scRank
importedsoftware/scrank
A computational method to rank and infer drug-responsive cell population towards in-silico drug perturbation using a target-perturbed gene regulatory network (tpGRN) for single-cell transcriptomic…
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- GPL-3.0(osi)
- Status
- maintained
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/ZJUFanLab/scRank
- Documentation
- unknown
- Tags
- cell-type-prioritization · drug-response · gene-network · manifold-learning · single-cell
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- scDHMapmanifold-learning · single-cell
Model-based deep hyperbolic manifold learning for visualizing complex hierarchical structures in single-cell genomics data
- topometrymanifold-learning · single-cell
Systematically learn and evaluate the latent geometry of high-dimensional data, with a focus on scRNAseq analysis
- cellrankmanifold-learning
CellRank: dynamics from multi-view single-cell data
- spd_learnmanifold-learning
SPDlearn: A Geometric Deep Learning Python Library for Neural Decoding Through Trivialization
- TSMNetmanifold-learning
Code and reuslts accompanying the NeurIPS 2022 paper with the title SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG
- ISCMFmanifold-learning
ISCMF: Integrated Similarity-Constrained Matrix Factorization for Drug-Drug Interaction Prediction
- api.github.com/repos/ZJUFanLab/scRankretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2025-10-16, 76 stars, license reported as GPL-3.0. Category and schematic were assigned by keyword heuristics and are unreviewed.
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/v1/entries/25.json→ .entries["scrank"]
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