deepcpg
DNA predictor
A deep learning framework for predicting DNA methylation states from incomplete data.
Deep neural networks for predicting CpG methylation
143 stars
13 watching
67 forks
Language: Python
last commit: about 5 years ago
Linked from 1 awesome list
deep-neural-networksdeeplearningepigeneticsmethylationsingle-cell
seandavi/awesome-single-cellRelated projects:
| Repository | Description | Stars |
|---|---|---|
 bplaye/nnk_dti | An open-source project evaluating deep learning methods for predicting ligands and drugs in chemogenomics | 3 |
 atomistic-machine-learning/dtnn | An open-source Python framework for developing machine learning models to predict quantum-mechanical observables of molecular systems. | 77 |
 weiqiangzhou/bird | A software tool that predicts DNase I hypersensitivity based on gene expression data | 30 |
 shen-lab/deepaffinity | A deep learning framework for predicting protein-compound affinity from molecular sequences and structures | 137 |
 dougsm/ggcnn | A deep learning-based system for generating precise grasp poses for robots in real-time | 514 |
 imatge-upc/saliency-2016-cvpr | This project proposes a solution to predict salient areas in images using convolutional neural networks. | 185 |
 paularindam/chemixnet | A deep learning framework for predicting chemical properties using mixed neural architectures and multiple molecular representations | 1 |
 masashitsubaki/cpi_prediction | CPI prediction tool using graph neural networks and convolutional neural networks | 159 |
 lifanchen-simm/transformercpi | Develops a deep learning model to predict compound-protein interactions by leveraging sequence-based learning and self-attention mechanisms | 134 |
 bjoux2/deepdtis_dbn | A Python framework for deep learning-based drug-target interaction prediction using a DBN architecture. | 48 |
 hkmztrk/deepdta | A system that predicts drug-target binding affinity using convolutional neural networks and protein sequences. | 225 |
 davidtellez/contrastive-predictive-coding | An unsupervised machine learning algorithm that extracts meaningful patterns from data using contrastive predictive coding | 525 |
 jaechanglim/gnn_dti | This project implements a deep learning approach to predicting docking affinities for molecules with proteins | 66 |
 chemprop/chemprop | A software framework for machine learning of chemical property prediction using message passing neural networks | 1,786 |
 andreaskapou/melissa | A software framework for analyzing single-cell DNA methylation data using Bayesian methods | 14 |