BioParity.UFO / UAP research

2 papers for “Yuqi Tan”

Results

PaperS7568

SPACEc: a streamlined, interactive Python workflow for multiplexed image processing and analysis

Yuqi Tan, Tim N Kempchen, Martin Becker, Maximilian Haist, Dorien Feyaerts, Jiaqi Liu, Marieta Toma, Yang Xiao, Graham Su, Andrew J Rech, Michael Hölzel, Rong Fan, John W Hickey, Garry P Nolan. ebi.ac.uk. November 27, 2025.

SPACEc combines spatial proteomics processing, cell annotation and neighbourhood analysis. Nolan is credited with supervision. The supplied article, static supplement and reporting form were reviewed; peer-review correspondence is partly read. Reused tissues, expert labels and nested cell counts limit independent replication. Computational comparisons depend on dataset, platform, normalization and metric definitions; funding does not establish a UAP programme.

Complete supplied main and static supplement text read; peer review partial
PaperS7553

Strategies for Accurate Cell Type Identification in CODEX Multiplexed Imaging Data

John W. Hickey, Yuqi Tan, Garry P. Nolan, Yury Goltsev. ebi.ac.uk. August 13, 2021.

The study compares 20 cell-annotation pipelines using four healthy-colon tissue blocks from one donor. Agreement improves with broader labels, but both reference sets use the same images and one explicitly favors a pipeline being evaluated. The authors recommend checking expression patterns and image locations when assigning cell types. Marker counts, a worked F-score example and several caption or settings inconsistencies remain documented. These results do not establish universal clinical accuracy or a UAP connection.

Supplied text and scoped apparatus read

A curated public selection. Source review describes what was read; it does not establish that a claim is true. Our research approach