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Towards Unmanned Proteomics Data Generation: A Fully Automated Sample-to-Data System for Proteomic Experiments

Wang, D.; Chen, W.; Xie, L.; Xu, Y.; Huang, C.; Liu, Y.; Wang, X.; Huang, X.; Zhang, K.; Pan, M.; Wang, S.; Qin, B.; Yang, Y.; Yang, J.; Tang, L.; Tian, R.; He, F.

2025-06-04 biochemistry
10.1101/2025.06.02.656978 bioRxiv
Show abstract

The {pi}-HuB project requires proteomic measurements of millions of low-input samples that are challenging with current technology. Here, we introduce a pilot {pi}-HuB data factory that features a fully automated sample-to-data system to enable high-throughput digitization of human samples. Our platform, as a proof-of-concept towards unmanned proteomics, was demonstrated to show longitudinal robustness and applied for spatial proteomics and the profiling of plasma and cell lines, thereby serving as the workhorse to drive {pi}-HuB.

Published in Cell Discovery · training set

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20
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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.