Architecting data-driven microbial electrochemistry from scratch

Waheed Miran; Gaku Imamura; Akihiro Okamoto

doi:10.1016/j.patter.2022.100637

Architecting data-driven microbial electrochemistry from scratch

Waheed Miran^*
, Gaku Imamura^*
, Akihiro Okamoto^*

^*Kontaktforfatter

National University of Sciences and Technology Pakistan
National Institute for Materials Science
Osaka University
Hokkaido University

Publikation: Bidrag til tidsskrift › Kommentar/debat › Forskning › peer review

Abstract

Waheed, a former postdoctoral researcher; Gaku, a senior researcher; and Akihiro, a group leader in Okamoto lab succeeded high-quality database construction and discovered a highly stable microbial power-generation mechanism. They talk about how wet electrochemists jumped into the data science field and the potential of data science to explore complex bacteria/electrode interactions.

Originalsprog	Engelsk
Artikelnummer	100637
Tidsskrift	Patterns
Vol/bind	3
Udgave nummer	11
DOI	https://doi.org/10.1016/j.patter.2022.100637
Status	Udgivet - 11. nov. 2022
Udgivet eksternt	Ja

Bibliografisk note

Publisher Copyright:
© 2022 The Author(s)

Dokumenter og links

10.1016/j.patter.2022.100637

SDU link

Tjek adgangen til materialet i Syddansk Universitetsbiblioteks søgemaskine

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Link to publication in Scopus

Citationsformater

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N2 - Waheed, a former postdoctoral researcher; Gaku, a senior researcher; and Akihiro, a group leader in Okamoto lab succeeded high-quality database construction and discovered a highly stable microbial power-generation mechanism. They talk about how wet electrochemists jumped into the data science field and the potential of data science to explore complex bacteria/electrode interactions.

AB - Waheed, a former postdoctoral researcher; Gaku, a senior researcher; and Akihiro, a group leader in Okamoto lab succeeded high-quality database construction and discovered a highly stable microbial power-generation mechanism. They talk about how wet electrochemists jumped into the data science field and the potential of data science to explore complex bacteria/electrode interactions.

UR - https://www.scopus.com/pages/publications/85141785044

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DO - 10.1016/j.patter.2022.100637

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Architecting data-driven microbial electrochemistry from scratch

Abstract

Bibliografisk note

Dokumenter og links

SDU link

Andre filer og links

Fingeraftryk

Citationsformater