AI-based pathology predicts origins for cancers of unknown primary - Nature
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- wsi-images
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AI-based pathology predicts origins for cancers of unknown primary - Nature
An automatic code generator for nonlinear model predictive control (NMPC) and the continuation/GMRES method (C/GMRES) based numerical solvers for NMPC
Sparse matrix formats for linear algebra supporting scientific and machine learning applications
OpenBioLink is a resource and evaluation framework for evaluating link prediction models on heterogeneous biomedical graph data.
Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.
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
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
Easy link prediction tool
a physics library wrapper for love2d
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.
Predicting Cell Health with Morphological Profiles
PyTorch implementation of "TGSA: Protein-Protein Association-Based Twin Graph Neural Networks for Drug Response Prediction with Similarity Augmentation"
Nova DSO Tracker is an open-source Flask application for astrophotographers, providing real-time tracking of deep-sky objects' altitude, observability prediction, and integration with Stellarium and SIMBAD databases.
Satellite prediction library for crystal using the sgp4 model
DeepAEG: A model for predicting cancer drug response based on data enhancement and edge-collaborative update strategies
Interpretable drug response prediction with graph neural networks over drugs, cell lines, and genes.
GNN-based gene-selection deep learning model for drug response prediction