Tools
All of our tools, software and research results, etc. are open-source, we strive to make resources reproducible and high quality in: cleanly written, robustly constructed and tested, well-documented, easy-to-use, accessible, customizable.
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An easy-to-use workflow for generating context specific genome-scale metabolic models and predicting metabolic interactions within microbial communities directly from metagenomic data. metaGEM is a Snakemake workflow that integrates an array of existing bioinformatics and metabolic modeling tools, for the purpose of predicting metabolic interactions within bacterial communities of microbiomes. From whole metagenome shotgun datasets, metagenome assembled genomes (MAGs) are reconstructed, which are then converted into genome-scale metabolic models (GEMs) for in silico simulations. Additional outputs include abundance estimates, taxonomic assignment, growth rate estimation, pangenome analysis, and eukaryotic MAG identification.

ProteinGAN, a specialised variant of the generative adversarial network that is able to ‘learn’ natural protein sequence diversity and enables the generation of functional protein sequences. ProteinGAN learns the evolutionary relationships of protein sequences directly from the complex multidimensional amino acid sequence space and creates new, highly diverse sequence variants with natural-like physical properties.

CANDIA is a GPU-powered unsupervised multiway factor analysis framework that deconvolves multispectral scans to individual analyte spectra, chromatographic profiles, and sample abundances, using the PARAFAC (or canonical decomposition) method. The deconvolved spectra can be annotated with traditional database search engines or used as a high-quality input for de novo sequencing methods.
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Repository contains scripts to reproduce the analysis and figures. The data is available at Zenodo, extract the archive to a folder named ‘data’.

This repository contains scripts to reproduce the analysis and figures. The data is available at Zenodo, extract the archive to a folder named ‘data’.