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Full-Text Articles in Life Sciences
Characterization Of Mrna Polyadenylation In The Apicomplexa, Ashley T. Stevens, Daniel K. Howe, Arthur G. Hunt
Characterization Of Mrna Polyadenylation In The Apicomplexa, Ashley T. Stevens, Daniel K. Howe, Arthur G. Hunt
Plant and Soil Sciences Faculty Publications
Messenger RNA polyadenylation is a universal aspect of gene expression in eukaryotes. In well-established model organisms, this process is mediated by a conserved complex of 15–20 subunits. To better understand this process in apicomplexans, a group of unicellular parasites that causes serious disease in humans and livestock, a computational and high throughput sequencing study of the polyadenylation complex and poly(A) sites in several species was conducted. BLAST-based searches for orthologs of the human polyadenylation complex yielded clear matches to only two—poly(A) polymerase and CPSF73—of the 19 proteins used as queries in this analysis. As the human subunits that recognize the …
Evaluating Reproducibility In Computational Biology Research, Morgan Oneka
Evaluating Reproducibility In Computational Biology Research, Morgan Oneka
Honors Projects
For my Honors Senior Project, I read five research papers in the field of computational biology and attempted to reproduce the results. However, for the most part, this proved a challenge, as many details vital to utilizing relevant software and data had been excluded. Using Geir Kjetil Sandve's paper "Ten Simple Rules for Reproducible Computational Research" as a guide, I discuss how authors of these five papers did and did not obey these rules of reproducibility and how this affected my ability to reproduce their results.
Fast And Space-Efficient Location Of Heavy Or Dense Segments In Run-Length Encoded Sequences, Ronald I. Greenberg
Fast And Space-Efficient Location Of Heavy Or Dense Segments In Run-Length Encoded Sequences, Ronald I. Greenberg
Ronald Greenberg
This paper considers several variations of an optimization problem with potential applications in such areas as biomolecular sequence analysis and image processing. Given a sequence of items, each with a weight and a length, the goal is to find a subsequence of consecutive items of optimal value, where value is either total weight or total weight divided by total length. There may also be a specified lower and/or upper bound on the acceptable length of subsequences. This paper shows that all the variations of the problem are solvable in linear time and space even with non-uniform item lengths and divisible …
An Interdisciplinary Approach To The Target Elucidation Of Novel Antibiotic 31g12, Larissa A. Walker
An Interdisciplinary Approach To The Target Elucidation Of Novel Antibiotic 31g12, Larissa A. Walker
Graduate Student Theses, Dissertations, & Professional Papers
Staphylococcus aureus is a Gram-positive bacterial pathogen responsible for nosocomial and community-acquired infections that can quickly acquire antibiotic resistance. We have identified a novel triazole antimicrobial 31G12 based on the natural product core of nonactin isolated from the fermentation of Streptomyces griseus, that is active against many Gram-positive bacteria as well as antibiotic resistant methicillin-resistant S. aureus and vancomycin-resistant Enterococcus. The synthesis and characterization indicate that 31G12 exists as a mixture of two rotamers at room temperature and displays bacteriostatic activity against S. aureus with moderate mammalian cell toxicity. We have currently identified potential protein targets of 31G12 in …
Scalable Feature Selection And Extraction With Applications In Kinase Polypharmacology, Derek Jones
Scalable Feature Selection And Extraction With Applications In Kinase Polypharmacology, Derek Jones
Theses and Dissertations--Computer Science
In order to reduce the time associated with and the costs of drug discovery, machine learning is being used to automate much of the work in this process. However the size and complex nature of molecular data makes the application of machine learning especially challenging. Much work must go into the process of engineering features that are then used to train machine learning models, costing considerable amounts of time and requiring the knowledge of domain experts to be most effective. The purpose of this work is to demonstrate data driven approaches to perform the feature selection and extraction steps in …