Nandha Kumar Balasubramaniam, Scott Penberthy, David Fenyo, Nina Viessmann, Christoph Russmann, Christoph H Borchers
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This data integration and analysis is aided through digital transformation, leading to better clinical outcomes. We also highlight the challenges and opportunities of Digitalomics, and provide examples of the application of Artificial Intelligence, cloud- and high-performance computing, and use of tensors for multiomic analysis workflows.</p><p><strong>Expert opinion: </strong>Biomarker discovery, aided by digital transformation, is having a significant impact on cancer, cardiovascular, infectious, immunological, and neurological diseases, among others. Data insights garnered from multiomic analyses, combined with patient meta data, aids patient stratification and targeted treatment across a broad spectrum of diseases. Digital transformation offers time and cost savings while leading to improved patent healthcare. Here, we highlight the impact of digital transformation on multiomics- based biomarker discovery with specific applications related to oncology.</p>","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":" ","pages":"337-344"},"PeriodicalIF":3.8000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Digitalomics - digital transformation leading to omics insights.\",\"authors\":\"Nandha Kumar Balasubramaniam, Scott Penberthy, David Fenyo, Nina Viessmann, Christoph Russmann, Christoph H Borchers\",\"doi\":\"10.1080/14789450.2024.2413107\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Biomarker discovery is increasingly moving from single omics to multiomics, as well as from multi-cell omics to single-cell omics. These transitions have increasingly adopted digital transformation technologies to accelerate the progression from data to insight. Here, we will discuss the concept of 'digitalomics' and how digital transformation directly impacts biomarker discovery. This will ultimately assist clinicians in personalized therapy and precision-medicine treatment decisions.</p><p><strong>Areas covered: </strong>Genotype-to-phenotype-based insight generation involves integrating large amounts of complex multiomic data. This data integration and analysis is aided through digital transformation, leading to better clinical outcomes. 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Digitalomics - digital transformation leading to omics insights.
Introduction: Biomarker discovery is increasingly moving from single omics to multiomics, as well as from multi-cell omics to single-cell omics. These transitions have increasingly adopted digital transformation technologies to accelerate the progression from data to insight. Here, we will discuss the concept of 'digitalomics' and how digital transformation directly impacts biomarker discovery. This will ultimately assist clinicians in personalized therapy and precision-medicine treatment decisions.
Areas covered: Genotype-to-phenotype-based insight generation involves integrating large amounts of complex multiomic data. This data integration and analysis is aided through digital transformation, leading to better clinical outcomes. We also highlight the challenges and opportunities of Digitalomics, and provide examples of the application of Artificial Intelligence, cloud- and high-performance computing, and use of tensors for multiomic analysis workflows.
Expert opinion: Biomarker discovery, aided by digital transformation, is having a significant impact on cancer, cardiovascular, infectious, immunological, and neurological diseases, among others. Data insights garnered from multiomic analyses, combined with patient meta data, aids patient stratification and targeted treatment across a broad spectrum of diseases. Digital transformation offers time and cost savings while leading to improved patent healthcare. Here, we highlight the impact of digital transformation on multiomics- based biomarker discovery with specific applications related to oncology.
期刊介绍:
Expert Review of Proteomics (ISSN 1478-9450) seeks to collect together technologies, methods and discoveries from the field of proteomics to advance scientific understanding of the many varied roles protein expression plays in human health and disease.
The journal coverage includes, but is not limited to, overviews of specific technological advances in the development of protein arrays, interaction maps, data archives and biological assays, performance of new technologies and prospects for future drug discovery.
The journal adopts the unique Expert Review article format, offering a complete overview of current thinking in a key technology area, research or clinical practice, augmented by the following sections:
Expert Opinion - a personal view on the most effective or promising strategies and a clear perspective of future prospects within a realistic timescale
Article highlights - an executive summary cutting to the author''s most critical points.