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Gsepd: A Bioconductor Package For Rna-Seq Gene Set Enrichment And Projection Display, Karl D. Stamm, Aoy Tomita-Mitchell, Serdar Bozdag
Gsepd: A Bioconductor Package For Rna-Seq Gene Set Enrichment And Projection Display, Karl D. Stamm, Aoy Tomita-Mitchell, Serdar Bozdag
Computer Science Faculty Research and Publications
Background: RNA-seq, wherein RNA transcripts expressed in a sample are sequenced and quantified, has become a widely used technique to study disease and development. With RNA-seq, transcription abundance can be measured, differential expression genes between groups and functional enrichment of those genes can be computed. However, biological insights from RNA-seq are often limited by computational analysis and the enormous volume of resulting data, preventing facile and meaningful review and interpretation of gene expression profiles. Particularly, in cases where the samples under study exhibit uncontrolled variation, deeper analysis of functional enrichment would be necessary to visualize samples’ gene expression activity under …
Exploring The Impact Of (Not) Changing Default Settings In Algorithmic Crime Mapping - A Case Study Of Milwaukee, Wisconsin, Md Romael Haque, Katy Weathington, Shion Guha
Exploring The Impact Of (Not) Changing Default Settings In Algorithmic Crime Mapping - A Case Study Of Milwaukee, Wisconsin, Md Romael Haque, Katy Weathington, Shion Guha
Computer Science Faculty Research and Publications
Policing decisions, allocations and outcomes are determined by mapping historical crime data geo-spatially using popular algorithms. In this extended abstract, we present early results from a mixed-methods study of the practices, policies, and perceptions of algorithmic crime mapping in the city of Milwaukee, Wisconsin. We investigate this differential by visualizing potential demographic biases from publicly available crime data over 12 years (2005-2016) and conducting semi-structured interviews of 19 city stakeholders and provide future research directions from this study.