Browsing by Author "Yoon, Byung-Jun"
Now showing items 1-20 of 70
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Su, Junjie (2012-02-14)Finding reliable gene markers for accurate disease classification is very challenging due to a number of reasons, including the small sample size of typical clinical data, high noise in gene expression measurements, and ...
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Su, Junjie; Yoon, Byung-Jun; Dougherty, Edward R.; Stolovitzky, Gustavo (PloS One, 2009)
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Jeong, Hyundoo; Yoon, Byung-Jun (BMC Systems Biology, 2015)
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Gosangi, Rakesh (2013-07-17)Chemical sensors are generally used as one-dimensional devices, where one measures the sensor’s response at a fixed setting, e.g., infrared absorption at a specific wavelength, or conductivity of a solid-state sensor at a ...
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Kim, Mansuck; Yoon, Byung-Jun (BMC Genomics, 2012)
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Pande, Paritosh (2014-05-16)With significant progress made in the design and instrumentation of optical imaging systems, it is now possible to perform high-resolution tissue imaging in near real-time. The prohibitively large amount of data obtained ...
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Liu, Xueting (2019-11-21)Estimating density maps and counting the number of objects of interest from images has a wide range of applications, such as crowd counting, traffic monitoring, cell microscopy in biomedical imaging, plant counting in ...
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Lee, Joseph Sung (2016-04-22)Navigation is a fundamental task for mobile robots in applications such as exploration, surveillance, and search and rescue. The task involves solving the simultaneous localization and mapping (SLAM) problem, where a map ...
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Narayanan, Sanjeev (2019-11-06)This thesis focuses on 3 main tasks related to Document Recommendations. The first approach deals with applying existing techniques on Document Recommendations using Doc2Vec. A robust representation of the same is presented ...
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Wang, Yucheng (2021-04-27)Object counting in images has been studied extensively, in particular using deep network models recently. The existing counting models typically output the point estimates of the object counts in given images. However, ...
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Zamani Dadaneh, Siamak (2019-09-16)We develop a Bayesian framework for the analysis of high-throughput sequencing count data under a variety of settings, removing sophisticated ad-hoc pre-processing steps commonly required in existing algorithms. Specifically, ...
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Bayesian Semiparametric Density Deconvolution and Regression in the Presence of Measurement Errors Sarkar, Abhra (2014-06-24)Although the literature on measurement error problems is quite extensive, solutions to even the most fundamental measurement error problems like density deconvolution and regression with errors-in-covariates are available ...
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Atashpazgargari, Esmaeil (2014-08-27)Discovery and validation of protein biomarkers with high specificity is the main challenge of current proteomics studies. Different mass spectrometry models are used as shotgun tools for discovery of biomarkers which is ...
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Kim, Jinsu (2014-11-19)Markov chain Monte Carlo (MCMC) methods have proven to be a very powerful tool for analyzing data of complex structures. However, their compute-intensive nature, which typically require a large number of iterations and a ...
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Choi, Junsouk (2023-07-30)Observational zero-inflated count data arise in a wide range of areas such as economics, social sciences, and biology. One of the common research questions in these areas is to identify causal relationships by learning the ...
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Qian, Xiaoning; Yoon, Byung-Jun (BMC Bioinformatics, 2011)
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Kim, Mansuck (2016-02-15)Fusarium verticillioides is one of the key pathogens for stalk rot and ear rot on maize. While several genes associated with F. verticillioides pathogenicity and mycotoxin biosynthesis have been characterized, our knowledge ...
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Kim, Mansuck; Zhang, Huan; Woloshuk, Charles; Shim, Won-Bo; Yoon, Byung-Jun (BMC Bioinformatics, 2015)
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Nallaparaju, Venkata Vikas Varma (2018-11-21)RNA sequence analysis and structure prediction are classical topics of computational biology and a powerful tool to examine complex genomic data. Over the decades, various tools have been developed to predict RNA secondary ...
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Gadiyaram, Manasa (2022-04-19)Long non-coding RNA’s(lncRNA’s) are a type of RNA transcripts with a length of more than 200 nucleotides which cannot be translated into proteins. The study of lncRNAs is extremely important since it has been discovered ...