Results

Comparing polysaccharide decomposition between the type strains Gramella echinicola KMM 6050T (DSM 19838T) and Gramella portivictoriae UST040801-001T (DSM 23547T), and emended description of Gramella echinicola Nedashkovskaya et al. 2005 emend. Shahina et
Learn more
Natural Prodcast Episode 9: Roger Linington
… to try and create an open source database of all known microbial natural products. So if you think about natural … products science as a field, we have arguably been studying microbial natural products in an ordered way for perhaps 80 … identify every article which describes the discovery of a microbial natural product – DAN:  Right.  ROGER:  And that’s …
Learn more
Host population diversity as a driver of viral infection cycle in wild populations of green sulfur bacteria with long standing virus-host interactions
Learn more
Natural Prodcast Episode 22: Alison Narayan
Learn more
Dynamic root exudate chemistry and microbial substrate preferences drive patterns in rhizosphere microbial community assembly
Learn more
Metagenomic Sequencing of an In Vitro-Simulated Microbial Community
Learn more
High-resolution phylogenetic microbial community profiling
Learn more
A Comparison of Microbial Genome Web Portals
Learn more
The Integrated Microbial Genome Resource of Analysis
Learn more
Expanding Virophage Diversity
… available metagenomic datasets in JGI’s  Integrated Microbial Genomes & Microbiomes (IMG/M) data suite—which … Paez-Espino  discussed an early version of the paper at the 2018 Viral EcoGenomics & Applications (VEGA) Symposium. The …
Learn more
Engagement Webinar: Harnessing JGI’s Metabolomics Capabilities
… available through the  Community Science Program (CSP) . This includes mass spectrometry-based measurements of … . Q:  Are applicants outside of JGI eligible to apply for CSP?  I am at NIST. A: The JGI User Programs are designed to … Q:  Any advice on normalizing metabolomic data from a whole microbial community, without having cell counts or …
Learn more
Crysten Blaby-Haas
AT, Blaby-Haas CE. (2024) Machine learning sheds light on microbial dark proteins. Nature Rev Micro 22, 63. Davidi L, …
Learn more