Search Results - "Dougherty, E. R"

Optimal number of features as a function of sample size for various classification rules by Hua, Jianping, Xiong, Zixiang, Lowey, James, Suh, Edward, Dougherty, Edward R.

“…Motivation: Given the joint feature-label distribution, increasing the number of features always results in decreased classification error; however, this is…”
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Multivariate Measurement of Gene Expression Relationships by Kim, Seungchan, Dougherty, Edward R., Chen, Yidong, Sivakumar, Krishnamoorthy, Meltzer, Paul, Trent, Jeffery M., Bittner, Michael

“…The operational activities of cells are based on an awareness of their current state, coupled to a programmed response to internal and external cues in a…”
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Genomic profiles and predictive biological networks in oxidant-induced atherogenesis by Johnson, C. D, Balagurunathan, Y, Lu, K. P, Tadesse, M, Falahatpisheh, M. H, Carroll, R. J, Dougherty, E. R, Afshari, C. A, Ramos, K. S

“…1 Center for Environmental and Rural Health, Texas A&M University, College Station, Texas 77843 2 Department of Statistics, Texas A&M University, College…”
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Is cross-validation valid for small-sample microarray classification? by Braga-Neto, Ulisses M., Dougherty, Edward R.

“…Motivation: Microarray classification typically possesses two striking attributes: (1) classifier design and error estimation are based on remarkably small…”
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Aperture filters by Hirata, R., Dougherty, E.R., Barrera, J.

“…Except in the case of very low-bit signals (images), unconstrained design of mean-square-error optimal digital window-based filters from sample signals is…”
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From Boolean to probabilistic Boolean networks as models of genetic regulatory networks by Shmulevich, I., Dougherty, E.R., Wei Zhang

“…Mathematical and computational modeling of genetic regulatory networks promises to uncover the fundamental principles governing biological systems in an…”
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Multiscale Denoising of Biological Data: A Comparative Analysis by Nounou, M. N., Nounou, H. N., Meskin, N., Datta, A., Dougherty, E. R.

“…Measured microarray genomic and metabolic data are a rich source of information about the biological systems they represent. For example, time-series…”
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Gene perturbation and intervention in probabilistic Boolean networks by Shmulevich, Ilya, Dougherty, Edward R., Zhang, Wei

“…Motivation: A major objective of gene regulatory network modeling, in addition to gaining a deeper understanding of genetic regulation and control, is the…”
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Gene selection: a Bayesian variable selection approach by KYEONG EUN LEE, NAIJUN SHA, DOUGHERTY, Edward R, VANNUCCI, Marina, MALLICK, Bani K

“…Selection of significant genes via expression patterns is an important problem in microarray experiments. Owing to small sample size and the large number of…”
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Generating Boolean networks with a prescribed attractor structure by Pal, Ranadip, Ivanov, Ivan, Datta, Aniruddha, Bittner, Michael L., Dougherty, Edward R.

“…Motivation: Dynamical modeling of gene regulation via network models constitutes a key problem for genomics. The long-run characteristics of a dynamical system…”
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On approximate stochastic control in genetic regulatory networks by Faryabi, B, Datta, A, Dougherty, E R

“…The control of probabilistic Boolean networks as a model of genetic regulatory networks is formulated as an optimal stochastic control problem and has been…”
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A general axiomatic theory of intrinsically fuzzy mathematical morphologies by Sinha, D., Dougherty, E.R.

“…Intrinsic fuzzification of mathematical morphology is grounded on an axiomatic characterization of subset fuzzification. The result is an axiomatic formulation…”
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RNAi microarray analysis in cultured mammalian cells by Mousses, Spyro, Caplen, Natasha J, Cornelison, Robert, Weaver, Don, Basik, Mark, Hautaniemi, Sampsa, Elkahloun, Abdel G, Lotufo, Roberto A, Choudary, Ashish, Dougherty, Edward R, Suh, Ed, Kallioniemi, Olli

“…RNA interference (RNAi) mediated by small interfering RNAs (siRNAs) is a powerful new tool for analyzing gene knockdown phenotypes in living mammalian cells…”
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Ratio statistics of gene expression levels and applications to microarray data analysis by YIDONG CHEN, KAMAT, Vishnu, DOUGHERTY, Edward R, BITTNER, Michael L, MELTZER, Paul S, TRENT, Jeffery M

“…Expression-based analysis for large families of genes has recently become possible owing to the development of cDNA microarrays, which allow simultaneous…”
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The Role of Certain Post Classes in Boolean Network Models of Genetic Networks by Shmulevich, Ilya, Lähdesmäki, Harri, Dougherty, Edward R., Astola, Jaakko, Zhang, Wei

“…A topic of great interest and debate concerns the source of order and remarkable robustness observed in genetic regulatory networks. The study of the generic…”
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Coefficient of determination in nonlinear signal processing by Dougherty, Edward R., Kim, Seungchan, Chen, Yidong

“…For statistical design of an optimal filter, it is probabilistically advantageous to employ a large number of observation random variables; however, estimation…”
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Inference of Boolean networks under constraint on bidirectional gene relationships by Vahedi, G, Ivanov, I V, Dougherty, E R

“…The coefficient of determination (CoD) has been used to infer Boolean networks (BNs) from steady-state data, in particular, to estimate the constituent BNs for…”
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Missing-value estimation using linear and non-linear regression with Bayesian gene selection by Zhou, Xiaobo, Wang, Xiaodong, Dougherty, Edward R.

“…Motivation: Data from microarray experiments are usually in the form of large matrices of expression levels of genes under different experimental conditions…”
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Is cross-validation better than resubstitution for ranking genes? by Braga-Neto, Ulisses, Hashimoto, Ronaldo, Dougherty, Edward R., Nguyen, Danh V., Carroll, Raymond J.

“…Motivation: Ranking gene feature sets is a key issue for both phenotype classification, for instance, tumor classification in a DNA microarray experiment, and…”
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Small sample issues for microarray-based classification by Dougherty, Edward R.

“…In order to study the molecular biological differences between normal and diseased tissues, it is desirable to perform classification among diseases and stages…”
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