Name: Francesco Patane, MSc
Type: User
Company: SynBio, University of Padova
Bio: Biotechnologist. Keen on scientific programming and machine learning applied to drug discovery.
Research Intern at University of Padova, Italy
Twitter: francescop966
Location: Padova, Italy
Blog: biotechub.com
Francesco Patane, MSc's Projects
Create a bioactivity prediction model using molecular descriptors (PADEL) and supervised machine learning (ML).
Code for Mastering Python for Bioinformatics (O'Reilly, 2021, ISBN 9781098100889)
simple bioinfomatics tools
This R script allow you to retrieve entrez gene accession from ensembl gene ids from RNA seq analysis. Entrez symbols can then utilize to perform gene enrichment analysis of up and downregulate genes in platforms like Enrichr.
a comprehensive repository designed to empower researchers, scientists, and enthusiasts in the fields of bioinformatics and biotechnology. This repository serves as a one-stop destination for a myriad of invaluable resources, ranging from insightful guides and cutting-edge research papers to informative podcasts, web tools, and efficient workflows
Model interpretability and understanding for PyTorch
This pipeline provides a way to perform pharmaceutical compounds virtual screening using similarity-based analysis, ligand-based and structure-based techniques. The pipeline contains a collections of modules to perform a variety of analysis.
10 Weeks, 20 Lessons, Data Science for All!
Deep functional residue identification
The scope of the project is to create a public and easy to access repository containing a vast coort of similarity-based drug discovery models.
eNERVE is a dynamic, high-throughput and standalone in silico reverse vaccinology pipeline for eukaryotic protein candidate vaccines (PVCs) discovery from entire proteomes (FASTA file).
eNERVE graphic user interface via Docker
enerve code repo for docker container
pre-trained models to run DeepFRI in enerve
Evolutionary Scale Modeling (esm): Pretrained language models for proteins
Repository containing colab sheets for experimenting with ESM2 pre-trained large protein language model.
An easy fragment of code to read in fasta format files
Config files for my GitHub profile.
Hidden markov models implementation tutorials
Google Colab Tutorials for IBM3202
iFeature is a comprehensive Python-based toolkit for generating various numerical feature representation schemes from protein or peptide sequences. iFeature is capable of calculating and extracting a wide spectrum of 18 major sequence encoding schemes that encompass 53 different types of feature descriptors. Furthermore, iFeature also integrates fi
iFeatureOmega is a comprehensive platform for generating, analyzing and visualizing more than 170 representations for biological sequences, 3D structures and ligands. To the best of our knowledge, iFeatureOmega supplies the largest number of feature extraction and analysis approaches for most molecule types compared to other pipelines. Three versio
The LinearDesign mRNA design software.