Neuro-Symbolic Process Anomaly Detection

arXiv:2603.26461v1 Announce Type: cross Abstract: Process anomaly detection is an important application of process mining for identifying deviations from the normal behavior of a process.

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  • Integrative Genomic, Transcriptomic, and Microbiome Profiles of Colon Cancer by Ancestry Provide Insights into Molecular Distinctions

Colorectal cancer (CRC) incidence, tumor biology, and clinical outcomes differ by patient ancestry, yet African ancestry (AFR) populations remain underrepresented in genomic and microbiome studies. Here, we comprehensively characterized genomic, transcriptomic and microbiome features of AFR and European ancestry (EUR) colon cancer patients residing in New York City and Long Island. While confirming known drivers from other large CRC studies, our AFR to EUR comparison of somatic variation also revealed a possible enrichment of functional KRAS variants in AFR tumors. Colon cancer genomes in patients in this study also exhibit distinct patterns of DNA copy number variation, correlating with consensus molecular subtypes. Fusobacterium nucleatum-positive tumors were enriched for co-occurring oral taxa, suggesting an organized oral microbial structure within the tumor microenvironment. Our findings highlight ancestry-associated differences in somatic mutation, copy number variation, and tumor microbiome composition, underscoring the urgent need to expand AFR representation in genomic studies to uncover population-specific determinants of CRC risk and to develop treatment strategies that reflect the full diversity of patients affected by this disease.

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