GRaph-based Analysis of Subcellular/Spatial Proteomics
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Updated
Oct 6, 2026 - Python
GRaph-based Analysis of Subcellular/Spatial Proteomics
Fine-tuning a pre-trained BERT Model (ProtBert) in PyTorch using DeepLoc Dataset
Support Vector Machine-based method for subcellular localization of human proteins using amino acid compositions, their order, and similarity search
Improved method for predicting subcellular localization of eukaryotic proteins
Isoform-resolved subcellular localization of human lncRNAs: gene-level analysis masks compartment-spanning isoforms (dry-only, GTEx + ENCODE). Code for Tani, submitted.
Agent skill to retrieve, analyze, and visualize Human Protein Atlas (HPA) data—featuring 3D subcellular organelle mapping, 10-system anatomical IHC heatmaps, RNA-to-protein concordance, cancer pathology profiling, and standalone HTML5 dashboards.
CPPLocPred: A method for predicting subcellular location prediction of cell penetrating peptides
NuclQ - an ImageJ plugin to quantify intensity levels by distance to the nuclear membrane.
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