Blood provides a rich and accessible source of clinical information, yet no centralized resource systematically documents which proteins are detectable across blood sample types, analytical workflows, and disease states. To address these needs, we developed the Human Blood Proteome (HuBP) database that links protein detectability, abundance, and reproducibility across analytical workflows, sample types, and disease contexts.Using data-independent acquisition, we profiled healthy plasma with complementary workflows, including direct analysis, high-abundance protein depletion, low-abundance protein enrichment, and extracellular vesicle enrichment and identified 9,965 proteins in total. HuBP enables users to query protein detectability across methods and provides standardized performance metrics and detailed standard operating procedures (SOPs) to support reproducibility and cross-laboratory implementation.To characterize disease-associated alterations, we further analyzed 140 pancreatic ductal adenocarcinoma (PDAC), 111 clear cell renal cell carcinoma (ccRCC), and 82 lung adenocarcinoma (LUAD) whole-blood samples, identifying 8,002, 8,006, and 8,009 proteins, respectively. Across these cancers, 8,021 proteins were detected, including 498 proteins absent in healthy controls, highlighting disease-specific blood proteomic signatures.In total, HuBP assembles 10,463 nonredundant blood proteins, representing the most comprehensive blood proteome resource to date. By providing an integrated and quantitative atlas across workflows, sample types, and disease contexts, HuBP offers a valuable platform for optimizing experimental designs in both large-scale blood proteomics studies and targeted analyses of disease-specific proteins, ultimately supporting the discovery of non-invasive biomarkers and the advancement of precision medicine.