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Full-Text Articles in Bioinformatics
Identification Of Genes Involved In Diauxic Shift Of Saccharomyces Cerevisiae Through Gateway Node Analysis., Emily Pachunka
Identification Of Genes Involved In Diauxic Shift Of Saccharomyces Cerevisiae Through Gateway Node Analysis., Emily Pachunka
UNO Student Research and Creative Activity Fair
The use of high-throughput assays, or experiments yielding large data sets, in biological research has become a standard practice in laboratories throughout the world. Because such investigations have the ability to produce high volume and comprehensive data sets, it is then important to develop methods that allow researchers to quickly pull meaningful information from an overwhelming amount of data. Network modeling has become a popular technique for visualizing and analyzing large biological data sets. A network is a basic graph with nodes and edges (i.e. social networks) that also integrates complex principles of graph theory for deeper analysis and pattern …
Identification Of Optimal Parameter Ranges In Building And Assessing Correlation Networks Built From Gene Expression., Qianran Li
UNO Student Research and Creative Activity Fair
In this project, I investigate and define the range of acceptable outputs of a gene expression correlation network model. Gene expression refers to the amount of product made by a gene under a given biological condition. A correlation network is a graphical model where the nodes represent genes in an organism and the edges represent the amount of correlation between genes, based on their expression. Correlation network modeling has been used in cellular and biomedical domains to identify functional relationships between genes. The network model in general is a wonderful tool for showcasing relationships, but often times they are misused …
A Network Mdoel To Investigate Robustness Of Gene Expressions, Naresh Pasupuleti
A Network Mdoel To Investigate Robustness Of Gene Expressions, Naresh Pasupuleti
UNO Student Research and Creative Activity Fair
Correlation networks are ideal to describe the relationship between the expression profiles of genes. Gene expression is a characteristic exhibited by a particular gene. Our body has thousands of genes; each of them expresses differently, and each one of them has a particular function associated with them. When genes corresponding to a particular part of the body becomes non-functional, i.e., not expressed, then the function corresponding to that part of the body does not happen, thereby causing impairment or mutations. Co-regulation is a method involved in clustering analysis to find genes that perform similar functions. We want to identify genes …
Correlation Networks: Causative Relationships From Gene Expression Data, Grogan W. Huff
Correlation Networks: Causative Relationships From Gene Expression Data, Grogan W. Huff
UNO Student Research and Creative Activity Fair
Genes that share expression conditions show a biological correlation, and no modern method of visualization displays these intricate co-expression patterns better than a graph. Structural observations about a co-expression graph can reveal the secrets of the biological system that it models, but experimentally validated co-expression graphs are pain-staking work to produce. Present day correlation network analysis shows potential for drawing conclusions from large volumes of biological systems data in an inexpensive and easy-to-produce way, however, work remains to confirm the appropriateness and scope of such methods for specific, scientific application. Toward this effort, we generated a Pearson correlation network from …