Bi-Directional Equivariant Long-Range DNA Sequence Modeling
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MolTrans: Molecular Interaction Transformer for Drug Target Interaction Prediction (Bioinformatics)
A Network Integration Approach for Drug-Target Interaction Prediction
MOGONET (Multi-Omics Graph cOnvolutional NETworks) is a novel multi-omics data integrative analysis framework for classification tasks in biomedical applications.
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.
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
PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturbations at bulk and single-cell levels.
TypeDB Bio: Biomedical Knowledge Graph
- bioinformatics
- knowledge-graph
- knowledge-base
- drug-discovery
NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
- computational-biology
- bioinformatics
- graph-convolution
- deep-learning
Run scripts, explore your genome, and get personalized explanations — all in natural dialogue.
- analysis
- claude
- claudecode
- dna
High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations
Predicting Cell Health with Morphological Profiles
- carpenter-lab
- morphological-profiling
- crispr
- cell-painting
PyTorch implementation of "TGSA: Protein-Protein Association-Based Twin Graph Neural Networks for Drug Response Prediction with Similarity Augmentation"
Data logistics system enabling real-time pathogen surveillance. Built for the Seattle Flu Study.
- postgres
- postgresql
- python
- infectious-disease
Official implementation of JAMIE, Joint variational Autoencoders for Multimodal Imputation and Embedding
- autoencoder
- imputation
- integration
- multimodal
A flexible Julia toolkit for high-dimensional cellular profiles
- julia
- morphological-analysis
- high-content-screening
DetecDiv provides a comprehensive set of tools to analyze time microscopy images using deep learning methods. The software structure is such that data can be processed either at the command line or using a graphical user-interface. Detecdiv classification models include : image classification and regression, semantic segmentation, LSTM networks to analyze data and image timeseries.