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Integrated Omics Technology for Basic and Clinical Research
Published in Jyoti Ranjan Rout, Rout George Kerry, Abinash Dutta, Biotechnological Advances for Microbiology, Molecular Biology, and Nanotechnology, 2022
Kuldeep Giri, Vinod Singh Bisht, Sudipa Maity, Kiran Ambatipudi
Recently, advanced multiomics technology has contributed immensely in the disciplines of precision medicine, agricultural sciences, and food microbiology. Although integrative omics techniques are spreading rapidly in heterogeneous research areas, it lacks cost-effectiveness and requires specific bioinformatics and biostatics tools to integrate large datasets obtained at different levels. However, with careful planning and investment of time and human resources, the multiomics approach has the promising potential to unravel hidden features or trace molecular components in multiscale spatial organization. Thus a successful integrative omics approach calls for a prominent need to establish a global infrastructure for achieving high-output to translate basic research to clinical applications from bench to bedside. Due to the advantages of omics technologies with a wide/whole range of applications in different fields, this book chapter will discuss newer omics technologies with a particular emphasis on the transfer of application from bench-to-bedside. Furthermore, we will discuss a few examples of integrated omics approach together with bioinformatics and statistics in different fields of biology such as microbiology, biomedicine, pharmacology and their clinical validation.
Advance Methods
Published in Atsushi Kawaguchi, Multivariate Analysis for Neuroimaging Data, 2021
So far, we have considered the brain image data matrix X obtained from a single measuring device, but now we will extend it to have multiple brain image data per person. By analyzing multiple data sets that have been analyzed individually, disease characterization is performed simultaneously from various angles. In brain image analysis, this is known as multimodality and it evaluates brain pathology from the perspectives of brain morphology and function. In bioinformatics, it is called multi-omics and comprehensively analyzes biomolecular information such as genome, transcription, protein, metabolism, etc.
Applications of imaging genomics beyond oncology
Published in Ruijiang Li, Lei Xing, Sandy Napel, Daniel L. Rubin, Radiomics and Radiogenomics, 2019
Xiaohui Yao, Jingwen Yan, Li Shen
Multi-omics data analyses have been integrated in many cancer-related studies, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and so on. Compared with oncology studies, the availability of multi-omics data from brain tissues is far more limited in brain imaging genomic studies. It appears highly infeasible to collect brain region-specific omics data from the live subjects. Thus many strategies implemented in cancer imaging genomics cannot be directly applied to brain imaging genomics.
Incorporation of chemical and toxicological availability into metal mixture toxicity modeling: State of the art and future perspectives
Published in Critical Reviews in Environmental Science and Technology, 2022
Bing Gong, Hao Qiu, Ana Romero-Freire, Cornelis A. M. Van Gestel, Erkai He
Together, genomics, transcriptomics, and proteomics can provide information on processes at the cellular level, however, in order to further connect genotype to phenotype another layer of information is needed (Fell, 2001). Metabolomics can bridge this gap and provide quantitative information at the intracellular metabolic level which stands for the supreme level of functional components of cellular processes (Fiehn, 2002; Halama, 2014). The metabolites, defined as the metabolome, act as the cell’s supplements composed of small and low molecular weight compounds, which are necessary for growth, function and maintenance (Quanbeck et al. 2012). The goal of metabolomics is to systematically identify and quantify these compounds and to report the most relevant information to the phenotype under genetic and/or environmental changes in the biological system (Barupal et al., 2012; Fiehn, 2002; Mashego et al., 2007). Previously, the omics-based approach was often used alone in practical applications. Nowadays, the multiomics methodology has become a popular and revolutionary approach in comparison to single omics, which gathers information from multiple layers and allows to understand better the complex mechanisms of intoxication and defense that act in organisms.
Developments in enzyme and microalgae based biotechniques to remediate micropollutants from aqueous systems—A review
Published in Critical Reviews in Environmental Science and Technology, 2022
Zeba Usmani, Minaxi Sharma, Tiit Lukk, Yevgen Karpichev, Vijay Kumar Thakur, Vivek Kumar, Abdelmounaaim Allaoui, Abhishek Kumar Awasthi, Vijai Kumar Gupta
Further studies using multiomics strategies such as transcriptomics, genomics, proteomics, and metabolomics could reveal species and community-specific interactions. The genomics and metagenomics studies have resulted in identification of several genes in different microorganisms which leads to the detection of the enzymes associated with their biotransformation. The genomes of micropollutant degrading strains are quite significant in deploying other omics approaches (Bell et al., 2015; Techtmann & Hazen, 2016). Some of the microbial species that have been studied to remediate pharmaceutical pollutants include Pseudomonas putida XWY-1 (Zhu et al., 2019), Micrococcus sp. strain 2385 (Pathak et al., 2016) and Microbacterium esteraromaticum (Panneerselvan et al., 2018). These genomic studies could be used as the basis to better understand the characteristics of microbial enzymes and their application in bioremediation of micropollutants.