Author

Rhys Newell

The University of Queensland

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 2 Microbiology· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:gene regulatory network inference· 2 Assay:ATAC-seq· 1 Research Focus:benchmarking· 1 Assay:ChIP-seq· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1

Frequent Co-Authors

Alexandra EssebieriD· 2 shared Brad BaldersoniD· 2 shared Mikael Bodén AiD· 2 shared Alena L. PribyliD· 1 shared Andrea Rabellino· 1 shared Annika KruegeriD· 1 shared Areej S. Alsheikh-HussainiD· 1 shared Ariane MoraiD· 1 shared

Activity by Year

2021-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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2 shared papersBioinformatics

Alexandra EssebierORCID

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3 papers

Recent·Most cited

A rational approach for the targeted discovery and characterisation of microbiome-derived therapeutics

Lutz Krause, Joel A. Boyd, Charlotte Vivian, Annika Krueger, Jeimy Johana Jimenez Loayza, Johanna K. Ljungberg, Joyce Zhou, Andrea Rabellino, Bozica Nyeverecz, Michael D. Nissen, Kaylyn D. Tousignant, Mareike Bongers, Martha M. Cooper, Donovan H. Parks, Areej S. Alsheikh-Hussain, , Páraic Ó Cuív

This paper identifies microbiome-derived therapeutics for IBD using a metagenome-guided approach, showing improved disease markers and safety in preclinical models.

bioRxiv · Oct 22, 2024 · PreprintMicrobiology

Engineering indel and substitution variants of diverse and ancient enzymes using Graphical Representation of Ancestral Sequence Predictions (GRASP)

Gabriel Foley, Ariane Mora, Connie M. Ross, Scott Bottoms, Leander Sützl, Marnie L. Lamprecht, Julian Zaugg, Alexandra Essebier, Brad Balderson, Rhys Newell, Raine E. S. Thomson, Boštjan Kobe, Ross Thomas Barnard, Luke W. Guddat, Gerhard Schenk, , Mikael Bodén A

The paper introduces GRASP, a method for ancestral sequence reconstruction that handles large datasets and indels, demonstrating its ability to generate biologically active enzyme ancestors.

PLoS Computational Biology · Oct 24, 2022Peer-reviewedBioinformatics

ChIP-R: Assembling reproducible sets of ChIP-seq and ATAC-seq peaks from multiple replicates

Rhys Newell, Richard Pienaar, Brad Balderson, Michael Piper, Alexandra Essebier, Mikael Bodén A

ChIP-R improves the reproducibility of ChIP-seq and ATAC-seq peak calls by statistically combining replicates, outperforming existing methods in recovering transcription factor binding sites.

Genomics · Apr 18, 2021Peer-reviewedBioinformatics