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How do we see medicine, health and disease? A basic set of rules and fundamental paradigms (including evidence!)
Published in Milos Jenicek, Foundations of Evidence-Based Medicine, 2019
Under the name of functional somatic disorders, medicine also deals with impaired biological functions without known organic or structural function, such as chronic fatigue syndrome, fibromyalgia or essential hypertension and others. They are subject of functional medicine.92 Bland93 defines more recently functional medicine as dealing and understanding of the impact of person's environment and lifestyle on their functional genomics/proteomics/metabolomics and their relationship to health or disease and considers functional medicine as an operating system for integrative medicine.
Gene Expression Profiling to Detect New Treatment Targets in Leukemia and Lymphoma: A Future Perspective
Published in Gertjan J. L. Kaspers, Bertrand Coiffier, Michael C. Heinrich, Elihu Estey, Innovative Leukemia and Lymphoma Therapy, 2019
Torsten Haferlach, Wolfgang Kern, Alexander Kohlmann
Both biology and medicine are undergoing a revolution that is based on the accelerating determination of DNA sequences, including the completion of whole genomes of a growing number of organisms (2). In parallel to the sequencing efforts, a wide range of technologies with tremendous potential has been achieved that can take advantage of the vast quantity of genetic information being now available. The field of functional genomics seeks to devise and apply these technologies, such as microarrays, to analyze the full complement of genes and proteins encoded by an organism to understand the functions of genes and proteins (3) (Fig. 1).
Functional Omics and Big Data Analysis in Microalgae
Published in Gokare A. Ravishankar, Ranga Rao Ambati, Handbook of Algal Technologies and Phytochemicals, 2019
Chetan Paliwal, Tonmoy Ghosh, Asha A. Nesamma, Pavan P. Jutur
Genomics is the study of the whole genome of an organism, including genes, recombinant cDNA, and expressed sequence tags (ESTs), to obtain a hypothesis of the cellular machinery (Rai et al. 2016). Initially, only information about sequencing and gene assembly can be deduced from the genomic data, but functional genomics can infer the function of a gene helping in understanding and regulation of the metabolic pathways (Jamers et al. 2009). The year 2005 marked the beginning of next-generation sequencing, which has led to an unprecedented rise in the amount of microalgal genome data (Lu et al. 2016). High throughput analysis and systematic sequencing methodology have enabled an understanding of the molecular machinery of microalgae. By the end of 2010, only 7 microalgal genomes existed, but as of now >30 microalgal genomes have been sequenced (Brodie et al. 2017; Rismani-Yazdi et al. 2011).
Polygenic and Network-based studies in risk identification and demystification of cancer
Published in Expert Review of Molecular Diagnostics, 2022
Christopher El Hadi, Georges Ayoub, Yara Bachir, Michèle Haykal, Nadine Jalkh, Hampig Raphael Kourie
Network analysis in cancer genomics has begun to be used in the last five years, with strong growth in the last two years [6]. The field of ‘functional genomics’ is concerned with the study of this complexity, and it is still in its infancy [7]. It integrates studies of molecular and cellular biology and deals with the structure, function, and regulation of groups of genes rather than individual genes, thus moving beyond classical molecular biology. Moreover, these molecular networks show remarkable conservation across species, both in their architecture and in their internal properties [8], suggesting the existence of a fundamental law governing them. Therefore, using gene networks as a unit of study instead of single genes could help understand, treat, and prevent all complex diseases, which is the ultimate goal of modern medicine.
Proteomics and plant biology: contributions to date and a look towards the next decade
Published in Expert Review of Proteomics, 2021
From a biological perspective, by using proteomics we aim to find out ‘how’, ‘where’, ‘when’, and ‘what for’ are the several hundred thousand individual protein species produced in a living organism. Namely, how they interact with one another and with other molecules to construct the cell building, and how they work in order to fit in with programmed growth and development, and to interact with their biotic and abiotic environment. As a functional genomics approach, proteomics will help to understand biological processes in the protein language, as to which gene products and translational and posttranslational mechanisms determine a specific phenotype. In addition, at the genomics interface, proteogenomics has emerged as a branch aimed at correcting gene sequences, identifying novel genes, splice variants, transcription and translation starting sites, exons and introns [4].
Novel deep learning-based survival prediction for oral cancer by analyzing tumor-infiltrating lymphocyte profiles through CIBERSORT
Published in OncoImmunology, 2021
Yeongjoo Kim, Ji Wan Kang, Junho Kang, Eun Jung Kwon, Mihyang Ha, Yoon Kyeong Kim, Hansong Lee, Je-Keun Rhee, Yun Hak Kim
The analysis of hidden patterns within gene expression data is a tremendous strategy to attaining an in-depth understanding of functional genomics. However, the complexity of biological networks and the large number of genes make data analysis very difficult; thus, some clustering algorithms help derive useful information by identifying patterns in gene expression data.27 Based on this idea, by clustering the ORCA CIBERSORT results, which accurately estimate immune composition, we aimed to achieve a more immune-specific and noise-free clustering efficiency. In addition, to examine whether the results could be validly analyzed, the immunological characteristics of each high- and low-risk group were determined by comparing the estimated immune cell fraction identified using CIBERSORT in each group.