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iMetActv2.0
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Bioinformatics Platform
iMetAct v2.0 — Inference of Metabolic Enzyme ActivityData sourced from TCGA Research Network. For research use only.
陕ICP备2023012414号-1

Subtype Prediction

Machine Learning

Upload HCC RNA-seq expression data to predict metabolic subtypes. iMetAct infers enzyme activities and a Random Forest classifier (trained on TCGA-LIHC) assigns each sample to C1 (Glycolytic), C2 (Lipogenic), or C3 (Mixed).

How It Works

1

Upload Data

Upload HCC RNA-seq expression matrix (CSV/TSV/TXT).

2

Validate & Predict

iMetAct infers enzyme activity, Random Forest classifies subtypes.

3

Review & Download

View pie chart, per-sample results, and download CSV report.

Upload Expression Data

Upload expression matrix (CSV/TSV/TXT)

Drag & drop or click to browse · .csv,.tsv,.txt · Max 50MB

Model Information

AlgorithmRandom Forest
Training DataTCGA-LIHC (n=371)
Features2,678 enzymes (iMetAct)
Accuracy92.3% (10-fold CV)

Prediction Results

No Results Yet

Configure parameters and run the analysis to see results here.