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The Arabidopsis Leaf Quantitative Atlas: a cellular and subcellular mapping through unified data integration

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NIAID Data Ecosystem2026-05-01 收录
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https://zenodo.org/record/10410540
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Additional data accompanying Tolleter et. al. The Arabidopsis Leaf Quantitative Atlas: a cellular and subcellular mapping through unified data integration Quantitative Plant Biology. 2024. Quantitative analyses and models are required to connect a plant's cellular organization with its metabolism. However, quantitative data are often scattered over multiple studies, and finding such data and converting them into useful information is time consuming. Consequently, there is a need to centralize the available data and to highlight the remaining knowledge gaps. Here, we present a step-by-step approach to manually extract quantitative data from various information sources, and to unify the data format. First, data from Arabidopsis leaf were collated, checked for consistency and correctness, and curated by cross-checking sources. Second, quantitative data were combined by applying calculation rules. They were then integrated into a unique comprehensive, referenced, modifiable and reusable data compendium representing an Arabidopsis reference leaf. This atlas contains the metrics of the 15 cell types found in leaves at the cellular and subcellular levels. Table_S1_2023_12_12.xlsx: All supplementary data relating to the Arabidopsis Leaf Quantitative Atlas ChloroKB data export.ipynb: A jupyter notebook containing code to convert Quantitative_data_2023_12_13.xlsx (from http://umr5558-chlorokb.univ-lyon1.fr:8080/ChloroKB_Grails/static/images/csv/Quantitative_data.csv) into Table_S5_2023_12_13.xlsx. Variable_conversion_table.xlsx ,Localisation_conversion_table.xlsx, Localisation_conversion_table_isolated_organelles.xlsx: Conversion factors required by ChloroKB data export.ipynb for unit conversion.
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2023-12-22
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