A database of paths that represent the mechanism of action from a drug to a disease in an indication.
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A database of paths that represent the mechanism of action from a drug to a disease in an indication.
How to create Selfie2Anime from tflite model to Android.
AuShadha (औषध): Means medicine in Sanskrit. This is a Electronic Medical Records (EMR) and Public Health Management for small clinics written in Django and Dojo
Code repository for The Automation Ahead series, showcasing practical examples for GenAI-driven automation in investments. Each installment dives into specific tools, techniques, and use cases to help professionals assess and apply GenAI effectively.
SplineDist: Automated Cell Segmentation with Spline Curves
Peax is a tool for interactive visual pattern search and exploration in epigenomic data based on unsupervised representation learning with autoencoders
Various Jupyter notebooks about Common Crawl data
Research experiments exploring uncommon quant techniques.
Exercises for the lecture "Selected Topics in Audio Signal Processing"
Simple demo of filtering signal with an LPF and plotting its Short-Time Fourier Transform (STFT) and Laplace transform, in Python.
Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications
Using ag-Grid in Jupyter notebooks.
Repository for paper scMulan: a multitask generative pre-trained language model for single-cell analysis.
Cell and line magic for PGF/TikZ-to-SVG rendering in Jupyter notebooks
Jupyterlab extension to show notebook cell completion notifications
Classification and Gradient-based Localization of Chest Radiographs using PyTorch.
The repository host gives no description.
High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations
Open Matrix (OMX)
Tools for drawing 2d and 3d interactive visualizations using Jupyter proxy widgets
The repository host gives no description.
Deep learning model for single-cell inference of multi-omic profiles from a single input modality.
open source E-book on statistical physics
Mobile Deep Learning Projects, published by Packt