Institution
University of Memphis
Education•Memphis, Tennessee, United States•
About: University of Memphis is a education organization based out in Memphis, Tennessee, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 7710 authors who have published 20082 publications receiving 611618 citations. The organization is also known as: U of M.
Papers published on a yearly basis
Papers
More filters
TL;DR: The Mexican Drought Atlas (MXDA) as mentioned in this paper provides a new spatial perspective on the historical impacts of moisture extremes over Mexico during the past 600-years, including the Aztec Drought of One Rabbit in 1454, the drought of El Ano de Hambre in 1785-1786, and the drought that preceded the Mexican Revolution of 1909-1910.
186 citations
Washington University in St. Louis1, Brandeis University2, Northwestern University3, University of Pennsylvania4, Swiss Institute of Bioinformatics5, University of Lausanne6, Weizmann Institute of Science7, University of California, Irvine8, University of Central Florida9, Texas A&M University10, New York University11, University of Zurich12, Fundación Instituto Leloir13, University of Texas Health Science Center at Houston14, University of California, Davis15, Max Planck Society16, Dartmouth College17, Morehouse School of Medicine18, University of Surrey19, University of Kansas20, Harvard University21, University of Notre Dame22, University of Florida23, University of Michigan24, Cincinnati Children's Hospital Medical Center25, University of California, San Francisco26, Nestlé27, University of Amsterdam28, University of California, San Diego29, University of Texas Southwestern Medical Center30, Duke University31, Medical Research Council32, Charité33, Vanderbilt University34, Rensselaer Polytechnic Institute35, University of Washington36, Kyoto Prefectural University of Medicine37, Ohio State University38, Scripps Research Institute39, Amherst College40, University of Missouri41, Wuhan University42, University of Memphis43, University of Guelph44, Ludwig Maximilian University of Munich45, University of Edinburgh46, Donald Danforth Plant Science Center47, École Polytechnique Fédérale de Lausanne48, University of Geneva49, Yale University50, University of Seville51, University of Warwick52, Francis Crick Institute53, University College London54, University of North Carolina at Chapel Hill55, McGill University56, Soochow University (Suzhou)57, Leibniz Association58, University of Southampton59, Rockefeller University60
TL;DR: CircaInSilico is introduced, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms, and several unmet analytical needs, including applications to clinical medicine, are discussed and productive avenues to address them are suggested.
Abstract: Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding "big data" that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them.
186 citations
TL;DR: The regression-based d effect size did not improve the understanding of single-subject treatment outcomes when compared to nonregression effect sizes and Pearson product-moment correlations indicated that effect sizes differed in statistical relationships to one another.
Abstract: Controversy exists regarding appropriate methods for summarizing treatment outcomes for single-subject designs. Nonregression- and regression-based methods have been proposed to summarize the efficacy of single-subject interventions with proponents of both methods arguing for the superiority of their respective approaches. To compare findings for different single-subject effect sizes, 117 articles that targeted the reduction of problematic behaviors in 181 individuals diagnosed with autism were examined. Four effect sizes were calculated for each article: mean baseline reduction (MBLR), percentage of nonoverlapping data (PND), percentage of zero data (PZD), and one regression-based d statistic. Although each effect size indicated that behavioral treatment was effective, moderating variables were detected by the PZD effect size only. Pearson product-moment correlations indicated that effect sizes differed in statistical relationships to one another. In the present review, the regression-based d effect size...
186 citations
TL;DR: This article examined the relation between the Cattell-Horn-Carroll (CHC) theory of cognitive abilities and reading achievement during childhood and adolescence, and found that CHC theory was associated with reading achievement.
Abstract: This study examined the relations between the Cattell-Horn-Carroll (CHC) theory of cognitive abilities and reading achievement during childhood and adolescence. In a large, nationally representativ...
186 citations
TL;DR: This was a lively panel which dealt with the following main issues: cooperation, cooperation, and the centrality of the issue.
Abstract: Cooperation is often presented as one of the key concepts which differentiates multi-agent systems from other related disciplines such as distributed computing, object-oriented systems, and expert systems. However, it is a concept whose precise usage in agent-based systems is at best unclear and at worst highly inconsistent. Given the centrality of the issue, and the different ideological viewpoints on the subject, this was a lively panel which dealt with the following main issues.
185 citations
Authors
Showing all 7827 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| James F. Sallis | 169 | 825 | 144836 |
| Robert G. Webster | 158 | 843 | 90776 |
| Ching-Hon Pui | 145 | 805 | 72146 |
| James Whelan | 128 | 786 | 89180 |
| Tom Baranowski | 103 | 485 | 36327 |
| Peter C. Doherty | 101 | 516 | 40162 |
| Jian Chen | 96 | 1718 | 52917 |
| Arthur C. Graesser | 95 | 614 | 38549 |
| David Richards | 95 | 578 | 47107 |
| Jianhong Wu | 93 | 726 | 36427 |
| Richard W. Compans | 91 | 526 | 31576 |
| Shiriki K. Kumanyika | 90 | 349 | 44959 |
| Alexander J. Blake | 89 | 1133 | 35746 |
| Marek Czosnyka | 88 | 747 | 29117 |
| David M. Murray | 86 | 300 | 21500 |