Author

Helen T. Power

Commonwealth Scientific and Industrial Research OrganisationORCID 0000-0001-5771-2736Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Bioengineering· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Assay:proteomics· 1 Approach:variational autoencoder· 1

Frequent Co-Authors

Akbar K. VahidiiD· 1 shared Alessandro SerafiniiD· 1 shared Angelica Faith L. SuareziD· 1 shared Cheng Soon OngiD· 1 shared Daniel SteinbergiD· 1 shared Lorivie Fragata· 1 shared Pradeep M. NairiD· 1 shared Robert E. SpeightiD· 1 shared

Activity by Year

2025-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperBioengineering

Akbar K. VahidiORCID

Mutual co-authors in cluster

Author profile →

1 paper

Recent·Most cited

Generative Machine Learning and Microfluidics uHTS: An Efficient Partnership for Enzyme Engineering

Pradeep M. Nair, Daniel Steinberg, Tiago Resende, Angelica Faith L. Suarez, Helen T. Power, Cheng Soon Ong, Vijay Sairam, S CHENG, Lorivie Fragata, Alessandro Serafini, Victor H. Oh, Say Hwa Tan, Robert E. Speight, Akbar K. Vahidi

This paper combines microfluidic high-throughput screening with a generative model to engineer an enzyme with improved specificity, achieving higher product enrichment than traditional screening methods.

bioRxiv · Nov 2, 2025 · PreprintBioengineering