Search Results - "Stanhope, Stephen A"

MicroRNA 29c is down-regulated in nasopharyngeal carcinomas, up-regulating mRNAs encoding extracellular matrix proteins by Sengupta, Srikumar, den Boon, Johan A, Chen, I. How, Newton, Michael A, Stanhope, Stephen A, Cheng, Yu-Juen, Chen, Chien-Jen, Hildesheim, Allan, Sugden, Bill, Ahlquist, Paul

“…Using highly sensitive microarray-based procedures, we identified eight microRNAs (miRNAs) showing robust differential expression between 31…”
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The effects of home-based primary care on Medicare costs at Spectrum Health/Priority Health (Grand Rapids, MI, USA) from 2012-present: a matched cohort study by Stanhope, Stephen A, Cooley, Mary C, Ellington, Linda F, Gadbois, Gregory P, Richardson, Andrew L, Zeddes, Timothy C, LaBine, Jay P

“…In the United States, home-based primary care (HBPC) is increasingly proposed as a means of enabling frail elders to remain at home for as long as possible,…”
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Occupancy modeling, maximum contig size probabilities and designing metagenomics experiments by Stanhope, Stephen A

“…Mathematical aspects of coverage and gaps in genome assembly have received substantial attention by bioinformaticians. Typical problems under consideration…”
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Improved minimum cost and maximum power two stage genome-wide association study designs by Stanhope, Stephen A, Skol, Andrew D

“…In a two stage genome-wide association study (2S-GWAS), a sample of cases and controls is allocated into two groups, and genetic markers are analyzed…”
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Statistical use of argonaute expression and RISC assembly in microRNA target identification by Stanhope, Stephen A, Sengupta, Srikumar, den Boon, Johan, Ahlquist, Paul, Newton, Michael A

“…MicroRNAs (miRNAs) posttranscriptionally regulate targeted messenger RNAs (mRNAs) by inducing cleavage or otherwise repressing their translation. We address…”
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A noncoding antisense RNA in tie-1 locus regulates tie-1 function in vivo by Li, Keguo, Blum, Yannick, Verma, Anjali, Liu, Zhong, Pramanik, Kallal, Leigh, Noah R., Chun, Chang Z., Samant, Ganesh V., Zhao, Baofeng, Garnaas, Maija K., Horswill, Mark A., Stanhope, Stephen A., North, Paula E., Miao, Robert Q., Wilkinson, George A., Affolter, Markus, Ramchandran, Ramani

“…Recently, messenger RNAs in eukaryotes have shown to associate with antisense (AS) transcript partners that are often referred to as long noncoding RNAs…”
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GLOGS: a fast and powerful method for GWAS of binary traits with risk covariates in related populations by STANHOPE, Stephen A, ABNEY, Mark

“…Mixed model-based approaches to genome-wide association studies (GWAS) of binary traits in related individuals can account for non-genetic risk factors in an…”
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A novel method for biodosimetry by Megid, Wael Abdel, Ensenberger, Martin G, Halberg, Richard B, Stanhope, Stephen A, Kent-First, Marijo G, Prolla, Tomas A, Bacher, Jeff W

“…Accurate methods for measuring the biological effects of radiation are critical for estimating an individual's health risk from radiation exposure. We…”
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Statistical Use of Argonaute Expression and RISC Assembly in microRNA Target Identification: e1000516 by Stanhope, Stephen A, Sengupta, Srikumar, Boon, Johan den, Ahlquist, Paul, Newton, Michael A

“…MicroRNAs (miRNAs) posttranscriptionally regulate targeted messenger RNAs (mRNAs) by inducing cleavage or otherwise repressing their translation. We address…”
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Detecting m- and miRNA targeting relationships from observational microarray studies: Systems biology and statistical modeling by Stanhope, Stephen A

“…MicroRNAs (miRNAs) posttranscriptionally regulate targeted messenger RNAs (mRNAs) by inducing cleavage or otherwise repressing their translation. I address the…”
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Detecting m- and miRNA targeting relationships from observational microarray studies: Systems biology and statistical modeling by Stanhope, Stephen A

“…MicroRNAs (miRNAs) posttranscriptionally regulate targeted messenger RNAs (mRNAs) by inducing cleavage or otherwise repressing their translation. I address the…”
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(1+1) genetic algorithm fitness dynamics in a changing environment by Stanhope, S.A., Daida, J.M.

“…We analyze the fitness dynamics of a (1+1) mutation-only genetic algorithm (GA) operating on a family of simple time-dependent fitness functions. Resulting…”
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