There are 3 repositories under microbes topic.
DecontaMiner is a tool designed and developed to investigate the presence of contaminating sequences in unmapped NGS data. It can suggest the presence of contaminating organisms in sequenced samples, that might derive either from laboratory contamination or from their biological source, and in both cases can be considered as worthy of further investigation and experimental validation. The novelty of DecontaMiner is mainly represented by its easy integration with the standard procedures of NGS data analysis, while providing a complete, reliable, and automatic pipeline. https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2684-x
To explore biotic associations of microbes at the community level. See the detailed package tutorial (https://joshualiuxu.github.io/).
A constraint-based method for prediction of metabolic engineering targets using ecModels of metabolism
Deep learning-based instance segmentation tool for roundish objects in 2D and 2D+t data
Omero based integrated Workflow for annotating Microbes in the Cloud
A theorectical investigation into mechanisms of drought legacy formation and influencing factors in soil microbiomes using DEMENTpy.
Neutral evolution modeling of microbes.
Targeted Probe Design Pipeline. Using mWGS genome bin clusters, prokka annotation predictions, and blast+ databases for generation, processing and filtering probe sequences.
Python simulation for visualizing the net geochemical outcomes of microbial metabolism - referred to here as "dead-end states." Poster presentation at Univ. Oregon Undergrad Symposium 2022.
Classification of stressful microbial growth conditions using gene fitness data and support vector machines
Javascript and D3 are used to create an interactive dashboard to explore a microbes on human subjects dataset.
Classification model predicting the type of microbe from provided features
Build an interactive dashboard to explore the Belly Button Biodiversity dataset, which catalogues the microbes that colonize human navels by using Plotly and D3.js libraries.
Using Plotly, JavaScript, d3, and Bootstrap, created an interactive dashboard to explore the Belly Button Biodiversity dataset, which catalogs the microbes that colonize human navels. The dataset reveals that a small handful of microbial species (also called operational taxonomic units, or OTUs, in the study) were present in more than 70% of people, while the rest were relatively rare.
Interactive dashboard to explore the Belly Button Biodiversity dataset using Plotly for Javascript.
This repository contains python code used to create figures in the accompanying manuscript.
Significance of non-microbial processes in organic matter decompositon in ecosystems across scales
A tool for phylogenetic comparison and analysis of microbe including gene's environmental association