The Microbe Directory v2.0: An Expanded Database of Ecological and Phenotypical Features of Microbes.
Sierra, M. A.; Bhattacharya, C.; Ryon, K.; Meierovich, S.; Shaaban, H.; Westfall, D.; Mohammad, R.; Kuchin, K.; Afshinnekoo, E.; Danko, D. C.; Mason, C. E.
Show abstract
The Microbe Directory (TMD) is a comprehensive database of annotations for microbial species collating features such as gram-stain, capsid-symmetry, resistance to antibiotics and more. This work presents a significant improvement to the original Microbe Directory (2018). This update adds 68,852 taxa, many new annotation features, an interface for the statistical analysis of microbiomes based on TMD features, and presents a portal for the broad community to add or correct entries. This update also adds curated lists of gene annotations which are useful for characterizing microbial genomes. Much of the new data in TMD is sourced from a set of databases and independent studies collating these data into a single quality controlled and curated source. This will allow researchers and clinicians to have easier access to microbial data and provide for the possibility of serendipitous discovery of otherwise unexpected trends.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Omnicrobe, an open-access database of microbial habitats and phenotypes using a comprehensive text mining and data fusion approach 95%
- GAMBIT (Genomic Approximation Method for Bacterial Identification and Tracking): A methodology to rapidly leverage whole genome sequencing of bacterial isolates for clinical identification 94%
- Genomic characterization of a diazotrophic microbiota associated with maize aerial root mucilage 94%
Similar papers in this journal
- rRNA Operon Improves Species-Level Classification of Bacteria and Microbial Community Analysis Compared to 16S rRNA 96%
- Library Preparation and Sequencing Platform Introduce Bias in Metagenomic-Based Characterizations of Microbiomes 94%
- TolRad: A model for predicting radiation tolerance using Pfam annotations identifies novel radiosensitive bacterial species from reference genomes and MAGs 93%
Similar papers in this journal
- Beyond Microbial Abundance: Metadata Integration Enhances Disease Prediction in Human Microbiome Studies 94%
- Gut Microbiome Dynamics and Predictive Value in Hospitalized COVID-19 Patients: A Comparative Analysis of Shallow and Deep Shotgun Sequencing 94%
- CANT-HYD: A curated database of phylogeny-derived Hidden Markov Models for annotation of marker genes involved in hydrocarbon degradation 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.