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cellular-senescence-agent

Maintainer FreedomIntelligence · Last updated April 1, 2026

Cellular senescence analysis: marker scoring, SASP profiling, tissue aging assessment.

OpenClawNanoClawAnalysisReproductioncellular-senescence-agent🧠 bioos extended suiteresearch infrastructure & agentscellular

Original source

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/cellular-senescence-agent

Maintainer
FreedomIntelligence
License
MIT
Last updated
April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

  • The Cellular Senescence Agent provides comprehensive AI-driven analysis of cellular senescence signatures for aging research, cancer biology, and senolytic therapeutic development.
  • When identifying senescent cells in tissue or single-cell data.
  • To analyze senescence-associated secretory phenotype (SASP).
  • For predicting senolytic drug sensitivity.
  • When studying therapy-induced senescence in cancer.

Source Doc

Excerpt From SKILL.md

Core Capabilities

  1. Senescence Scoring: Calculate senescence signatures from transcriptomic data.

  2. SASP Profiling: Characterize senescence-associated secretory phenotype composition.

  3. Single-Cell Detection: Identify senescent cells in scRNA-seq data.

  4. Senolytic Prediction: Predict sensitivity to senolytic drugs.

  5. Tissue Aging: Assess senescence burden across tissues.

  6. Cancer Senescence: Analyze therapy-induced senescence.

Senescence Markers

CategoryMarkersDetection
Cell cyclep16INK4a, p21CIP1, p53Expression, IHC
SA-β-galGLB1 (lysosomal)Activity assay
SASPIL-6, IL-8, MMP3, PAI-1Expression, secretion
DNA damageγH2AX, 53BP1 fociImmunofluorescence
MorphologyEnlarged, flattenedImaging
EpigeneticSAHF, SAHMsChromatin marks

Workflow

  1. Input: Bulk or single-cell RNA-seq, proteomics, imaging data.

  2. Signature Scoring: Apply senescence gene signatures.

  3. SASP Analysis: Profile secretory phenotype.

  4. Cell Identification: Flag senescent cells (single-cell).

  5. Senolytic Prediction: Match to drug sensitivity profiles.

  6. Burden Estimation: Quantify senescence load.

  7. Output: Senescence scores, SASP profile, drug recommendations.

Use cases

  • When identifying senescent cells in tissue or single-cell data.

Not for

  • Do not rely on this catalog entry alone for installation or maintenance details.

Upstream Related Skills

  • Single_Cell - For scRNA-seq analysis
  • Cancer_Metabolism_Agent - For metabolic senescence
  • Tumor_Microenvironment - For SASP effects

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