Deep unsupervised learning methods for the identification and characterization of TCR specificity to Sars-Cov-2

Este repositorio contiene la colección de Jupyter Notebooks generados para implementar la metodología descrita en el documento de Tesis "Detección de genomas anómalos de sars-cov-2 por medio de algoritmos de aprendizaje no supervisados".

Scripts and data for the CoVaRR-Net Pillar 6 notebook

SARS-CoV-2 genomics surveillance work notebooks for data management and analysis.

Jupyter Notebooks of COVID19 Data

An example of reading a 13 gigapixel SARS-CoV-2 image (around 27 GB on disk) in Jupyter using Zarr

A Jupyter Notebook about SARS-CoV-2 DNA analysis with Biopython module. Data from National Center for Biotechnology Information.

Data analysis of the COVID-19 outbreak in Italy updated daily from official sources