Author

Rose McNelly

John Innes CentreORCID 0000-0002-5313-7380Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Approach:benchmark study· 1 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:development & morphogenesis· 1 Approach:experimental assay· 1 Research Focus:genome assembly· 1

Frequent Co-Authors

David SeungiD· 2 shared Amy BriffaiD· 1 shared Ashleigh ListeriD· 1 shared Bernardo ClavijoiD· 1 shared Brendan F. FahyiD· 1 shared Cristóbal UauyiD· 1 shared Darren HeavensiD· 1 shared David BakeriD· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 16 mutual co-author links

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2 shared papersPlant Biology

David SeungORCID

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3 papers

Recent·Most cited

Targeting granule initiation and amyloplast structure to create giant starch granules in wheat

Rose McNelly, Lara Esch, Qi Yang Ngai, Katalin Pohan, Rhea Stringer, Brendan F. Fahy, Frederick J. Warren, David Seung

This paper creates giant starch granules in wheat by modifying amyloplast size and granule initiation, resulting in starch with altered physicochemical properties.

Science Advances · Jul 3, 2026Peer-reviewedPlant Biology

A curve fitting method for analysing starch granule size distributions in cereals

Rose McNelly, Amy Briffa, Georgia Yiasoumi, Cristóbal Uauy, Ryo Matsushima, David Seung

The paper develops a curve fitting method using Python to analyze starch granule size distributions in cereals, finding that mixed distributions best describe wheat and barley, while unimodal distributions apply to maize and rice.

Cereal Chemistry · May 1, 2025Peer-reviewedPlant Biology

Sequencing smart: De novo sequencing and assembly approaches for non-model mammals.

Graham Etherington, Darren Heavens, David Baker, Ashleigh Lister, Rose McNelly, Gonzalo Garcia, Bernardo Clavijo, Iain C. Macaulay, Wilfried Haerty, Federica Di Palma

The paper evaluates de novo genome assembly methods for a low-quality non-model mammal sample, finding that more data types do not always improve assembly quality.

GigaScience · May 1, 2020Peer-reviewedGenomics