The Difference
Generic AI vs LancetClaw
Generic AI
Based on my training data, RNA-seq analysis typically involves using tools like DESeq2 to identify differentially expressed genes. The general approach includes normalizing count data, performing statistical tests, and visualizing results with volcano plots...
LancetClaw
library(DESeq2)dds <- DESeqDataSetFromMatrix(...)res <- results(dds, alpha = 0.05)
Capabilities
6 core research capabilities
Genomics & Multi-omics
RNA-seq differential expression, single-cell clustering, pathway enrichment. Real DESeq2, Seurat, Scanpy code.
Drug & Clinical Research
Virtual screening, ADMET prediction, drug interactions. Evidence from thousands of clinical trials.
AI Medical Imaging
Pathology slide analysis, image annotation, DICOM processing. Automated feature extraction and reporting.
Figure Generation
Volcano plots, heatmaps, pathway diagrams, survival curves. Publication-ready, export as SVG/PNG/PDF.
Skills Marketplace
140+ Scientific Skills
Pre-built research skills that run real code. Each skill is a tested pipeline — from data input to publication-ready output.
Genomics
Literature
Drug Discovery
Medical Imaging
Visualization
Statistics
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