Author

Anna Quaglieri

The University of MelbourneORCID 0000-0002-3660-6990Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:experimental assay· 2 Research Focus:software / tool· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Organism:human· 1 Assay:metagenomics· 1 Assay:proteomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Aaron TriantafyllidisiD· 2 shared Andrew Ian WebbiD· 2 shared Giuseppe InfusiniiD· 2 shared Joseph BloomiD· 2 shared Paula Burton NgoviD· 2 shared Bradley Green· 1 shared Christoffer FlensburgiD· 1 shared Ian J. MajewskiiD· 1 shared

Activity by Year

2020-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 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 papersBioinformatics

Aaron TriantafyllidisORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintDec 12, 2022

Mass Dynamics 2.0: An improved modular web-based platform for accelerated proteomics insight generation and decision making

Anna Quaglieri, Joseph Bloom, Aaron Triantafyllidis…·Andrew Ian Webb

MD 2.0 is a web-based platform for quantitative proteomics data analysis that enables modular, customizable workflows to accelerate insight generation and collaboration.

8 citations

proteomicsexperimental assay

𝕏 PostBluesky

BioinformaticsJournal of Proteome ResearchPeer-reviewedOct 14, 2021

Mass Dynamics 1.0: A streamlined, web-based environment for analyzing, sharing and integrating Label-Free Data.

Joseph Bloom, Aaron Triantafyllidis, Anna Quaglieri…·Andrew Ian Webb

Mass Dynamics 1.0 provides a web-based platform for analyzing, visualizing, and sharing label-free proteomics data with automated processing and collaboration features.

16 citations

metagenomicsexperimental assay

𝕏 PostBluesky

BioinformaticsBMC BioinformaticsPeer-reviewedDec 1, 2020

Finding a suitable library size to call variants in RNA-seq

Anna Quaglieri, Christoffer Flensburg, Terence Paul Speed, Ian J. Majewski

The paper evaluates the impact of library size on variant detection sensitivity in RNA-seq, finding that 30M-40M fragments are needed to recover 90%-95% of variants in recurrently mutated myeloid genes.

8 citations

humanbulk RNA-seq

𝕏 PostBluesky