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ProtTrans is providing state of the art pretrained language models for proteins. ProtTrans was trained on thousands of GPUs from Summit and hundreds of Google TPUs using Transformers Models.
TorchXRayVision: A library of chest X-ray datasets and models. Classifiers, segmentation, and autoencoders.
WebGL accelerated JavaScript molecular graphics library
Foundation Models for Genomics & Transcriptomics
Pathology Foundation Model - Nature Medicine
bert-loves-chemistry: a repository of HuggingFace models applied on chemical SMILES data for drug design, chemical modelling, etc.
Genomic Pretrained Network - GPN, GPN-MSA, PhyloGPN, GPN-Star
Deep Reinforcement Learning for de-novo Drug Design
Repository for Nicheformer: a foundation model for single-cell and spatial omics
A python Two Source Energy Balance model for estimation of evapotranspiration with remote sensing data
🏃 The go-to single-cell Foundation Model
A collection of tasks to probe the effectiveness of protein sequence representations in modeling aspects of protein design
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.
BulkFormer: A large-scale foundation model for human bulk transcriptomes
Repository for paper scMulan: a multitask generative pre-trained language model for single-cell analysis.
Deep learning model for single-cell inference of multi-omic profiles from a single input modality.
CancerFoundation: A single-cell RNA sequencing foundation model to decipher drug resistance in cancer