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Full-Text Articles in Physical Sciences and Mathematics
Estimation And Testing Of Gene Expression Heterosis, Tieming Ji, Peng Liu, Dan Nettleton
Estimation And Testing Of Gene Expression Heterosis, Tieming Ji, Peng Liu, Dan Nettleton
Dan Nettleton
Heterosis, also known as the hybrid vigor, occurs when the mean phenotype of hybrid offspring is superior to that of its two inbred parents. The heterosis phenomenon is extensively utilized in agriculture though the molecular basis is still unknown. In an effort to understand phenotypic heterosis at the molecular level, researchers have begun to compare expression levels of thousands of genes between parental inbred lines and their hybrid offspring to search for evidence of gene expression heterosis. Standard statistical approaches for separately analyzing expression data for each gene can produce biased and highly variable estimates and unreliable tests of heterosis. …
Predictions Generated From A Simulation Engine For Gene Expression Micro-Arrays For Use In Research Laboratories, Gopinath R. Mavankal, John Blevins, Dominique Edwards, Monnie Mcgee, Andrew Hardin
Predictions Generated From A Simulation Engine For Gene Expression Micro-Arrays For Use In Research Laboratories, Gopinath R. Mavankal, John Blevins, Dominique Edwards, Monnie Mcgee, Andrew Hardin
SMU Data Science Review
In this paper we introduce the technical components, the biology and data science involved in the use of microarray technology in biological and clinical research. We discuss how laborious experimental protocols involved in obtaining this data used in laboratories could benefit from using simulations of the data. We discuss the approach used in the simulation engine from [7]. We use this simulation engine to generate a prediction tool in Power BI, a Microsoft, business intelligence tool for analytics and data visualization [22]. This tool could be used in any laboratory using micro-arrays to improve experimental design by comparing how predicted …
Integrative Biomarker Identification And Classification Using High Throughput Assays, Pan Tong
Integrative Biomarker Identification And Classification Using High Throughput Assays, Pan Tong
Dissertations & Theses (Open Access)
It is well accepted that tumorigenesis is a multi-step procedure involving aberrant functioning of genes regulating cell proliferation, differentiation, apoptosis, genome stability, angiogenesis and motility. To obtain a full understanding of tumorigenesis, it is necessary to collect information on all aspects of cell activity. Recent advances in high throughput technologies allow biologists to generate massive amounts of data, more than might have been imagined decades ago. These advances have made it possible to launch comprehensive projects such as (TCGA) and (ICGC) which systematically characterize the molecular fingerprints of cancer cells using gene expression, methylation, copy number, microRNA and SNP microarrays …
Nonparametric Methods For Analyzing Replication Origins In Genomewide Data, Debashis Ghosh
Nonparametric Methods For Analyzing Replication Origins In Genomewide Data, Debashis Ghosh
The University of Michigan Department of Biostatistics Working Paper Series
Due to the advent of high-throughput genomic technology, it has become possible to globally monitor cellular activities on a genomewide basis. With these new methods, scientists can begin to address important biological questions. One such question involves the identification of replication origins, which are regions in chromosomes where DNA replication is initiated. In addition, one hypothesis regarding replication origins is that their locations are non-random throughout the genome. In this article, we develop methods for identification of and cluster inference regarding replication origins involving genomewide expression data. We compare several nonparametric regression methods for the identification of replication origin locations. …
A Statistical Method For Constructing Transcriptional Regulatory Networks Using Gene Expression And Sequence Data , Biao Xing, Mark J. Van Der Laan
A Statistical Method For Constructing Transcriptional Regulatory Networks Using Gene Expression And Sequence Data , Biao Xing, Mark J. Van Der Laan
U.C. Berkeley Division of Biostatistics Working Paper Series
Transcriptional regulation is one of the most important means of gene regulation. Uncovering transcriptional regulatory network helps us to understand the complex cellular process. In this paper, we describe a comprehensive statistical approach for constructing the transcriptional regulatory network using data of gene expression, promoter sequence, and transcription factor binding sites. Our simulation studies show that the overall and false positive error rates in the estimated transcriptional regulatory network are expected to be small if the systematic noise in the constructed feature matrix is small. Our analysis based on 658 microarray experiments on yeast gene expression programs and 46 transcription …