Majorbio cloud: Novel end-to-end solution for proteomics research

Recent advances in high-resolution mass spectrometry and DIA acquisition have driven proteomics toward large-cohort, multi-omics and translational clinical research. However, existing analytical tools suffer from obvious drawbacks: standalone raw data pipelines lack statistical modules, statistical platforms feature siloed visualization functions, and integrated software cannot support personalized, scenario-specific analytical workflows. To resolve these bottlenecks, Majorbio Cloud launched its 2026 comprehensive proteomics upgrade, constructing a fully cloud-based, one-stop analytical system compatible with all mainstream quantification and data acquisition modalities. The platform covers conventional proteomics, phosphoproteomics, metaproteomics, and multi-omics integrative analysis.

Backed by 17 years of cumulative omics service experience, the platform serves over 200,000 academic and clinical researchers across more than 14,000 institutions worldwide and has completed over 700,000 omics analytical tasks. In 2025 alone, users published 5,753 papers with a combined total impact factor of 39,425.4, corresponding to an average IF of 7, which verifies its capacity to support high-quality research outputs. The platform incorporates 11 mature analytical workflows, including 9 single-omics pipelines and two multi-omics integration modules for proteome–transcriptome and proteome–transcriptome–metabolome combined analysis. It supports TMT/iTRAQ labeling, DDA-based label-free quantification, and sample-specific DIA workflows customized for clinical plasma and agricultural specimens, featuring tunable parameters, customizable publication-ready figures, and secure multi-user collaborative data management capabilities.

Three landmark upgraded workflows form the core competitiveness of the 2026 version. The optimized DIA pipeline is fully compatible with 3D/4D MS datasets and supports result imports from Spectronaut and DIA-NN. Fitted with automated threshold iteration and real-time QC alert systems, this pipeline contains two dedicated sub-workflows for mitochondrial disease investigation and plasma cohort tracking, alongside a full suite of machine learning algorithms (LASSO, LightGBM, SHAP) for biomarker screening and predictive model construction. The newly developed phosphoproteomics workflow encompasses five complete modules spanning raw data preprocessing to kinase–substrate enrichment analysis, enabling site-resolved functional mining of phosphorylation events. The innovative metaproteomics pipeline simultaneously discriminates host and microbial proteins and generates taxonomic diversity statistics, multi-level differential analyses, and taxon–protein–functional regulatory networks to unravel host-microbe crosstalk. Furthermore, six proprietary composite visualization templates and auto-generated standardized result interpretations drastically reduce manuscript preparation workload.

Moving forward, Majorbio Cloud will further advance multi-omics integration and expand AI deployments in drug target prediction and disease biomarker modeling. Ongoing constraints, such as slow data loading for ultra-large cohorts and species-specific analytical restrictions, are being mitigated through detailed user manuals and a dedicated systematic learning center. As an all-in-one proteomics analytical solution, Majorbio Cloud simplifies intricate bioinformatic workflows, lowers technical entry barriers, and accelerates translational proteomics discoveries spanning fundamental biology, clinical cohort studies, and microbiome research.