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Systems biologybuilding a usefulmodel from multiplemarkers and profiles P. MayerBernd MayerGert Mayer2012 год

Systems biology building a useful model from multiple markers and profiles
review

Полный текстСтраница публикацииПубликация в OpenAlex
Аннотация: The pathophysiology of diabetic nephropathy (DN) is driven by a complex, multi-facetted interplay of numerous molecular processes (protective as well as damaging) and the balance between these, rather than the activity of a single pathway, determines clinical presentation and outcome. We present a concept for deriving a biomarker panel aimed to represent the relevant processes involved. Our approach rests on a hybrid gene/protein interaction network that holds ample information on molecular features (nodes) and their relations (edges), as a result providing a basic structure to navigate in molecular content and context being identified as relevant in DN. Extensive literature search on omics studies in DN provided a molecular feature list mapping to a total of 2175 unique protein-coding genes [13 from single nucleotide polymorphisms (SNPs), 12 as targets from relevant miRNAs, 1583 from transcriptomics, 5 from proteomics and 53 from metabolomics via linking to enzymes; 509 features were identified from multiple sources]. Two hundred and eighty-seven further human protein-coding genes associated with DN were derived from searching NCBI Pubmed (utilizing MeSH and gene-to-pubmed). Text mining of patents and clinical trial descriptors in the context of DN further added about 1 000 features. These data were used to label the respective nodes in the interaction network, as a result obtaining a DN-specific subgraph. Application of a segmentation algorithm on this subgraph allowed the identification of DN-specific molecular units, each characterizing a cluster of genes/proteins with a high internal functional association. We interpret each such unit as a functionally relevant molecular process contributing to the presentation of DN, and the total set of such units as a molecular model of DN. We propose that selecting appropriate biomarkers from each unit might allow the description of a patient's specific 'type' of DN, ultimately leading to a better stratification of patients regarding progression risk and optimal interventional approach.
Год издания: 2012
Авторы: P. Mayer, Bernd Mayer, Gert Mayer
Издательство: Oxford University Press
Источник: Nephrology Dialysis Transplantation
Ключевые слова: Bioinformatics and Genomic Networks, Genetic Associations and Epidemiology, Metabolomics and Mass Spectrometry Studies
Другие ссылки: Nephrology Dialysis Transplantation (PDF)
Nephrology Dialysis Transplantation (HTML)
PubMed (HTML)