Nov 13, 2023

App Releases and Updates Q4 2023

Improved Metabolic Models with ModelSeed 2 Apps

Our metabolic modeling team released new MS2: Build Prokaryotic Metabolic Models and MS2: Improved Gapfill Metabolic Models apps for building and refining genome-scale models. These apps greatly improve energy metabolism reconstruction capabilities of the models and are capable of accurately predicting ATP yields across all microbes, outperforming current gold standard tools! This release includes a new template for Archaea model reconstruction for better metabolic models drafted from archaeal genomes. Metabolic models generated with ModelSeed2 have more accurate pathway annotations and biochemical representations for important subsystems including methanogenesis, iron redox reactions, sulfate reduction, and nitrogen cycling. We encourage our metabolic modeling users to run these new apps and explore the improved models for their own organisms of interest. Check out the preprint paper submitted demonstrating platform improvements with 5000 diverse microbial genomes.

Detect Viral Sequences with VirSorter2

The Microbes Persist Science Focus Area team has released the VirSorter2 app for identifying viral sequences in both genomic and metagenomic sequencing data. VirSorter2 leverages genome-informed database advances across a collection of customized automatic classifiers to accurately detect DNA and RNA viruses in your samples. VirSorter2’s modular design allows this app to expand to new types of viruses via the design of new classifiers to maintain maximal sensitivity and specificity. Learn more about the technical details of this tool at the VirSorter2 BitBucket page.

New Summarize GenomeSet App

Use the Summarize GenomeSet app to produce a useful report for all the Genomes in your GenomeSet. This report can include taxonomic classification for the genomes, counts of feature types, quality completeness and contamination measures from CheckM, and hits for some commonly relevant functional genes for environmental bioelement processing.

Pre-Print and Beta Testing for Genome Classifier Suite

A recently released pre-print paper introduces a new suite of apps in KBase that employ machine learning algorithms to generate classifiers to accurately predict phenotypes of unclassified bacteria. This paper includes two case studies and their corresponding Narratives for classifying both Bacterial Gram Staining and Bacterial Respiration using these apps. This suite of apps enables users to upload high-quality data to train classifiers, annotate genomes in the training set, build genome classifiers, and predict the phenotype of unclassified genomes. These apps are currently in Beta, so we encourage users to test these tools and report any issues to our Help Board.

SpeciesTreeBuilder Apps Bugfix

Many users submitted tickets to our KBase Help Board reporting an error when using our popular suite of apps for building phylogenetic trees. We’re happy to report that our support team identified and squashed the bug that generated the “App Startup Error: Unable to find object reference” error. We encourage all users to submit bugs, features requests, and technical questions to our Help Board for support.

About the Authors

Ben Allen
Ben Allen

Ben Allen coordinates outreach and user development activities to build the KBase user community while engaging in scientific collaborations to advance the use of the platform. His background in biochemistry and science education helps him develop protocols and training materials that provide depth while being accessible to a wide audience. Research interests include systems biology, microbial ecology, bioremediation studies, and biology education.