Background: The Cell and cYTOkine CONcentrations DataBase (CYTOCON DB) is a manually curated digital repository detailing human baseline concentrations of cytokines and cells across healthy individuals and patients with diverse pathologies [1] . An important feature of the DB is its potential for predictive analytics. It allows users to estimate the distribution of baseline cell or cytokine concentrations across specific patient populations. Subsequently, these distributions can be compared, facilitating a comparative analysis across different diseases.
Methods: CYTOCON DB currently catalogues over 70,000 cytokine or cell concentrations, standardized to pM or kcells/L (when applicable) from multiple sources (papers, posters, etc.) [2] . For researchers and data analysts, this DB simplifies the preliminary stages of data analysis by offering datasets in a highly structured csv format, ensuring minimal time is expended on data preparation.
Results: In this case study, From the CYTOCON DB, IL9 serum distribution data was extracted for Healthy Control (HC), Colorectal Cancer (CRC), Chronic hepatitis B (HB) and Psoriasis (PS) (Figure 1A ). Density plot is created based on the number of patients from each source, assuming normal data distribution and disregarding negative values (Figure 1B). Analysis of density plot leads to following conclusions:
• For both HC and CRC, the distributions were unimodal, suggesting a single prominent peak or central value for both groups.
• The distribution of IL9 concentrations varied significantly across the four categories. The dispersion order was observed as: PS > HB > HC > CRC.
• When comparing the average concentrations, CRC and HC exhibited equivalent mean values for IL9.
Conclusion: The results shed light on the fluctuations and central patterns of IL9 concentrations across varying health conditions. CYTOCON DB emerges as a useful resource for the research community, fostering an in-depth understanding of cytokine and cell concentrations in health and disease.
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