Multiomic Sequencing

Extracted Attributes

• Applications

  Molecular profiling in primary tissues, estimation of biological age of organs and systems, understanding disease development, single-cell omics, spatial omics

• Primary Goal

  Analyze complex biological data to find novel associations, pinpoint biomarkers, build elaborate markers of disease and physiology, and understand geno-pheno-envirotype relationships

• Also known as

  Multi-omics, integrative omics, panomics, pan-omics

• Core Function

  Combines data from multiple 'omes' including genome, epigenome, transcriptome, proteome, metabolome, exposome, and microbiome

• ASCO Definition

  Refers to the interaction of all biological functions within a cell and with other body functions, combining data collected by targeted tests and global assays with other patient-specific information

• Economic Significance

  Identified as one of five key innovation platforms expected to drive significant productivity growth and economic change

• Relationship to Systems Biology

  Often foundational to systems biology approaches

• Expected Economic Impact (Cathie Wood)

  Trigger an unprecedented productivity boom, accelerating real GDP growth to over 7% and driving inflation to 0% or lower

Multiomics

Multiomics, multi-omics, integrative omics, "panomics" or "pan-omics" is a biological analysis approach in which the data consists of multiple "omes", such as the genome, epigenome, transcriptome, proteome, metabolome, exposome, and microbiome (i.e., a meta-genome and/or meta-transcriptome, depending upon how it is sequenced); in other words, the use of multiple omics technologies to study life in a concerted way. By combining these "omes", scientists can analyze complex biological big data to find novel associations between biological entities, pinpoint relevant biomarkers and build elaborate markers of disease and physiology. In doing so, multiomics integrates diverse omics data to find a coherently matching geno-pheno-envirotype relationship or association. The OmicTools service lists more than 99 pieces of software related to multiomic data analysis, as well as more than 99 databases on the topic. Systems biology approaches are often based upon the use of multiomic analysis data. The American Society of Clinical Oncology (ASCO) defines panomics as referring to "the interaction of all biological functions within a cell and with other body functions, combining data collected by targeted tests ... and global assays (such as genome sequencing) with other patient-specific information."

Web Search Results

• Multiomics | A holistic view of human health - Illumina

  Illumina offers comprehensive solutions across biological resolutions from broad bulk analysis to targeted single cells. Partek Flow makes the challenges of multiomics data analysis easy with a user-friendly interface, advanced statistical algorithms, and rich interactive visualizations for start‑to‑finish multiomics analyses. Illumina Connected Multiomics A comprehensive cloud-based genomics data platform for secure data management, infrastructure scalability, and bioinformatics workflow implementation. Multiomics Analysis with Partek Flow makes the challenges of multiomics data analysis easy with a user-friendly interface, advanced statistical algorithms, and rich interactive visualizations for start‑to‑finish multiomics analyses. Illumina Connected Multiomics is the first fully integrated multiomic and multimodal analysis software from Illumina, enabling seamless sample-to-insights workflows. Researchers can explore multiomic data, reveal deeper biological insights, and accelerate discoveries.

• Multiomic sequencing - Oxford Nanopore Technologies

  Multiomic studies utilise multiple omics methods — including genomics, transcriptomics, epigenomics, and proteomics — to gain a more comprehensive understanding

• Applications of multi‐omics analysis in human diseases - PMC

  For instance, the molecular profiling in primary tissues through multi‐omics integration to reveal molecular mechanisms of the progress of disease,1 estimation of the biological age of organs (liver, kidneys, etc.), and systems (immune and metabolic systems) by a multi‐omics approach for the assessment of aging status.2 Moreover, since the occurrence and development of diseases are not only affected by the latest gene mutations, but also by the environmental factor, genetic background, gene regulation, and so on, the research of multi‐omics from different levels has also laid the foundation for the development of systems biology technology, such as multi‐omics reveals systems biology in cardiovascular disease.3 Recently, single‐cell omics and spatial omics provide more detail information about the mechanisms of interactions between intracellular and intercellular molecules that control development, physiology, and pathology.4 The integration analysis of single‐cell transcriptomics and spatial transcriptomics has successfully resolved the logic underlying spatially organized immune‐malignant cell networks in human colorectal cancer.5 However, although many high‐throughput omics technologies have made good research progress in the medical field, there are few systematic introductions on how multi‐omics should be carried out in disease research, such as experimental design, data integration, analysis tools, and so on,6 especially for researchers who are just coming or preparing to conduct multi‐omics research.

• What is Multiomics? - News-Medical.Net

  Image 4: News-Medical Retrieved on August 23, 2025 from https://www.news-medical.net/life-sciences/What-is-Multiomics.aspx. https://www.news-medical.net/life-sciences/What-is-Multiomics.aspx. News-Medical, viewed 23 August 2025, https://www.news-medical.net/life-sciences/What-is-Multiomics.aspx. \* You can change your privacy preferences at any time by signing in to your profile at https://www.news-medical.net/azoprofile/account/ you can amend or select your newsletter preferences at https://www.news-medical.net/life-sciences/newsletters Image 17: How cohesin mechanics and nanotracker tech are redefining DNA research### Todd Bauman and Chris Povich Right shoring your supply chain in Life Sciences: Balancing cost, risk & resilience Discover expert insights on right shoring supply chains in medical and life sciences. Image 31: News-Medical News-Medical.Net provides this medical information service in accordance with these terms and conditions.

• Single-cell sequencing to multi-omics: technologies and applications

  Integrating data from multiple experiments requires the use of employ algorithms such as Seurat's canonical correlation analysis (CCA), mutual nearest neighbors