Community-led, integrated, reproducible multi-omics with anvi’o

By A. M. Eren, E. Kiefl, Alon Shaiber, Iva A. Veseli, Samuel E. Miller, M. S. Schechter, Isaac Fink, Jessica N. Pan, Mahmoud Yousef, Emily C. Fogarty and 25 more. Nature Microbiology, 2020

838 citations recorded by the source corpus.

Big data abound in microbiology, but the workflows designed to enable researchers to interpret data can constrain the biological questions that can be asked. Five years after anvi’o was first published, this community-led multi-omics platform is maturing into an open software ecosystem that reduces constraints in ‘omics data analyses.

Subfields: Genetics, Insect Science, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/9c0f91242d07bfbaa92c1cdfd9571f7cdfaad44c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Genetics

1. Maria Sorokina
2. Nadine Ziemert

In Molecular Biology

1. Kai Blin
2. Philippe Schwaller
3. Marnix H. Medema
4. Nadine Ziemert
5. Maria Sorokina
6. Marwin H. S. Segler
7. Djork-Arné Clevert
8. Marcy J. Balunas

Citations in the corpus

• Artificial Intelligence For Natural Product Drug Discovery (2023, methodology): “Fortunately, early tools such as NPLinker 190 , GraphOmics 200 and anvi’o 201 are starting to overcome some of these challenges.”