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(Precedente collocazione CAR 147.4500502678)$fB $h20220810$i20220810 977 $a 01$a BN 996 $aCommentario breve al codice di procedura civile$9648480 997 $aUNISANNIO LEADER 04530nam 2201153z- 450 001 9910404089603321 005 20210212 010 $a3-03928-745-1 035 $a(CKB)4100000011302242 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/60435 035 $a(oapen)doab60435 035 $a(oapen)60435 035 $a(EXLCZ)994100000011302242 100 $a20202102d2020 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSystems Analytics and Integration of Big Omics Data 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2020 215 $a1 online resource (202 p.) 311 08$a3-03928-744-3 330 $aA "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. 606 $aMedicine$2bicssc 606 $aMedicine and Nursing$2bicssc 610 $aalgorithm development for network integration 610 $aAlzheimer's disease 610 $aamyloid-beta 610 $aannotation 610 $aartificial intelligence 610 $abiocuration 610 $abioinformatics pipelines 610 $acandidate genes 610 $acausal inference 610 $acell lines 610 $achallenges 610 $achromatin modification 610 $aclass imbalance 610 $aclinical data 610 $acognitive impairment 610 $acurse of dimensionality 610 $adata integration 610 $adatabase 610 $adeep phenotype 610 $adementia 610 $adirect effect 610 $adisease variants 610 $adistance correlation 610 $adrug sensitivity 610 $aenrichment analysis 610 $aepidemiological data 610 $aepigenetics 610 $afeature selection 610 $aGene Ontology 610 $agene-environment interactions 610 $agenomics 610 $agenotype 610 $aheterogeneous data 610 $aindirect effect 610 $aintegrative analytics 610 $ajoint modeling 610 $aKEGG pathways 610 $alogic forest 610 $amachine learning 610 $amicrotubule-associated protein tau 610 $amiRNA-gene expression networks 610 $amissing data 610 $amulti-omics 610 $amultiomics integration 610 $amultivariate analysis 610 $amultivariate causal mediation 610 $an/a 610 $anetwork topology analysis 610 $aneurodegeneration 610 $anon-omics data 610 $aomics data 610 $apharmacogenomics 610 $aphenomics 610 $aphenotype 610 $aplot visualization 610 $aprecision medicine informatics 610 $aproteomic analysis 610 $aregulatory genomics 610 $aRNA expression 610 $ascalability 610 $asequencing 610 $asupport vector machine 610 $asystemic lupus erythematosus 610 $atissue classification 610 $atissue-specific expressed genes 610 $atranscriptome 615 7$aMedicine 615 7$aMedicine and Nursing 700 $aHardiman$b Gary$4auth$01314898 906 $aBOOK 912 $a9910404089603321 996 $aSystems Analytics and Integration of Big Omics Data$93032113 997 $aUNINA