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Integrated pipeline for multiplexed image analysis
- multiplexed-imaging
- python
This repository is to create tflite models for the available ocr models
REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets --- https://arxiv.org/abs/2004.07999
Cyber Defence Monitoring Course Suite :: Suricata, Arkime (and others in the past)
- moloch
- suricata
- monitoring
- nsm
Compilado de recursos sobre Computação Quântica em português
PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturbations at bulk and single-cell levels.
A database of paths that represent the mechanism of action from a drug to a disease in an indication.
- ncats-translator
Various Jupyter notebooks about Common Crawl data
- jupyter-notebook
- common-crawl
- aws-athena
- webarchiving
Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications
- cell-annotation
- multiplexed-imaging
- mpif
Jupyterlab extension to show notebook cell completion notifications
- jupyter
- jupyterlab
- browser-notifications
- jupyterlab-extension
High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations
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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
CancerFoundation: A single-cell RNA sequencing foundation model to decipher drug resistance in cancer
- cancer
- foundation-model
- single-cell
Deciphering cell-cell communication from spatially resolved transcriptomic data at single-cell resolution with subgraph-based attentional graph neural network
American Sign Language Detection is a deep learning end to end project where we can detect American Sign Language.
- asl
- keras
- tensroflow
- tflite
A GTFS-based data transit network data standard suitable for dynamic transit modeling.
CNN, Caffe, LaMem,Azure
Interpretable drug response prediction with graph neural networks over drugs, cell lines, and genes.
Comparing the performance of Stacked Ensemble Learning & machine learning algorithms like Random Forest, Decision Tree, Adaboost, Gradient Boost and XGBoost Classifier in Python for Stock Market Trend Prediction.