Profile Likelihood Biclustering

Biclustering, the process of simultaneously clustering the rows and columns of a data matrix, is a popular and effective tool for finding structure in a high-dimensional dataset. Many biclustering procedures appear to work well in practice, but most do not have associated consistency guarantees. To address this shortcoming, we propose a new biclustering procedure based on profile likelihood. The procedure applies to a broad range of data modalities, including binary, count, and continuous observations. We prove that the procedure recovers the true row and column classes when the dimensions of the data matrix tend to infinity, even if the functional form of the data distribution is misspecified. The procedure requires computing a combinatorial search, which can be expensive in practice. Rather than performing this search directly, we propose a new heuristic optimization procedure based on the Kernighan-Lin heuristic, which has nice computational properties and performs well in simulations. We demonstrate our procedure with applications to congressional voting records, and microarray analysis.Comment: 40 pages, 11 figures; R package in development at https://github.com/patperry/biclustp

Writing Their Faith into the Law of the Land: Jehovah\u27s Witnesses, the Supreme Court and the Battle for the Meaning of the Free Exercise Clause, 1939-1945

The article traces the development of free exercise jurisprudence through the battles of Jehovah\u27s Witnesses before the Court, and the battles on the Court between Justices Black, Douglas and Frankfurter to establish their constitutional faiths as the law of the land during a brief period in the early 1940\u27s when these issues came before the Court in a flurry of decisions, then disappeared

Science Panel Discussion presentation: You Want to Do What? Managing and Distributing Identifying Data without Running Afoul of Your Research Sponsor, Your IRB, or Your Office of Counsel

Patrick Flynn, PhD, is Professor, Department of Computer Science and Engineering, University of Notre Dame. He discussed the data management for his university\u27s biometric data sampling projects, including human subjects issues, data distribution, and infrastructure

Myeloid-derived suppressor cell, arginase-1, IL-17 and cl-CD95L: an explosive cocktail in lupus?

International audienceComment on: Wu H, Zhen Y, Ma Z, et al. Arginase-1-dependent promotion of TH17 differentiation and disease progression by MDSCs in systemic lupus erythematosus. Sci Transl Med 2016;8:331ra40

Movement demands and perceived wellness associated with preseason training camp in NCAA Division I college football players

The aims of this study were to examine the movement demands of preseason practice in National Collegiate Athletic Association Division I college football players using portable global positioning system (GPS) technology and to assess perceived wellness associated with preseason practice to determine whether GPS-derived variables from the preceding day influence perceived wellness the following day. Twenty-nine players were monitored using GPS receivers (Catapult Innovations, Melbourne, Australia) during 20 preseason practices. Individual observations (n = 550) were divided into offensive and defensive position groups. Movement variables including low-, medium-, high-intensity, and sprint distance, player load, and acceleration and deceleration distance were assessed. Perceived wellness ratings (n = 469) were examined using a questionnaire which assessed fatigue, soreness, sleep quality, sleep quantity, stress, and mood. A 1-way analysis of variance for positional movement demands and multilevel regressions for wellness measures were used, followed by post hoc testing to evaluate the relational significance between categorical outcomes of perceived wellness scores and movement variables. Results demonstrated significantly (p ≤ 0.05) greater total, high-intensity, and sprint distance, along with greater acceleration and deceleration distances for the defensive back and wide receiver position groups compared with their respective offensive and defensive counterparts. Significant (p ≤ 0.05) differences in movement variables were demonstrated for individuals who responded more or less favorably on each of the 6 factors of perceived wellness. Data from this study provide novel quantification of the position-specific physical demands and perceived wellness associated with college football preseason practice. Results support the use of position-specific training and individual monitoring of college football players