentral): Transposon silencing in germline
circRNA (variable, RNAcentral): miRNA sponges, protein scaffolds (experimental evidence required)
Identification workflow:
Name starts with miR- or hsa-mir- → search miRBase
Name starts with LINC, MALAT, HOTAIR, XIST, or ends in -AS1 → search LNCipedia
Any ncRNA type → search RNAcentral (aggregates all databases)
RNA family question → search Rfam
Phase 1: Target & Interaction Analysis
For miRNAs — the targets determine the biology:
PRIMARY TOOL: ENCORI_get_miRNA_targets looks up miRNA-target interactions from ENCORI/starBase (CLIP-seq-supported + computationally predicted), no download needed:
miRNA → targets: ENCORI_get_miRNA_targets(mirna="hsa-miR-21-5p", clip_min=1) — each hit reports clip_experiments (CLIP-seq support; higher = stronger experimental evidence) and predicted_by (which programs call it). Results are ranked by CLIP support, so the top rows are the best-supported targets.
gene → miRNAs: ENCORI_get_miRNA_targets(gene="TP53") — which miRNAs target a gene.
Supporting/fallback approaches:
3. Literature (for mechanism/validation context): PubMed_search_articles(query="miR-21 target validation luciferase")
4. Cross-references: miRBase_get_mirna_xrefs(accession="MIMAT0000076")
5. For novel miRNAs not in ENCORI: search PubMed for "[miRNA] target".
Well-studied miRNA targets (for common oncomiRs/tumor suppressors):
Prediction only (T3-T4): miRanda, PicTar, RNA22 — hypothesis generation only; do not report as findings
For lncRNAs — the mechanism varies:
lncRNA Mechanism
Example
How to Investigate
Chromatin modifier
HOTAIR, XIST
Check interacting proteins (PRC2, LSD1) via PubMed
Transcription regulator
NEAT1, MEG3
Check nearby genes (cis-regulation) via genomic location
miRNA sponge
MALAT1, circRNAs
Search for miRNA binding sites
Scaffold
NKILA, BCAR4
Check protein interactions
Enhancer RNA
eRNAs
Check ENCODE enhancer annotations
Phase 2: Expression & Tissue Specificity
GTEx_get_median_gene_expression(gene_symbol="MIR21") # miRNA host gene expression# Note: GTEx measures RNA-seq; miRNA expression may need miRNA-seq data from GEO
Interpretation: Tissue-restricted ncRNAs are often functionally important in that tissue. Ubiquitous ncRNAs (like MALAT1) tend to have housekeeping roles.
Interpretation: If miR-21 targets are enriched in apoptosis and PI3K-AKT signaling → miR-21 is an oncomiR that promotes survival by simultaneously suppressing multiple tumor suppressors.
miRTarBase has Cloudflare protection blocking programmatic access. Use the R/Bioconductor data package or bulk download:
# Option 1: Download from miRTarBase bulk export (requires browser download first)# Go to: https://mirtarbase.cuhk.edu.cn/~miRTarBase/miRTarBase_2025/# Download: hsa_MTI.xlsx (human miRNA-target interactions)# Option 2: Use the GitHub data dump# https://github.com/jorainer/mirtarbase — R package with cached data# Once you have the file:import pandas as pd
mti = pd.read_excel("hsa_MTI.xlsx") # or read_csv if TSV# Filter for your miRNA
mir21_targets = mti[mti['miRNA'].str.contains('hsa-miR-21', case=False, na=False)]
print(f"miR-21 validated targets: {len(mir21_targets)}")
# Filter by evidence strength
strong = mir21_targets[mir21_targets['Support Type'].str.contains(
'Luciferase|Reporter|Western|CLIP', case=False, na=False
)]
print(f" Strong evidence (reporter/CLIP): {len(strong)}")
for _, row in strong.head(10).iterrows():
print(f" {row['Target Gene']:10s} — {row['Support Type']}")
When download is not available: Use the built-in reference table in Phase 1 for well-studied miRNAs, or search PubMed for validated targets.
Limitations
miRNA target prediction is noisy — even the best algorithms have >50% false positive rates; always prioritize experimentally validated targets
lncRNA function is poorly characterized — only ~5% of annotated lncRNAs have known functions
Expression measurement varies — miRNA-seq, RNA-seq, and microarray capture different ncRNA classes; check the assay type
Species differences — miRNAs are often conserved but lncRNAs are frequently species-specific; cross-species lncRNA comparisons are unreliable
