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2006

Statistics and Probability

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Articles 1 - 30 of 58

Full-Text Articles in Life Sciences

Wavelet-Based Functional Mixed Models To Characterize Population Heterogeneity In Accelerometer Profiles: A Case Study. , Jeffrey S. Morris, Cassandra Arroyo, Brent A. Coull, Louise M. Ryan, Steven L. Gortmaker Dec 2006

Wavelet-Based Functional Mixed Models To Characterize Population Heterogeneity In Accelerometer Profiles: A Case Study. , Jeffrey S. Morris, Cassandra Arroyo, Brent A. Coull, Louise M. Ryan, Steven L. Gortmaker

Jeffrey S. Morris

We present a case study illustrating the challenges of analyzing accelerometer data taken from a sample of children participating in an intervention study designed to increase physical activity. An accelerometer is a small device worn on the hip that records the minute-by-minute activity levels of the child throughout the day for each day it is worn. The resulting data are irregular functions characterized by many peaks representing short bursts of intense activity. We model these data using the wavelet-based functional mixed model. This approach incorporates multiple fixed effects and random effect functions of arbitrary form, the estimates of which are ...


Alternative Probeset Definitions For Combining Microarray Data Across Studies Using Different Versions Of Affymetrix Oligonucleotide Arrays, Jeffrey S. Morris, Chunlei Wu, Kevin R. Coombes, Keith A. Baggerly, Jing Wang, Li Zhang Dec 2006

Alternative Probeset Definitions For Combining Microarray Data Across Studies Using Different Versions Of Affymetrix Oligonucleotide Arrays, Jeffrey S. Morris, Chunlei Wu, Kevin R. Coombes, Keith A. Baggerly, Jing Wang, Li Zhang

Jeffrey S. Morris

Many published microarray studies have small to moderate sample sizes, and thus have low statistical power to detect significant relationships between gene expression levels and outcomes of interest. By pooling data across multiple studies, however, we can gain power, enabling us to detect new relationships. This type of pooling is complicated by the fact that gene expression measurements from different microarray platforms are not directly comparable. In this chapter, we discuss two methods for combining information across different versions of Affymetrix oligonucleotide arrays. Each involves a new approach for combining probes on the array into probesets. The first approach involves ...


Semiparametric Regression Of Multi-Dimensional Genetic Pathway Data: Least Squares Kernel Machines And Linear Mixed Models, Dawei Liu, Xihong Lin, Debashis Ghosh Nov 2006

Semiparametric Regression Of Multi-Dimensional Genetic Pathway Data: Least Squares Kernel Machines And Linear Mixed Models, Dawei Liu, Xihong Lin, Debashis Ghosh

Harvard University Biostatistics Working Paper Series

No abstract provided.


Multiple Testing With An Empirical Alternative Hypothesis, James E. Signorovitch Nov 2006

Multiple Testing With An Empirical Alternative Hypothesis, James E. Signorovitch

Harvard University Biostatistics Working Paper Series

An optimal multiple testing procedure is identified for linear hypotheses under the general linear model, maximizing the expected number of false null hypotheses rejected at any significance level. The optimal procedure depends on the unknown data-generating distribution, but can be consistently estimated. Drawing information together across many hypotheses, the estimated optimal procedure provides an empirical alternative hypothesis by adapting to underlying patterns of departure from the null. Proposed multiple testing procedures based on the empirical alternative are evaluated through simulations and an application to gene expression microarray data. Compared to a standard multiple testing procedure, it is not unusual for ...


Prepms: Tof Ms Data Graphical Preprocessing Tool, Yuliya V. Karpievitch, Elizabeth G. Hill, Adam J. Smolka, Jeffrey S. Morris, Kevin R. Coombes, Keith A. Baggerly, Jonas S. Almeida Nov 2006

Prepms: Tof Ms Data Graphical Preprocessing Tool, Yuliya V. Karpievitch, Elizabeth G. Hill, Adam J. Smolka, Jeffrey S. Morris, Kevin R. Coombes, Keith A. Baggerly, Jonas S. Almeida

Jeffrey S. Morris

We introduce a simple-to-use graphical tool that enables researchers to easily prepare time-of-flight mass spectrometry data for analysis. For ease of use, the graphical executable provides default parameter settings experimentally determined to work well in most situations. These values can be changed by the user if desired. PrepMS is a stand-alone application made freely available (open source), and is under the General Public License (GPL). Its graphical user interface, default parameter settings, and display plots allow PrepMS to be used effectively for data preprocessing, peak detection, and visual data quality assessment.


Exploration Of Distributional Models For A Novel Intensity-Dependent Normalization , Nicola Lama, Patrizia Boracchi, Elia Mario Biganzoli Oct 2006

Exploration Of Distributional Models For A Novel Intensity-Dependent Normalization , Nicola Lama, Patrizia Boracchi, Elia Mario Biganzoli

COBRA Preprint Series

Currently used gene intensity-dependent normalization methods, based on regression smoothing techniques, usually approach the two problems of location bias detrending and data re-scaling without taking into account the censoring characteristic of certain gene expressions produced by experiment measurement constraints or by previous normalization steps. Moreover, the bias vs variance balance control of normalization procedures is not often discussed but left to the user's experience. Here an approximate maximum likelihood procedure to fit a model smoothing the dependences of log-fold gene expression differences on average gene intensities is presented. Central tendency and scaling factor were modeled by means of B-splines ...


New Polymorphic Microsatellites In Glossina Pallidipes (Diptera: Glossinidae) And Their Cross-Amplification In Other Tsetse Fly Taxa, J. O. Ouma, J. G. Marquez, E. S. Krafsur Oct 2006

New Polymorphic Microsatellites In Glossina Pallidipes (Diptera: Glossinidae) And Their Cross-Amplification In Other Tsetse Fly Taxa, J. O. Ouma, J. G. Marquez, E. S. Krafsur

Entomology Publications

We report the development and characterization of three new microsatellite markers in the tsetse fly, Glossina pallidipes (Diptera: Glossinidae). Fifty-eight alleles were scored in 192 individuals representing six natural populations. Allelic diversity ranged from 9 to 28 alleles per locus (mean 19.3 ± 5.5). Averaged across loci, observed heterozygosity was 0.581 ± 0.209, and expected heterozygosity was 0.619 ± 0.181. Cross-species amplifications of the G. pallidipesloci in other tsetse fly taxa are reported.


Stage-Specific Suppression Of Basal Defense Discriminates Barley Plants Containing Fast- And Delayed-Acting Mla Powdery Mildew Resistance Alleles, Rico A. Caldo, Dan Nettleton, Jiqing Peng, Roger P. Wise Sep 2006

Stage-Specific Suppression Of Basal Defense Discriminates Barley Plants Containing Fast- And Delayed-Acting Mla Powdery Mildew Resistance Alleles, Rico A. Caldo, Dan Nettleton, Jiqing Peng, Roger P. Wise

Statistics Publications

Nonspecific recognition of pathogen-derived general elicitors triggers the first line of plant basal defense, which in turn, preconditions the host towards resistance or susceptibility. To elucidate how basal defense responses influence the onset of Mla (mildew resistance locus a)-specified resistance, we performed a meta-analysis of GeneChip mRNA expression for 155 basal defense-related genes of barley (Hordeum vulgare) challenged with Blumeria graminis f. sp. hordei, the causal agent of powdery mildew disease. In plants containing the fast-acting Mla1, Mla6, or Mla13 alleles, transcripts hyper-accumulated from 0 to 16 h after inoculation (hai) in both compatible and incompatible interactions. Suppression of ...


A Discussion Of Statistical Methods For Design And Analysis Of Microarray Experiments For Plant Scientists, Dan Nettleton Sep 2006

A Discussion Of Statistical Methods For Design And Analysis Of Microarray Experiments For Plant Scientists, Dan Nettleton

Statistics Publications

There is much excitement among biologists and statisticians regarding new high-dimension data sets that have arisen from the application of microarray technology. In statistics, there has been a flurry of activity surrounding the development of new methods for the analysis of such data, and biologists are eager to extract as much information as possible from their substantial investments in microarray experiments. In this article, I offer statistical advice for plant biologists engaged in microarray research. My views are those of a statistician who has been working with scientists on the design and analysis of microarray experiments for the past 5 ...


Estimating The Number Of True Null Hypotheses From A Histogram Of P Values, Dan Nettleton, J.T. Gene Hwang, Rico A. Caldo, Roger P. Wise Sep 2006

Estimating The Number Of True Null Hypotheses From A Histogram Of P Values, Dan Nettleton, J.T. Gene Hwang, Rico A. Caldo, Roger P. Wise

Statistics Publications

In an earlier article, an intuitively appealing method for estimating the number of true null hypotheses in a multiple test situation was proposed. That article presented an iterative algorithm that relies on a histogram of observed p values to obtain the estimator. We characterize the limit of that iterative algorithm and show that the estimator can be computed directly without iteration. We compare the performance of the histogram-based estimator with other procedures for estimating the number of true null hypotheses from a collection of observed p values and find that the histogram-based estimator performs well in settings similar to those ...


Structural Inference In Transition Measurement Error Models For Longitudinal Data, Wenqin Pan, Xihong Lin, Donglin Zeng Aug 2006

Structural Inference In Transition Measurement Error Models For Longitudinal Data, Wenqin Pan, Xihong Lin, Donglin Zeng

Harvard University Biostatistics Working Paper Series

No abstract provided.


Estimation In Semiparametric Transition Measurement Error Models For Longitudinal Data, Wenqin Pan, Donglin Zeng, Xihong Lin Aug 2006

Estimation In Semiparametric Transition Measurement Error Models For Longitudinal Data, Wenqin Pan, Donglin Zeng, Xihong Lin

Harvard University Biostatistics Working Paper Series

No abstract provided.


Nonparametric Regression Using Local Kernel Estimating Equations For Correlated Failure Time Data, Zhangsheng Yu, Xihong Lin Aug 2006

Nonparametric Regression Using Local Kernel Estimating Equations For Correlated Failure Time Data, Zhangsheng Yu, Xihong Lin

Harvard University Biostatistics Working Paper Series

No abstract provided.


Causal Inference In Hybrid Intervention Trials Involving Treatment Choice, Qi Long, Rod Little, Xihong Lin Aug 2006

Causal Inference In Hybrid Intervention Trials Involving Treatment Choice, Qi Long, Rod Little, Xihong Lin

Harvard University Biostatistics Working Paper Series

No abstract provided.


A Comparison Of Methods For Estimating The Causal Effect Of A Treatment In Randomized Clinical Trials Subject To Noncompliance, Rod Little, Qi Long, Xihong Lin Aug 2006

A Comparison Of Methods For Estimating The Causal Effect Of A Treatment In Randomized Clinical Trials Subject To Noncompliance, Rod Little, Qi Long, Xihong Lin

Harvard University Biostatistics Working Paper Series

No abstract provided.


Scanning Microarrays At Multiple Intensities Enhances Discovery Of Differentially Expressed Genes, David S. Skibbe, Xiujuan Wang, Xuefeng Zhao, Lisa A. Borsuk, Dan Nettleton, Patrick S. Schnable Aug 2006

Scanning Microarrays At Multiple Intensities Enhances Discovery Of Differentially Expressed Genes, David S. Skibbe, Xiujuan Wang, Xuefeng Zhao, Lisa A. Borsuk, Dan Nettleton, Patrick S. Schnable

Statistics Publications

Motivation: Scanning parameters are often overlooked when optimizing microarray experiments. A scanning approach that extends the dynamic data range by acquiring multiple scans of different intensities has been developed.

Results: Data from each of three scan intensities (low, medium, high) were analyzed separately using multiple scan and linear regression approaches to identify and compare the sets of genes that exhibit statistically significant differential expression. In the multiple scan approach only one-third of the differentially expressed genes were shared among the three intensities, and each scan intensity identified unique sets of differentially expressed genes. The set of differentially expressed genes from ...


Gene Expression Profiling In Salmonella Choleraesuis-Infected Porcine Lung Using A Long Oligonucleotide Microarray, Shu-Hong Zhao, Daniel Kuhar, Joan K. Lunney, Harry Dawson, Catherine Guidry, Jolita J. Uthe, Shawn M. D. Bearson, Justin Recknor, Dan Nettleton, Christopher K. Tuggle Jul 2006

Gene Expression Profiling In Salmonella Choleraesuis-Infected Porcine Lung Using A Long Oligonucleotide Microarray, Shu-Hong Zhao, Daniel Kuhar, Joan K. Lunney, Harry Dawson, Catherine Guidry, Jolita J. Uthe, Shawn M. D. Bearson, Justin Recknor, Dan Nettleton, Christopher K. Tuggle

Statistics Publications

Understanding the transcriptional response to pathogenic bacterial infection within food animals is of fundamental and applied interest. To determine the transcriptional response to Salmonella enterica serovar Choleraesuis (SC) infection, a 13,297-oligonucleotide swine array was used to analyze RNA from control, 24-h postinoculation (hpi), and 48-hpi porcine lung tissue from pigs infected with SC. In total, 57 genes showed differential expression (p < 0.001; false discovery rate = 12%). Quantitative real-time PCR (qRT-PCR) of 61 genes was used to confirm the microarray results and to identify pathways responding to infection. Of the 33 genes identified by microarray analysis as differentially expressed, 23 were confirmed by qRT-PCR results. A novel finding was that two transglutaminase family genes (TGM1 and TGM3) showed dramatic increases in expression postinoculation; combined with several other apoptotic genes, they indicated the induction of apoptotic pathways during SC infection. A predominant T helper 1-type immune response occurred during infection, with interferon γ ...


Some Statistical Issues In Microarray Gene Expression Data, Matthew S. Mayo, Byron J. Gajewski, Jeffrey S. Morris Jun 2006

Some Statistical Issues In Microarray Gene Expression Data, Matthew S. Mayo, Byron J. Gajewski, Jeffrey S. Morris

Jeffrey S. Morris

In this paper we discuss some of the statistical issues that should be considered when conducting experiments involving microarray gene expression data. We discuss statistical issues related to preprocessing the data as well as the analysis of the data. Analysis of the data is discussed in three contexts: class comparison, class prediction and class discovery. We also review the methods used in two studies that are using microarray gene expression to assess the effect of exposure to radiofrequency (RF) fields on gene expression. Our intent is to provide a guide for radiation researchers when conducting studies involving microarray gene expression ...


Bounded Search For De Novo Identification Of Degenerate Cis-Regulatory Elements, Jonathan M. Carlson, Arijit Chakravarty, Radhika S. Khetani, Robert H. Gross May 2006

Bounded Search For De Novo Identification Of Degenerate Cis-Regulatory Elements, Jonathan M. Carlson, Arijit Chakravarty, Radhika S. Khetani, Robert H. Gross

Open Dartmouth: Faculty Open Access Scholarship

The identification of statistically overrepresented sequences in the upstream regions of coregulated genes should theoretically permit the identification of potential cis-regulatory elements. However, in practice many cis-regulatory elements are highly degenerate, precluding the use of an exhaustive word-counting strategy for their identification. While numerous methods exist for inferring base distributions using a position weight matrix, recent studies suggest that the independence assumptions inherent in the model, as well as the inability to reach a global optimum, limit this approach.


Evaluating Linear And Nonlinear Models For The Respiration Rate Of Four Breeds Of Heat Stressed Feedlot Heifers, Q. Huang, A. M. Parkhurst, T. M. Brown-Brandl, R. A. Eigenberg, J. A. Nienaber Apr 2006

Evaluating Linear And Nonlinear Models For The Respiration Rate Of Four Breeds Of Heat Stressed Feedlot Heifers, Q. Huang, A. M. Parkhurst, T. M. Brown-Brandl, R. A. Eigenberg, J. A. Nienaber

Conference on Applied Statistics in Agriculture

Heat stress is a factor that causes loss of production and even death in cattle. Animals differ in vulnerability to heat stress. One reason for the difference may be the coat color associated with different breeds or genotypes. A good measure of the heat stress is respiration rate which increases in response to increasing ambient temperature. The objective of this study is to characterize the respiration rates of four genotypes of heat stressed feedlot heifers. Linear and nonlinear models will be compared to find an appropriate method of detecting differences among genotypes.


A Comparison Of Models And Designs For Experiments With Nonlinear Dose-Response Relationships, Shengjie Guo, W. W. Stroup, E. T. Paparozzi, M. E. Conley Apr 2006

A Comparison Of Models And Designs For Experiments With Nonlinear Dose-Response Relationships, Shengjie Guo, W. W. Stroup, E. T. Paparozzi, M. E. Conley

Conference on Applied Statistics in Agriculture

Research investigating dose-response relationship is common in agricultural science. Animal response to drug dose and plant response to amount of irrigation, pesticide, or fertilizer are familiar examples. This paper is motivated by plant nutrition research in horticulture. Plant response to level of nutrient applied is typically sigmoidal, i.e. no response at very low levels, observable response at mid-levels, point-of-diminishing returns and plateau at high levels. Plant scientists need accurate estimates of these response relationships 1) to determine lower threshold below which plants show deficiency symptoms and 2) to determine upper point-of-diminishing returns, above which excessive doses are economically and ...


Decision Quality Metrics – A Tool For Managing Quality Of Repeated Bioassays, Nancy Ferry, William Letsinger Apr 2006

Decision Quality Metrics – A Tool For Managing Quality Of Repeated Bioassays, Nancy Ferry, William Letsinger

Conference on Applied Statistics in Agriculture

Bioassays are often used in tiered screening systems to detect potential products, such as crop protection products. Often these assays are not replicated. The ultimate products of these bioassays are decisions, with biologically “active” compounds advanced to the next level of screening. Activity is determined by the response of the test organisms (e.g., weeds, insects or fungi) to each compound. The reproducibility of the bioassay is crucial. There are two types of possible errors in screening, false positives and false negatives. The quality of the decisions based upon these bioassays can be monitored through time using controls. This paper ...


Evaluating Nonlinear Crossed Random Effects Models For Comparing Temperature Of Feeding Pigs Under Different Thermal Environments, M. Zhou, A. M. Parkhurst, R. A. Eigenberg, J. A. Nienaber, G. L. Hahn Apr 2006

Evaluating Nonlinear Crossed Random Effects Models For Comparing Temperature Of Feeding Pigs Under Different Thermal Environments, M. Zhou, A. M. Parkhurst, R. A. Eigenberg, J. A. Nienaber, G. L. Hahn

Conference on Applied Statistics in Agriculture

The thermal environment plays a large role in an animal’s ability to convert feed into weight gain. A better understanding of a pig’s metabolism will help swine producers select environmental specifications for optimizing feed conversion. The objectives of this study are to 1) characterize the thermoregulatory responses of pigs during a feeding event 2) compare those responses for three thermal environmental treatments applied in a Latin Square design 3) investigate different procedures for fitting nonlinear mixed-effect models with crossed random effects (NLME function in R, %NLINMIX macro in SAS, random effects modeling in AD Model Builder: ADMB-RE). We ...


Modeling Dispersal Of Yellow Starthistle In The Canyon Grasslands Of North Central Idaho, Bahman Shafii, William J. Price, Timothy S. Prather, Lawrence W. Lass, Derek Howard Apr 2006

Modeling Dispersal Of Yellow Starthistle In The Canyon Grasslands Of North Central Idaho, Bahman Shafii, William J. Price, Timothy S. Prather, Lawrence W. Lass, Derek Howard

Conference on Applied Statistics in Agriculture

Yellow starthistle is an invasive plant species that reduces productivity and plant diversity within the canyon grasslands of Idaho. Early detection of yellow starthistle and predicting its spread have important managerial implications that could greatly reduce the economic/environmental losses due to this weed. The spread of an invasive plant species depends on its ability to reproduce and disperse seed into new areas. Typically, information on the factors that directly affect a plant’s ability to reproduce and subsequently disperse seed is not available or difficult to obtain. Alternatively, topographic factors, such as slope and aspect as well as competitive ...


All Possible Model Selection In Proc Mixed – A Sas Macro Application, George C J Fernandez Apr 2006

All Possible Model Selection In Proc Mixed – A Sas Macro Application, George C J Fernandez

Conference on Applied Statistics in Agriculture

A user-friendly SAS macro application to perform all possible model selection of fixed effects including quadratic and cross products in the presence of random and repeated measures effects using SAS PROC MIXED is available. This macro application will complement the model selection option currently available in the SAS PROC REG for multiple linear regressions and the experimental SAS procedure GLMSELECT that focuses on the standard independently and identically distributed general linear model for univariate responses. Options are also included in this macro to select the best covariance structure associated with the user-specified fully saturated repeated measures model; to graphically explore ...


Using Random Sampling To Estimate Insect Counts As Response Surfaces Involving Space And Time, Benjamin G. Mullinix, Glynn Tillman Apr 2006

Using Random Sampling To Estimate Insect Counts As Response Surfaces Involving Space And Time, Benjamin G. Mullinix, Glynn Tillman

Conference on Applied Statistics in Agriculture

In fall 2000, an on-farm sustainable agricultural research project was established for cotton (Gossypium hirstum L.) in Tift County, Georgia. Twenty fields that were to be planted to cotton in 2001 were identified which were approximately 5 to 10 acres in size. Four randomly selected fields were assigned to each of five cover crops: 1) cereal rye (Secale cereale L.); 2) crimson clover (Trifolium incarnatum L.); 3) legume mixture of balansa clover (T. michelianum Savi), crimson clover, and hairy vetch (Vicia villosa Roth); 4) previous legume mixture plus cereal rye; and 5) no cover crop (fallow) in conventionally tilled fields ...


An Estimator Of Treatment Effects Under Combined Sampling And Experimental Designs, Christina D. Smith Apr 2006

An Estimator Of Treatment Effects Under Combined Sampling And Experimental Designs, Christina D. Smith

Conference on Applied Statistics in Agriculture

Sampling design and experimental design have developed relatively independently in recent statistical history. However, many studies do involve both a sampling design and an ex-perimental design. For example, a polluted site may be exhaustively partitioned into area plots, a random sample of plots selected, and the selected plots randomly assigned to three clean-up regimens. To date there is no commonly used procedure for incorporating both the sampling design and the experimental design into the estimation of treatment effects. For this reason we will consider an estimator of treatment effect that does incorporate both sampling and experimental designs and discuss some ...


Appropriate Statistical Methods For Comparing Sources Of Nutritional Methionine, D. D. Kratzer, R. C. Littell Apr 2006

Appropriate Statistical Methods For Comparing Sources Of Nutritional Methionine, D. D. Kratzer, R. C. Littell

Conference on Applied Statistics in Agriculture

Kratzer and Ash(1996) presented Experimentation Science as a process to accomplish the Scientific Method with a complete protocol including relevant statistical design and analyses The first principal to sound Experimentation Science is the principle of Relevance. This is a case study primarily of Relevance in Experimentation Science. In our consulting work we found a so called “performance” design as not relevant because of the use of null hypothesis testing to promote a concept of equivalence. The best alternative involves equivalence testing, more replication and representative-ness. Secondly we found a dose response design for two products where non-linear asymptotic regression ...


Clustering A Series Of Replicated Polyploid Gene Expression Experiments In Maize, Lingling An, Nicole C. Riddle, James A. Birchler, R. W. Doerge Apr 2006

Clustering A Series Of Replicated Polyploid Gene Expression Experiments In Maize, Lingling An, Nicole C. Riddle, James A. Birchler, R. W. Doerge

Conference on Applied Statistics in Agriculture

Ploidy level is defined as the number of individual sets of chromosomes contained in a single cell. Many important crop plants, such as potato, soybean and wheat are polyploid. Although it is widely known that polyploidy is a frequent evolutionary event, it is not fully understand why polyploids have been so successful. In this work cluster analysis is employed to study gene expression changes in a maize inbred line (B73) across a range of polyploidy levels. The B73 ploidy series includes monoploid, diploid, triploid and tetraploid plants and consists of biological and technical replicates as measured by microarray technology. An ...


A Visual Aid For Statisticians And Molecular Biologists Working With Microarray Experiments, Deborah L. Boykin, Earl W. Taliercio, Rowena Y. Kelley, W. Paul Williams Apr 2006

A Visual Aid For Statisticians And Molecular Biologists Working With Microarray Experiments, Deborah L. Boykin, Earl W. Taliercio, Rowena Y. Kelley, W. Paul Williams

Conference on Applied Statistics in Agriculture

The use of microarrays to measure the expression of large numbers of genes simultaneously is increasing in agriculture research. Statisticians are expected to help biologists analyze these large data sets to identify biologically important genes that are differentially regulated in the samples under investigation. However, molecular biologists are often unfamiliar with the statistical methods used to analyze microarrays. Presented here are methods developed to graphically represent microarray data and various types of errors commonly associated with microarrays to help visualize sources of error. Two case studies were used. In case study one, genes differentially regulated when two corn lines, one ...