Browsing by Author "Dougherty, Edward R"
Now showing items 1-20 of 22
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Zollanvari, Amin; Cunningham, Mary Jane; Braga-Neto, Ulisses; Dougherty, Edward R (BMC Bioinformatics, 2009)
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Li, Xiangfang; Qian, Lijun; Hua, Jianping; Bittner, Michael L; Dougherty, Edward R (BMC Genomics, 2012)
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Vakulabaranam Sridharan, Sriram (2015-01-20)The aim of effective cancer treatment is to prolong the patients’ life while offering a reasonable quality of life during and after treatment. The treatments must carry their actions/effects in a manner such that a very ...
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Sun, Youting; Zhang, Jianqiu; Braga-Neto, Ulisses; Dougherty, Edward R (BMC Bioinformatics, 2010)
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Ghaffari, Noushin; Ivanov, Ivan; Qian, Xiaoning; Dougherty, Edward R (BMC Bioinformatics, 2011)
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Hsu, Fang-Han (2013-05-01)The advances of high-throughput technologies, such as next-generation sequencing and microarrays, have rapidly improved the accessibility of molecular profiles in tumor samples. However, due to the immaturity of relevant ...
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Mohsenizadeh, Daniel N; Hua, Jianping; Bittner, Michael; Dougherty, Edward R (BMC Bioinformatics, 2015)
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Dehghannasiri, Roozbeh; Yoon, Byung-Jun; Dougherty, Edward R (BMC Bioinformatics, 2015)
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Su, Junjie; Yoon, Byung-Jun; Dougherty, Edward R (BMC Bioinformatics, 2010)
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Khunlertgit, Navadon (2016-11-22)Identification of robust biomarkers for cancer prognosis based on gene expression data is an important research problem in translational genomics. The high-dimensional and small-sample-size data setting makes the prediction ...
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Qian, Xiaoning; Ivanov, Ivan; Ghaffari, Noushin; Dougherty, Edward R (BMC Systems Biology, 2009)
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Knight, Jason M; Ivanov, Ivan; Dougherty, Edward R (BMC Bioinformatics, 2014)
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Ghaffari, Noushin; Yousefi, Mohammadmahdi R; Johnson, Charles D; Ivanov, Ivan; Dougherty, Edward R (BMC Bioinformatics, 2013)
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Hua, Jianping; Lowey, James; Xiong, Zixiang; Dougherty, Edward R (BMC Bioinformatics, 2006)
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Jiang, Xingde (2016-08-18)Bolstered resubstitution is a simple and fast error estimation method that has been shown to perform better than cross-validation and comparably with bootstrap in small-sample settings. However, it has been observed that ...
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Dehghannasiri, Roozbeh (2016-08-03)In many real-world engineering applications, model uncertainty is inherent. Largescale dynamical systems cannot be perfectly modeled due to systems complexity, lack of enough training data, perturbation, or noise. Hence, ...
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Knight, Jason Matthew (2015-05-04)Predictive modeling of the dynamic, multivariate, non-linear, stochastic systems of biology is a difficult enterprise. High throughput measurement techniques are enabling new approaches to computational biology, but the ...
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Xie, Shuilian (2021-05-18)The standard assumption in classification is that the training data are independent and identically distributed. Indeed, this assumption is so pervasive that it is often applied without mention. In this dissertation, we ...
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Jeong, Hyundoo (2017-07-24)Graph-based systems and data analysis methods have become critical tools in many fields as they can provide an intuitive way of representing and analyzing interactions between variables. Due to the advances in measurement ...
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Esfahani, Mohammad Shahrokh; Yoon, Byung-Jun; Dougherty, Edward R (BMC Bioinformatics, 2011)