AI-powered analysis of cellular senescence for aging research, cancer therapy response, and senolytic drug development.
원문 언어: 영어
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이 저장소의 skills
SkillsMP는 swaruplab/operon에서 579개의 skill을 수집했습니다. skill을 열어 소스와 세부 정보를 확인하세요.
swaruplab/operon수집된 skill 579개 중 40개를 표시합니다.
AI-powered analysis of cellular senescence for aging research, cancer therapy response, and senolytic drug development.
원문 언어: 영어
EHR Chat Assistant
원문 언어: 영어
Chemical Lab Agent
원문 언어: 영어
An LLM chemistry agent with expert-designed tools for organic synthesis, drug discovery, and materials design.
원문 언어: 영어
Compute RDKit-driven molecular properties (MW, logP, TPSA, QED, Lipinski) for a SMILES string to support downstream drug discovery tools.
원문 언어: 영어
Analyzes events through chemistry lens using molecular structure, reaction mechanisms, thermodynamics, kinetics, and analytical techniques (spectroscopy, chromatography, mass spectrometry). Provides insights on chemical processes, material properties,…
원문 언어: 영어
Autonomous chemical synthesis & analysis
원문 언어: 영어
Extracts medical entities (Diseases, Medications, Procedures) from unstructured clinical text using regex and simple rules (or LLM wrappers).
원문 언어: 영어
Structure raw clinical notes into SOAP-format summaries with explicit contradictions, missing data, and ICD-linked assessments using the provided prompt + usage script.
원문 언어: 영어
Guide foundry
원문 언어: 영어
Predicts potential off-target sites for a given sgRNA sequence using mismatch analysis.
원문 언어: 영어
AI-powered integration of cryo-EM structural data with generative AI and molecular dynamics for structure-based drug design targeting flexible proteins and membrane complexes.
원문 언어: 영어
AI-powered circulating tumor DNA dynamics analysis for molecular residual disease detection, treatment response monitoring, and early relapse prediction using liquid biopsy.
원문 언어: 영어
Publication-quality visualizations for biomedical and genomics data. Use when creating volcano plots, heatmaps, UMAP plots, dot plots, survival curves, forest plots, or multi-panel figures. Includes scanpy, matplotlib, seaborn, plotly workflows with…
원문 언어: 영어
AI-driven integration of cellular imaging, laser microdissection, and ultra-sensitive mass spectrometry for spatially-resolved single-cell proteomics.
원문 언어: 영어
AI-powered patient digital twin creation for clinical trial simulation, treatment outcome prediction, and personalized medicine using real-world data and multi-omics integration.
원문 언어: 영어
Checks for potential drug-drug interactions (DDIs) between a list of medications.
원문 언어: 영어
Provides comprehensive tools for working with Electronic Health Records (EHR) using the HL7 FHIR standard.
원문 언어: 영어
AI-powered DNA methylation analysis using MethylGPT foundation models for epigenomic profiling, differential methylation detection, and cancer epigenome characterization.
원문 언어: 영어
AI-powered design of targeted gene panels for clinical and research applications including cancer diagnostics, pharmacogenomics, and rare disease testing.
원문 언어: 영어
Federated variant lookup across 9 genomic databases — GWAS Catalog, Open Targets, PheWeb (UKB, FinnGen, BBJ), GTEx, eQTL Catalogue, and more.
원문 언어: 영어
AI-powered analysis for predicting optimal immune checkpoint inhibitor combinations based on tumor microenvironment, biomarkers, and molecular profiling.
원문 언어: 영어
AI-powered analysis of long-read sequencing data (PacBio, ONT) for structural variant detection, isoform discovery, epigenetic modifications, and de novo assembly.
원문 언어: 영어
AI-powered analysis of microbiome-cancer interactions including tumor microbiome profiling, immunotherapy response prediction, and microbiome-targeted therapeutic opportunities.
원문 언어: 영어
AI-powered molecular glue discovery for targeted protein degradation, enabling neo-substrate recruitment and undruggable target degradation through E3 ligase interface modulation.
원문 언어: 영어
Evolve Molecules
원문 언어: 영어
Analyzes medical images (X-ray, MRI, CT) using multimodal LLMs to identify anomalies and generate reports.
원문 언어: 영어
Foundation model-powered spatial transcriptomics analysis leveraging 53M+ spatially resolved cells for cellular architecture modeling and tissue niche discovery.
원문 언어: 영어
AI-powered NK cell therapy design for cancer immunotherapy including CAR-NK engineering, memory-like NK generation, and KIR/HLA matching optimization.
원문 언어: 영어
AI-powered analysis of patient-derived organoid (PDO) drug screening for personalized oncology treatment selection and biomarker discovery.
원문 언어: 영어
AI-powered pan-cancer analysis integrating genomic, transcriptomic, proteomic, and epigenomic data for cancer subtyping, driver identification, and cross-cancer pattern discovery.
원문 언어: 영어
AI-driven pharmacogenomic analysis for precision dosing and adverse event prediction using multi-omics data.
원문 언어: 영어
Fuse genomic variants, pathology findings, and clinical context to draft evidence-linked therapy options for tumor board review.
원문 언어: 영어
Predicts 3D protein structures from amino acid sequences using ESMFold or AlphaFold3 (mock).
원문 언어: 영어
AI-powered RNA velocity analysis for predicting cellular state transitions, differentiation trajectories, and dynamic gene regulation from single-cell RNA sequencing data.
원문 언어: 영어
Execute the MAD-based single-cell RNA-seq QC workflow (scripts + Python API) to filter low-quality cells and emit reports plus filtered AnnData files.
원문 언어: 영어
Performs quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive visualizations. Use when users request QC analysis, filtering low-quality cells, assessing data quality, or…
원문 언어: 영어
An agent that interprets spatial transcriptomics data to propose mechanistic hypotheses and analyze tissue organization.
원문 언어: 영어
AI-powered spatial epigenomics analysis combining chromatin accessibility, histone modifications, and DNA methylation with spatial coordinates for tissue architecture mapping.
원문 언어: 영어
Spatial analyst
원문 언어: 영어