Author

Matthew Hill

University of CambridgePrimary ORCID profile (0000-0001-6776-8709 · 8 papers)Unclaimed ORCID profile · follow to get notified of new preprints

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

Same name, identified by ORCID

Matthew HilliD8 papers · Cardiff University

Biology Disciplines

Click to filter author papers

Biochemistry· 1 Bioengineering· 1 Genomics· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:deep learning· 2 Research Focus:protein design· 2 Assay:protein sequence· 2 Assay:ATAC-seq· 1 Organism:C. elegans· 1 Research Focus:cell type annotation· 1 Research Focus:drug response / drug discovery· 1 Organism:E. coli· 1

Frequent Co-Authors

Frances H. ArnoldiD· 2 shared Jason YangiD· 2 shared Sukhvinder KauriD· 2 shared Alex Appert· 1 shared Amin Tavakoli· 1 shared Animashree AnandkumariD· 1 shared Arvind RamanathaniD· 1 shared Francesco Nicola CarelliiD· 1 shared

Activity by Year

2024-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 25 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

2 shared papersBiochemistry

Frances H. ArnoldORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Sequence-Based Generative AI-Guided Design of Versatile Tryptophan Synthases

Théophile Lambert, Amin Tavakoli, Gautham Dharuman, Jason Yang, Vignesh C. Bhethanabotla, Sukhvinder Kaur, Matthew Hill, Arvind Ramanathan, Animashree Anandkumar, Frances H. Arnold

This paper uses a generative AI model to design novel tryptophan synthase variants with enhanced catalytic activity and substrate promiscuity, outperforming natural and optimized versions.

bioRxiv · Aug 30, 2025 · PreprintBiochemistry

Active Learning-Assisted Directed Evolution

Jason Yang, Ravi G. Lal, James C. Bowden, Raul Astudillo, Mikhail A. Hameedi, Sukhvinder Kaur, Matthew Hill, Yisong Yue, Frances H. Arnold

This paper introduces ALDE, a machine learning-assisted directed evolution method that improves protein engineering outcomes by efficiently exploring epistatic mutation spaces.

Nature Communications · Jan 16, 2025Peer-reviewedBioengineering

A lineage-resolved multimodal single-cell atlas reveals the genomic dynamics of early C. elegans development

Servaas N. van der Burght, Francesco Nicola Carelli, Alex Appert, Yan Dong, Matthew Hill, Toby Buttress, Richard Butler, Julie Ahringer

This study constructs a lineage-resolved single-cell multimodal atlas of early C. elegans development, revealing genomic dynamics and zygotic genome activation mechanisms.

bioRxiv · Dec 2, 2024 · PreprintGenomics