Repository Index

GraphDTA: Predicting drug-target binding affinity with graph neural networks

Source code for "DeepDTA: deep drug-target binding affinity prediction"

• protein-ligand-interactions
• convolutional-neural-networks

RNA-seq prediction with deep convolutional neural networks.

Allocators, I/O streams, math, geometry, image and audio processing for D

• utility-library
• dlang
• linear-algebra
• computational-geometry

Umbrella package of the 'spatstat' family................

• r
• spatial-analysis
• spatial-data
• spatstat

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.

The implementation code for "DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction"

• generative-adversarial-network
• mri-reconstruction
• computer-vision
• deep-learning

PhyloNetworks: a julia package with utilities for phylogenetic networks

The V Tensor Library

• v
• hacktoberfest
• autograd
• deep-learning

🏃 The go-to single-cell Foundation Model

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

Optimising chemical reactions using machine learning

• chemistry
• machine-learning
• optimization
• bayesian-optimization

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

⚡ Open-source software for deep learning-based digital pathology

• deep-learning
• machine-learning
• digital-pathology
• computational-pathology

Easy link prediction tool

• python
• network-analysis
• link-prediction
• research

A tool for cell instance aware segmentation in densely packed 3D volumetric images

• segmentation
• deep-learning
• bioinformatics
• neural-network

Axon/Myelin segmentation using Deep Learning

• deep-learning
• machine-learning
• myelin
• axon

Graph and Network algorithms in Julia

Layout algorithms for graphs and trees in pure Julia.

• graph-visualization

Accelerated tensor operations and dynamic neural networks based on reverse mode automatic differentiation for every device that can run Swift - from watchOS to Linux

• deep-learning
• deep-neural-networks
• gradient-descent
• automatic-differentiation

A platform independent tensor library with autograd for the JVM

• java
• library
• deep-neural-networks

NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions

• computational-biology
• bioinformatics
• graph-convolution
• deep-learning

👩‍💻 Matrix and other math, accelerated by WebGPU and WASM

• webgpu
• deno
• matrix
• machine-learning

Deep learning model for single-cell inference of multi-omic profiles from a single input modality.

• single-cell
• scrna-seq
• scatac-seq
• deep-neural-networks