Samuel Miravet-Verde
@samuelmiver.bsky.social
HFSP postdoctoral fellow at @microbiomeresearch.bsky.social
Feedback and questions are very welcome!
October 1, 2026 at 4:02 PM
Feedback and questions are very welcome!
Special thanks to:
🔹All co-authors for their support and contributions
🔹All collaborators and OMDB users
🔹The @hfspo.bsky.social and @snsf.ch for supporting this research.
🔹All co-authors for their support and contributions
🔹All collaborators and OMDB users
🔹The @hfspo.bsky.social and @snsf.ch for supporting this research.
October 1, 2026 at 4:02 PM
Special thanks to:
🔹All co-authors for their support and contributions
🔹All collaborators and OMDB users
🔹The @hfspo.bsky.social and @snsf.ch for supporting this research.
🔹All co-authors for their support and contributions
🔹All collaborators and OMDB users
🔹The @hfspo.bsky.social and @snsf.ch for supporting this research.
🔹 Under warming, microbial richness declines faster than relative abundance
🔹 Grouping species into four thermal clusters revealed links to genome streamlining and protein thermostability
🔹 A microbe's preferred temperature can be predicted from the physicochemical properties of its proteins
🔹 Grouping species into four thermal clusters revealed links to genome streamlining and protein thermostability
🔹 A microbe's preferred temperature can be predicted from the physicochemical properties of its proteins
October 1, 2026 at 4:02 PM
🔹 Under warming, microbial richness declines faster than relative abundance
🔹 Grouping species into four thermal clusters revealed links to genome streamlining and protein thermostability
🔹 A microbe's preferred temperature can be predicted from the physicochemical properties of its proteins
🔹 Grouping species into four thermal clusters revealed links to genome streamlining and protein thermostability
🔹 A microbe's preferred temperature can be predicted from the physicochemical properties of its proteins
What we present:
🔹 OMDB brings together 274,282 genomes forming 31,058 species-level clusters, all searchable at lnkd.in/e-xT9MPP
🔹 Sea surface temperature can be predicted from microbial community composition, driven by closely related taxa occupying different thermal niches
🔹 OMDB brings together 274,282 genomes forming 31,058 species-level clusters, all searchable at lnkd.in/e-xT9MPP
🔹 Sea surface temperature can be predicted from microbial community composition, driven by closely related taxa occupying different thermal niches
October 1, 2026 at 4:02 PM
What we present:
🔹 OMDB brings together 274,282 genomes forming 31,058 species-level clusters, all searchable at lnkd.in/e-xT9MPP
🔹 Sea surface temperature can be predicted from microbial community composition, driven by closely related taxa occupying different thermal niches
🔹 OMDB brings together 274,282 genomes forming 31,058 species-level clusters, all searchable at lnkd.in/e-xT9MPP
🔹 Sea surface temperature can be predicted from microbial community composition, driven by closely related taxa occupying different thermal niches
This project brings together microbial ecology, microbiology and AI to tackle a question that matters globally: how will ocean microbes respond as the ocean warms? And for the same price, you get a fully accessible collection of marine microbial genomes :)
October 1, 2026 at 4:02 PM
This project brings together microbial ecology, microbiology and AI to tackle a question that matters globally: how will ocean microbes respond as the ocean warms? And for the same price, you get a fully accessible collection of marine microbial genomes :)