xianglin226/Benchmarking-Single-Cell-Perturbation
Single-Cell (Perturbation) Model Library
This library helps biomedical researchers and drug discovery scientists evaluate and compare various computational models that predict how single cells respond to genetic or chemical alterations. It takes single-cell perturbation data as input and provides an organized collection of methods to simulate and understand cellular changes, which can accelerate drug development and disease understanding. Researchers in drug discovery, genomics, and cell biology would find this useful.
Use this if you need to benchmark or apply different computational models to understand how individual cells react to specific gene edits or drug treatments.
Not ideal if you are looking for a tool to directly analyze raw single-cell sequencing data without focusing on perturbation response modeling.
Stars
93
Forks
6
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 10, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/xianglin226/Benchmarking-Single-Cell-Perturbation"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related models
tirtharajdash/LMLFStar
Generating target-specific novel lead molecules using an LLM
raghavagps/pptstab
PPTStab: Designing of thermostable proteins with a desired melting temperature
CelVoxes/ceLLama
Cell type annotation with local Large Language Models (LLMs) - Ensuring privacy and speed with...
kenflab/LLM-scCurator
Data-centric marker distillation for zero-shot cell-type and spatial annotation with LLMs.
Shreyas-Bhat/LMLF
Code for "Generating Novel Leads for Drug Discovery Using LLMs with Logical Feedback" --...