Author

Michael J. Wise

The University of Western AustraliaORCID 0000-0001-6559-4303Unclaimed ORCID profile · follow to get notified of new preprints

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Michael J. Wise1 paper

Biology Disciplines

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Bioinformatics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:gene regulatory network inference· 1 Assay:protein sequence· 1 Approach:statistical model· 1

Frequent Co-Authors

Amitava DattaiD· 1 shared David H. MathewsiD· 1 shared Irina N. BessarabiD· 1 shared Krithika ArumugamiD· 1 shared Marcell SzikszaiiD· 1 shared Max WardiD· 1 shared Rohan B. H. WilliamsiD· 1 shared

Activity by Year

2022-2023 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 9 mutual co-author links

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1 shared paperBioinformatics

Amitava DattaORCID

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2 papers

Recent·Most cited

GenomicsbioRxivPreprintOct 11, 2023

Exploring the genetic architecture of ecophysiological traits in microbial ecology using statistical analysis of the properties of protein sequences: application to the glycogen accumulating organism (GAO) phenotype

Rohan B. H. Williams, Irina N. Bessarab, Michael J. Wise, Krithika Arumugam

The paper analyzes protein sequence properties of the glgB gene to identify structural genetic variation associated with a glycogen accumulating phenotype in microbes.

DOI 10.1101/2023.10.11.561824

protein sequencestatistical model

𝕏 PostBluesky

BioinformaticsBioinformaticsPeer-reviewedJun 24, 2022

Deep learning models for RNA secondary structure prediction (probably) do not generalise across families

Marcell Szikszai, Michael J. Wise, Amitava Datta…·David H. Mathews

The paper shows that deep learning models for RNA secondary structure prediction do not generalize across families, using rigorous cross-validation methods.

86 citationstop 2%

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