04332nam 2201069z- 450 991040408960332120231214133627.03-03928-745-1(CKB)4100000011302242(oapen)https://directory.doabooks.org/handle/20.500.12854/60435(EXLCZ)99410000001130224220202102d2020 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierSystems Analytics and Integration of Big Omics DataMDPI - Multidisciplinary Digital Publishing Institute20201 electronic resource (202 p.)3-03928-744-3 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.precision medicine informaticsdrug sensitivitychromatin modificationcell linesbiocurationneurodegenerationmultivariate analysisartificial intelligenceepigeneticsmissing datasequencingclinical dataclass imbalanceintegrative analyticsalgorithm development for network integrationdeep phenotypenon-omics datafeature selectionGene OntologymiRNA-gene expression networksomics dataplot visualizationAlzheimer's diseasetissue classificationepidemiological dataproteomic analysisgenotypeRNA expressionindirect effectmulti-omicsdementiamultiomics integrationdata integrationphenomicsnetwork topology analysischallengestranscriptomeenrichment analysisregulatory genomicsscalabilityheterogeneous datasystemic lupus erythematosusdatabasemicrotubule-associated protein taudisease variantsgenomicsjoint modelingdistance correlationannotationphenotypedirect effectcurse of dimensionalitygene-environment interactionslogic forestmachine learningKEGG pathwaysmultivariate causal mediationamyloid-betabioinformatics pipelinessupport vector machinepharmacogenomicscandidate genestissue-specific expressed genescognitive impairmentcausal inferenceHardiman Garyauth1314898BOOK9910404089603321Systems Analytics and Integration of Big Omics Data3032113UNINA