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Full-Text Articles in Physical Sciences and Mathematics
Protein Residue-Residue Contact Prediction Using Stacked Denoising Autoencoders, Joseph Bailey Luttrell Iv
Protein Residue-Residue Contact Prediction Using Stacked Denoising Autoencoders, Joseph Bailey Luttrell Iv
Honors Theses
Protein residue-residue contact prediction is one of many areas of bioinformatics research that aims to assist researchers in the discovery of structural features of proteins. Predicting the existence of such structural features can provide a starting point for studying the tertiary structures of proteins. This has the potential to be useful in applications such as drug design where tertiary structure predictions may play an important role in approximating the interactions between drugs and their targets without expending the monetary resources necessary for preliminary experimentation. Here, four different methods involving deep learning, support vector machines (SVMs), and direct coupling analysis were …
Machine Learning Methods For Brain Image Analysis, Ahmed Fakhry
Machine Learning Methods For Brain Image Analysis, Ahmed Fakhry
Computer Science Theses & Dissertations
Understanding how the brain functions and quantifying compound interactions between complex synaptic networks inside the brain remain some of the most challenging problems in neuroscience. Lack or abundance of data, shortage of manpower along with heterogeneity of data following from various species all served as an added complexity to the already perplexing problem. The ability to process vast amount of brain data need to be performed automatically, yet with an accuracy close to manual human-level performance. These automated methods essentially need to generalize well to be able to accommodate data from different species. Also, novel approaches and techniques are becoming …
A Computational Framework For Learning From Complex Data: Formulations, Algorithms, And Applications, Wenlu Zhang
A Computational Framework For Learning From Complex Data: Formulations, Algorithms, And Applications, Wenlu Zhang
Computer Science Theses & Dissertations
Many real-world processes are dynamically changing over time. As a consequence, the observed complex data generated by these processes also evolve smoothly. For example, in computational biology, the expression data matrices are evolving, since gene expression controls are deployed sequentially during development in many biological processes. Investigations into the spatial and temporal gene expression dynamics are essential for understanding the regulatory biology governing development. In this dissertation, I mainly focus on two types of complex data: genome-wide spatial gene expression patterns in the model organism fruit fly and Allen Brain Atlas mouse brain data. I provide a framework to explore …