TY - BOOK ID - 46008 TI - Systems Analytics and Integration of Big Omics Data AU - Hardiman, Gary PY - 2020 SN - 9783039287444 / 9783039287451 DB - DOAB KW - tissue-specific expressed genes KW - transcriptome KW - tissue classification KW - support vector machine KW - feature selection KW - bioinformatics pipelines KW - algorithm development for network integration KW - miRNA–gene expression networks KW - multiomics integration KW - network topology analysis KW - candidate genes KW - gene–environment interactions KW - logic forest KW - systemic lupus erythematosus KW - Gene Ontology KW - KEGG pathways KW - enrichment analysis KW - proteomic analysis KW - plot visualization KW - Alzheimer’s disease KW - dementia KW - cognitive impairment KW - neurodegeneration KW - Gene Ontology KW - annotation KW - biocuration KW - amyloid-beta KW - microtubule-associated protein tau KW - artificial intelligence KW - genotype KW - phenotype KW - deep phenotype KW - data integration KW - genomics KW - phenomics KW - precision medicine informatics KW - epigenetics KW - chromatin modification KW - sequencing KW - regulatory genomics KW - disease variants KW - machine learning KW - multi-omics KW - data integration KW - curse of dimensionality KW - heterogeneous data KW - missing data KW - class imbalance KW - scalability KW - genomics KW - pharmacogenomics KW - cell lines KW - database KW - drug sensitivity KW - data integration KW - omics data KW - genomics KW - RNA expression KW - non-omics data KW - clinical data KW - epidemiological data KW - challenges KW - integrative analytics KW - joint modeling KW - multivariate analysis KW - multivariate causal mediation KW - distance correlation KW - direct effect KW - indirect effect KW - causal inference KW - n/a UR - https://www.doabooks.org/doab?func=search&query=rid:46008 AB - A “genotype"" is essentially an organism's full hereditary information which is obtained from its parents. A ""phenotype"" is an organism's actual observed physical and behavioral properties. These may include traits such as morphology, size, height, eye color, metabolism, etc. One of the pressing challenges in computational and systems biology is genotype-to-phenotype prediction. This is challenging given the amount of data generated by modern Omics technologies. This “Big Data” is so large and complex that traditional data processing applications are not up to the task. Challenges arise in collection, analysis, mining, sharing, transfer, visualization, archiving, and integration of these data. In this Special Issue, there is a focus on the systems-level analysis of Omics data, recent developments in gene ontology annotation, and advances in biological pathways and network biology. The integration of Omics data with clinical and biomedical data using machine learning is explored. This Special Issue covers new methodologies in the context of gene–environment interactions, tissue-specific gene expression, and how external factors or host genetics impact the microbiome. ER -