scispace - formally typeset
Search or ask a question
Institution

University of Utah

EducationSalt Lake City, Utah, United States
About: University of Utah is a education organization based out in Salt Lake City, Utah, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 52894 authors who have published 124076 publications receiving 5265834 citations. The organization is also known as: The U & The University of Utah.


Papers
More filters
Posted Content
TL;DR: In this paper, the authors propose a test for disparate impact based on analyzing the information leakage of the protected class from the other data attributes, and present empirical evidence supporting the effectiveness of their test and their approach for masking bias and preserving relevant information in the data.
Abstract: What does it mean for an algorithm to be biased? In U.S. law, unintentional bias is encoded via disparate impact, which occurs when a selection process has widely different outcomes for different groups, even as it appears to be neutral. This legal determination hinges on a definition of a protected class (ethnicity, gender, religious practice) and an explicit description of the process. When the process is implemented using computers, determining disparate impact (and hence bias) is harder. It might not be possible to disclose the process. In addition, even if the process is open, it might be hard to elucidate in a legal setting how the algorithm makes its decisions. Instead of requiring access to the algorithm, we propose making inferences based on the data the algorithm uses. We make four contributions to this problem. First, we link the legal notion of disparate impact to a measure of classification accuracy that while known, has received relatively little attention. Second, we propose a test for disparate impact based on analyzing the information leakage of the protected class from the other data attributes. Third, we describe methods by which data might be made unbiased. Finally, we present empirical evidence supporting the effectiveness of our test for disparate impact and our approach for both masking bias and preserving relevant information in the data. Interestingly, our approach resembles some actual selection practices that have recently received legal scrutiny.

679 citations

Journal ArticleDOI
01 Aug 1996-Genetics
TL;DR: A model is presented whereby the formation of gene clusters in bacteria is mediated by transfer of DNA within and among taxa, and predicts a mosaic structure of modern genomes in which ancestral chromosomal material is interspersed with novel, horizontally transferred operons providing peripheral metabolic functions.
Abstract: A model is presented whereby the formation of gene clusters in bacteria is mediated by transfer of DNA within and among taxa. Bacterial operons are typically composed of genes whose products contribute to a single function. If this function is subject to weak selection or to long periods with no selection, the contributing genes may accumulate mutations and be lost by genetic drift. From a cell's perspective, once several genes are lost, the function can be restored only if all missing genes were acquired simultaneously by lateral transfer. The probability of transfer of multiple genes increases when genes are physically proximate. From a gene's perspective, horizontal transfer provides a way to escape evolutionary loss by allowing colonization of organisms lacking the encoded functions. Since organisms bearing clustered genes are more likely to act as successful donors, clustered genes would spread among bacterial genomes. The physical proximity of genes may be considered a selfish property of the operon since it affects the probability of successful horizontal transfer but may provide no physiological benefit to the host. This process predicts a mosaic structure of modern genomes in which ancestral chromosomal material is interspersed with novel, horizontally transferred operons providing peripheral metabolic functions.

679 citations

Journal ArticleDOI
TL;DR: Key features of the histologic phenotypes of breast cancers in carriers of mutant BRCA1 and BRCa2 genes are identified and this information may improve the classification of breast cancer in individuals with a family history of the disease and may ultimately aid in the clinical management of patients.
Abstract: BACKGROUND: We have previously demonstrated that breast cancers associated with inherited BRCA1 and BRCA2 gene mutations differ from each other in their histopathologic appearances and that each of these types differs from breast cancers in patients unselected for family history (i.e., sporadic cancers). We have now conducted a more detailed examination of cytologic and architectural features of these tumors. METHODS: Specimens of tumor tissue (5-microm-thick sections) were examined independently by two pathologists, who were unaware of the case or control subject status, for the presence of cell mitosis, lymphocytic infiltration, continuous pushing margins, and solid sheets of cancer cells; cell nuclei, cell nucleoli, cell necrosis, and cell borders were also evaluated. The resulting data were combined with previously available information on tumor type and tumor grade and further evaluated by multifactorial analysis. All statistical tests are two-sided. RESULTS: Cancers associated with BRCA1 mutations exhibited higher mitotic counts (P = .001), a greater proportion of the tumor with a continuous pushing margin (P<.0001), and more lymphocytic infiltration (P = .002) than sporadic (i.e., control) cancers. Cancers associated with BRCA2 mutations exhibited a higher score for tubule formation (fewer tubules) (P = .0002), a higher proportion of the tumor perimeter with a continuous pushing margin (P<.0001), and a lower mitotic count (P = .003) than control cancers. CONCLUSIONS: Our study has identified key features of the histologic phenotypes of breast cancers in carriers of mutant BRCA1 and BRCA2 genes. This information may improve the classification of breast cancers in individuals with a family history of the disease and may ultimately aid in the clinical management of patients.

679 citations

Journal ArticleDOI
TL;DR: It is proposed that mitochondrial fission in yeast is a multi-step process, and that membrane-bound Fis1p is required for the proper assembly, membrane distribution, and function of Dnm1p-containing complexes during fission.
Abstract: Yeast Dnm1p is a soluble, dynamin-related GTPase that assembles on the outer mitochondrial membrane at sites where organelle division occurs. Although these Dnm1p-containing complexes are thought to trigger constriction and fission, little is known about their composition and assembly, and molecules required for their membrane recruitment have not been isolated. Using a genetic approach, we identified two new genes in the fission pathway, FIS1 and FIS2. FIS1 encodes a novel, outer mitochondrial membrane protein with its amino terminus exposed to the cytoplasm. Fis1p is the first integral membrane protein shown to participate in a eukaryotic membrane fission event. In a related study (Tieu, Q., and J. Nunnari. 2000. J. Cell Biol. 151:353–365), it was shown that the FIS2 gene product (called Mdv1p) colocalizes with Dnm1p on mitochondria. Genetic and morphological evidence indicate that Fis1p, but not Mdv1p, function is required for the proper assembly and distribution of Dnm1p-containing fission complexes on mitochondrial tubules. We propose that mitochondrial fission in yeast is a multi-step process, and that membrane-bound Fis1p is required for the proper assembly, membrane distribution, and function of Dnm1p-containing complexes during fission.

679 citations

Journal ArticleDOI
TL;DR: Motivational Interviewing was robust across moderators such as delivery location and patient characteristics, and appears efficacious when delivered in brief consultations and could be used for a wide range of behavioral issues in health care.

679 citations


Authors

Showing all 53431 results

NameH-indexPapersCitations
Bert Vogelstein247757332094
George M. Whitesides2401739269833
Hongjie Dai197570182579
Robert M. Califf1961561167961
Frank E. Speizer193636135891
Yusuke Nakamura1792076160313
David L. Kaplan1771944146082
Marc G. Caron17367499802
George M. Church172900120514
Steven P. Gygi172704129173
Lily Yeh Jan16246773655
Tobin J. Marks1591621111604
David W. Bates1591239116698
Alfred L. Goldberg15647488296
Charles M. Perou156573202951
Network Information
Related Institutions (5)
University of Washington
305.5K papers, 17.7M citations

97% related

University of California, San Diego
204.5K papers, 12.3M citations

96% related

Stanford University
320.3K papers, 21.8M citations

96% related

Columbia University
224K papers, 12.8M citations

96% related

University of Michigan
342.3K papers, 17.6M citations

95% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023203
2022769
20217,363
20207,015
20196,309
20185,651