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Full-Text Articles in Physical Sciences and Mathematics
Development And Evaluation Of Machine Learning Algorithms For Biomedical Applications, Turki Talal Turki
Development And Evaluation Of Machine Learning Algorithms For Biomedical Applications, Turki Talal Turki
Dissertations
Gene network inference and drug response prediction are two important problems in computational biomedicine. The former helps scientists better understand the functional elements and regulatory circuits of cells. The latter helps a physician gain full understanding of the effective treatment on patients. Both problems have been widely studied, though current solutions are far from perfect. More research is needed to improve the accuracy of existing approaches.
This dissertation develops machine learning and data mining algorithms, and applies these algorithms to solve the two important biomedical problems. Specifically, to tackle the gene network inference problem, the dissertation proposes (i) new techniques …
Big Data Analytics In Computational Biology And Bioinformatics, Kevin Byron
Big Data Analytics In Computational Biology And Bioinformatics, Kevin Byron
Dissertations
Big data analytics in computational biology and bioinformatics refers to an array of operations including biological pattern discovery, classification, prediction, inference, clustering as well as data mining in the cloud, among others. This dissertation addresses big data analytics by investigating two important operations, namely pattern discovery and network inference.
The dissertation starts by focusing on biological pattern discovery at a genomic scale. Research reveals that the secondary structure in non-coding RNA (ncRNA) is more conserved during evolution than its primary nucleotide sequence. Using a covariance model approach, the stems and loops of an ncRNA secondary structure are represented as a …
Statistical Learning Methods For Mining Marketing And Biological Data, Jie Zhang
Statistical Learning Methods For Mining Marketing And Biological Data, Jie Zhang
Dissertations
Nowadays, the value of data has been broadly recognized and emphasized. More and more decisions are made based on data and analysis rather than solely on experience and intuition. With the fast development of networking, data storage, and data collection capacity, data have increased dramatically in industry, science and engineering domains, which brings both great opportunities and challenges. To take advantage of the data flood, new computational methods are in demand to process, analyze and understand these datasets.
This dissertation focuses on the development of statistical learning methods for online advertising and bioinformatics to model real world data with temporal …