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Graduate schools around the United States are working to improve access to science, technology, engineering, and mathematics (STEM) in a manner that reflects local and national demographics. The admissions process has been the focus of examination, as it is a potential bottleneck for entry into STEM. Standardized tests are widely used as part of the decision-making process; thus, we examined the Graduate Record Examination (GRE) in two models of applicant review: metrics-based applicant review and holistic applicant review to understand whether it affected applicant demographics at The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences. We measured the relationship between GRE scores of doctoral applicants and admissions committee scores. Metrics-based review of applicants excluded twice the number of applicants who identified as a historically underrepresented minority compared with their peers. Efforts to implement holistic applicant review resulted in an unexpected result: the GRE could be used as a tool in a manner that did not reflect its reported bias. Applicant assessments in our holistic review process were independent of gender, racial, and citizenship status. Importantly, our recommendations provide a blueprint for institutions that want to implement a data-driven approach to assess applicants in a manner that uses the GRE as part of the review process.
Pubmed ID: 30735085
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THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.
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