Repository Index

GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations

Genomic Pretrained Network - GPN, GPN-MSA, PhyloGPN, GPN-Star

• dna
• language-model
• variant-effect-prediction
• genomics

UCE is a zero-shot foundation model for single-cell gene expression data

Native R and Python sample-deletion robustness for omics: candidate certificates, minimum deletion bounds, Bioconductor model refits and donor-level pseudobulk

• bioinformatics
• exact-optimization
• metabolomics
• paired-data

RNA-seq prediction with deep convolutional neural networks.

MolTrans: Molecular Interaction Transformer for Drug Target Interaction Prediction (Bioinformatics)

Ankh: Optimized Protein Language Model

Probabilistic cell segmentation for in situ spatial transcriptomics

A Network Integration Approach for Drug-Target Interaction Prediction

Open-source software for exploring and analyzing large, high-dimensional image-derived data.

• cellprofiler-analyst
• cellprofiler
• image-analysis
• machine-learning

OpenBioLink is a resource and evaluation framework for evaluating link prediction models on heterogeneous biomedical graph data.

🏃 The go-to single-cell Foundation Model

• batch-correction
• cell-biology
• celltype-annotation
• denoising

LLM for Drug Editing, ICLR 2024

• chatgpt
• conversation
• drug
• drug-discovery

Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.

• disentanglement
• drug-discovery
• genomics
• perturbation

TransformerCPI: Improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments(BIOINFORMATICS 2020) https://doi.org/10.1093/bioinformatics/btaa524

• self-attention
• compound-protein-interaction
• transformercpi
• structure-free-virtual-sreening

Interpretable bilinear attention network with domain adaptation improves drug-target prediction.

Python package for image-based profiling

• cytominer
• microscopy
• morphological-profiling
• python

A collection of tasks to probe the effectiveness of protein sequence representations in modeling aspects of protein design

• protein
• protein-sequences
• protein-design
• representation-learning

code to run sei and obtain sei and sequence class predictions

CASSIA: A Multi-Agent LLM-Based Single-Cell Cell Type Annotation Framework

• ai4science
• llm
• multiagent-systems
• prompt-engineering

Official repo for CellPLM: Pre-training of Cell Language Model Beyond Single Cells.

PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturbations at bulk and single-cell levels.

Peax is a tool for interactive visual pattern search and exploration in epigenomic data based on unsupervised representation learning with autoencoders

• epigenomics
• pattern-search
• data-visualization
• interactive-machine-learning

Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications

• cell-annotation
• multiplexed-imaging
• mpif