MLi-lab-Bioinformatics-NJUCM / HerbiVLinks
HerbiV是一个具有多种功能的中药网络药理学分析工具,可进行经典的网络药理学及反向网络药理学分析。HerbiV is a multi-functional traditional chinese medicine network pharmacology analysis tool for classical network pharmacology and reverse network pharmacology.
☆41Updated 3 months ago
Alternatives and similar repositories for HerbiV
Users that are interested in HerbiV are comparing it to the libraries listed below
Sorting:
- A Python spider for TCMSP☆33Updated 2 years ago
- Learning materials, files and codes for bioinformatics☆180Updated 2 years ago
- GeneCompass☆86Updated 2 months ago
- Deep Transfer Learning of Drug Sensitivity by Integrating Bulk and Single-cell RNA-seq data☆55Updated last year
- PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturb…☆57Updated 8 months ago
- Deep Learning the T Cell Receptor Binding Specificity of Neoantigen☆84Updated 3 years ago
- A Deep Learning based Efficacy Prediction System for drug discovery☆70Updated 2 years ago
- ☆61Updated 6 months ago
- KGWAS: novel genetics discovery enabled by massive functional genomics knowledge graph☆73Updated 5 months ago
- Multi-omics integration method using AE and GCN☆36Updated 2 years ago
- An AI Agent for Fully Automated Multi-omic Analyses☆192Updated 10 months ago
- materials for AIDD course☆14Updated 3 months ago
- ☆53Updated 2 years ago
- A visible neural network model for drug response prediction☆148Updated last year
- ☆43Updated last year
- NeuronMotif: deciphering cis-regulatory codes by layerwise demixing of deep neural networks☆15Updated 2 years ago
- This crawler can automatically crawl the target information of various molecular targets prediction websites, including SwissTargetPredic…☆19Updated last year
- ☆53Updated 8 months ago
- Transformer for One-Stop Interpretable Cell-type Annotation☆144Updated last year
- ☆25Updated 4 months ago
- A deep generative neural network based approach to impute drug response☆21Updated 4 years ago
- PyTorch implementation of the MIDAS algorithm for single-cell multimodal data integration (Nature Biotechnology 2024).☆59Updated last week
- ☆207Updated last year
- ☆31Updated 3 years ago
- Utilizing single-cell omics from patients tumor to predict response and resistance.☆71Updated 2 years ago
- ☆84Updated 2 weeks ago
- ☆125Updated 4 months ago
- Machine learning-based integration model with elegant performance☆153Updated 3 weeks ago
- ☆76Updated 2 weeks ago
- scDrug: From scRNA-seq to Drug Repositioning☆35Updated 2 years ago