2015
A genome-wide approach to link genotype to clinical outcome by utilizing next generation sequencing and gene chip data of 6,697 breast cancer patients
Pongor L, Kormos M, Hatzis C, Pusztai L, Szabó A, Győrffy B. A genome-wide approach to link genotype to clinical outcome by utilizing next generation sequencing and gene chip data of 6,697 breast cancer patients. Genome Medicine 2015, 7: 104. PMID: 26474971, PMCID: PMC4609150, DOI: 10.1186/s13073-015-0228-1.Peer-Reviewed Original ResearchConceptsRNA-seq dataNext-generation sequencingBreast cancer patientsTranscriptomic fingerprintGenome-wide approachesGeneration sequencingClinical outcomesCancer patientsHuman gene mutationsTumor suppressor geneGene chip dataSuch genesRNA-seqGene mutationsLarge breast cancer cohortGene expressionChip dataSuppressor geneBreast cancer cohortGenesMicroarray dataMutationsSomatic mutationsClinical characteristicsCox regression
2009
Building Networks with Microarray Data
Broom BM, Rinsurongkawong W, Pusztai L, Do KA. Building Networks with Microarray Data. Methods In Molecular Biology 2009, 620: 315-343. PMID: 20652510, DOI: 10.1007/978-1-60761-580-4_10.Peer-Reviewed Original ResearchConceptsDetailed differential equation modelsDifferential equation modelAvailable breast cancer dataMathematical detailsNetwork modelBayesian network modelCo-expression network analysisMicroarray dataGene expression data setsFalse interactionsBayesian networkGene interaction networksData setsNumber of samplesPlausible networksRobust networkBreast cancer dataExpression data setsMicroarray data setsGene clusterGene shavingGene interactionsInteraction networksPreliminary clusteringSubsequent biological experiments