Graduate Defense: Sarah Roscoe
“Formal Concept Analysis Applications in Genomics: A Survey”
1:00 pm –
2:00 pm
Zoom
Graduate Defense: Sarah Roscoe
October 27
1 p.m.
Zoom
“Formal Concept Analysis Applications in Genomics: A Survey”
Abstract: Genomics, the study of genes and their functions, can provide valuable analysis as to how genes interact with their environment. One such way to measure the interaction is through gene expression data, which determines whether (and how much) a certain gene activates in a situation. Analyzing this data can be critical for predicting diseases or other biological reactions. One method used for analysis is Formal Concept Analysis (FCA), a computing technique based in partial orders that allows the user to examine the structural properties of binary data based on which subsets of the data set depend on each other. This thesis surveys, in breadth and depth, the current literature related to the use of FCA for gene expression data. This includes descriptions of current data management techniques specific to FCA, such as lattice reduction, discretization, and variations of FCA to account for different data types. Advantages and shortcomings of using FCA for genomic investigations, as well as the feasibility of using FCA for this application are addressed. Finally, several areas for future doctoral research are proposed.
Zoom: Link: https://unl.zoom.us/j/96529943129?pwd=eVU2b3FoRTJGWkhKc1JZUjJuZ1o2Zz09
October 27
1 p.m.
Zoom
“Formal Concept Analysis Applications in Genomics: A Survey”
Abstract: Genomics, the study of genes and their functions, can provide valuable analysis as to how genes interact with their environment. One such way to measure the interaction is through gene expression data, which determines whether (and how much) a certain gene activates in a situation. Analyzing this data can be critical for predicting diseases or other biological reactions. One method used for analysis is Formal Concept Analysis (FCA), a computing technique based in partial orders that allows the user to examine the structural properties of binary data based on which subsets of the data set depend on each other. This thesis surveys, in breadth and depth, the current literature related to the use of FCA for gene expression data. This includes descriptions of current data management techniques specific to FCA, such as lattice reduction, discretization, and variations of FCA to account for different data types. Advantages and shortcomings of using FCA for genomic investigations, as well as the feasibility of using FCA for this application are addressed. Finally, several areas for future doctoral research are proposed.
Zoom: Link: https://unl.zoom.us/j/96529943129?pwd=eVU2b3FoRTJGWkhKc1JZUjJuZ1o2Zz09