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The field of biomedical research relies on the knowledge of binding interactions between various proteins of interest to create novel molecular targets for therapeutic purposes. While many of these interactions remain a mystery, knowledge of these properties and interactions could have significant medical applications in terms of understanding cell signaling and immunological defenses. Furthermore, there is evidence that machine learning and peptide microarrays can be used to make reliable predictions of where proteins could interact with each other without the definitive knowledge of the interactions. In this case, a neural network was used to predict the unknown binding interactions of TNFR2 onto LT-ɑ and TRAF2, and PD-L1 onto CD80, based off of the binding data from a sampling of protein-peptide interactions on a microarray. The accuracy and reliability of these predictions would rely on future research to confirm the interactions of these proteins, but the knowledge from these methods and predictions could have a future impact with regards to rational and structure-based drug design.
ContributorsPoweleit, Andrew Michael (Author) / Woodbury, Neal (Thesis director) / Diehnelt, Chris (Committee member) / Chiu, Po-Lin (Committee member) / School of Molecular Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Lung cancer is the leading cause of cancer-related deaths in the US. Low-dose computed tomography (LDCT) scans are speculated to reduce lung cancer mortality. However LDCT scans impose multiple risks including false-negative results, false- positive results, overdiagnosis, and cancer due to repeated exposure to radiation. Immunosignaturing is a new method proposed to screen and detect lung cancer, eliminating the risks associated with LDCT scans. Known and blinded primary blood sera from participants with lung cancer and no cancer were run on peptide microarrays and analyzed. Immunosignatures for each known sample collectively indicated 120 peptides unique to lung cancer and non-cancer participants. These 120 peptides were used to determine the status of the blinded samples. Verification of the results from Vanderbilt is pending.
ContributorsNguyen, Geneva Trieu (Author) / Woodbury, Neal (Thesis director) / Zhao, Zhan-Gong (Committee member) / Stafford, Phillip (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / Department of Psychology (Contributor)
Created2015-05
Description
Twitter, the microblogging platform, has grown in prominence to the point that the topics that trend on the network are often the subject of the news and other traditional media. By predicting trends on Twitter, it could be possible to predict the next major topic of interest to the public. With this motivation, this paper develops a model for trends leveraging previous work with k-nearest-neighbors and dynamic time warping. The development of this model provides insight into the length and features of trends, and successfully generalizes to identify 74.3% of trends in the time period of interest. The model developed in this work provides understanding into why par- ticular words trend on Twitter.
ContributorsMarshall, Grant A (Author) / Liu, Huan (Thesis director) / Morstatter, Fred (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
Description
Bots tamper with social media networks by artificially inflating the popularity of certain topics. In this paper, we define what a bot is, we detail different motivations for bots, we describe previous work in bot detection and observation, and then we perform bot detection of our own. For our bot detection, we are interested in bots on Twitter that tweet Arabic extremist-like phrases. A testing dataset is collected using the honeypot method, and five different heuristics are measured for their effectiveness in detecting bots. The model underperformed, but we have laid the ground-work for a vastly untapped focus on bot detection: extremist ideal diffusion through bots.
ContributorsKarlsrud, Mark C. (Author) / Liu, Huan (Thesis director) / Morstatter, Fred (Committee member) / Barrett, The Honors College (Contributor) / Computing and Informatics Program (Contributor) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
Description
With a quantum efficiency of nearly 100%, the electron transfer process that occurs within the reaction center protein of the photosynthetic bacteria Rhodobacter (Rh.) sphaeroides is a paragon for understanding the complexities, intricacies, and overall systemization of energy conversion and storage in natural systems. To better understand the way in which photons of light are captured, converted into chemically useful forms, and stored for biological use, an investigation into the reaction center protein, specifically into its cascade of cofactors, was undertaken. The purpose of this experimentation was to advance our knowledge and understanding of how differing protein environments and variant cofactors affect the spectroscopic aspects of and electron transfer kinetics within the reaction of Rh. sphaeroides. The native quinone, ubiquinone, was extracted from its pocket within the reaction center protein and replaced by non-native quinones having different reduction/oxidation potentials. It was determined that, of the two non-native quinones tested—1,2-naphthaquinone and 9,10- anthraquinone—the substitution of the anthraquinone (lower redox potential) resulted in an increased rate of recombination from the P+QA- charge-separated state, while the substitution of the napthaquinone (higher redox potential) resulted in a decreased rate of recombination.
ContributorsSussman, Hallie Rebecca (Author) / Woodbury, Neal (Thesis director) / Redding, Kevin (Committee member) / Lin, Su (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
Advances in peptide microarray technology have allowed for the creation of fast-paced and modular experiments within affinity ligand discovery. Previously, low density peptide arrays of 10,000 peptides were used to identify low affinity peptide ligands for a target protein; an approach that can be subsequently improved upon with a number of techniques. VDAP[a] offers more information about the relative affinity of protein-peptide interactions via signal intensity in contrast to high throughput screening (HTS) and display technologies which offer binary data. Now, high density peptide arrays with 130,000 to 330,000 peptides are available that allow screening across peptide libraries of greater diversity. With this increase in scale and diversity, faster analytical tools are needed to adequately characterize array data. Using the statistical power available in the R programming language, we have created a flexible analysis package that efficiently processes high density peptide array data from a variety of layouts, rank existing peptide hits, and utilize signal intensity data to generate new hits. This analysis provides a user-friendly method to efficiently analyze high density peptide array data, generate peptide leads for targeted therapeutic development, and further improve peptide array technologies.
ContributorsMoore, Cody Allen (Author) / Woodbury, Neal (Thesis director) / Diehnelt, Chris (Committee member) / Barrett, The Honors College (Contributor)
Created2015-12
Description
Photosynthesis is the process by which plants, algae, and bacteria use light energy to synthesize organic compounds to use as energy. Among these organisms are a kind of purple photosynthetic bacteria called Rhodobacter sphaeroides, a non-sulfur purple bacteria that grows aerobically in the dark by respiration. There have been many contributions throughout the history of this group of bacteria. Rhodobacter sphaeroides is metabolically very diverse as it has many different ways to obtain energy--aerobic respiration and anoxygenic photosynthesis being just a couple of the ways to do so. This project is part of a larger ongoing project to study different mutant strains of Rhodobacter and the different ways in which carries out electron transfer/photosynthesis. This thesis focused on the improvements made to protocol (standard procedure of site directed mutagenesis) through a more efficient technique known as infusion.
ContributorsNucuta, Diana Ileana (Author) / Woodbury, Neal (Thesis director) / Lin, Su (Committee member) / Loskutov, Andrey (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2014-05
Description
The influenza virus is the main cause of thousands of deaths each year in the United States, and far more hospitalizations. Immunization has helped in protecting people from this virus and there are a number of therapeutics which have proven effective in aiding people infected with the virus. However, these therapeutics are subject to various limitations including increased resistance, limited supply, and significant side effects. A new therapeutic is needed which addresses these problems and protects people from the influenza virus. Synbodies, synthetic antibodies, may provide a means to achieve this goal. Our group has produced a synbody, the 5-5 synbody, which has been shown to bind to and inhibit the influenza virus. The direct pull down and western blot techniques were utilized to investigate how the synbody bound to the influenza virus. Our research showed that the 5-5 synbody bound to the influenza nucleoprotein (NP) with a KD of 102.9 ± 74.48 nM. It also showed that the synbody bound strongly to influenza viral extract from two different strains of the virus, the Puerto Rico (H1N1) and Sydney (H3N2) strains. This research demonstrated that the 5-5 synbody binds with high affinity to NP, which is important because influenza NP is highly conserved between various strains of the virus and plays an important role in the replication of the viral genome. It also demonstrated that this binding is conserved between various strains of the virus, indicating that the 5-5 synbody potentially could bind many different influenza strains. This synbody may have potential as a therapeutic in the future if it is able to demonstrate similar binding in vivo.
ContributorsKombe, Albert E. (Author) / Diehnelt, Chris (Thesis director) / Woodbury, Neal (Committee member) / Legutki, Bart (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / School of International Letters and Cultures (Contributor)
Created2014-05
Description
To facilitate the development of the Semantic Web, we propose in this thesis a general automatic ontology-building algorithm which, given a pool of potential terms and a set of relationships to include in the ontology, can utilize information gathered from Google queries to build a full ontology for a certain domain. We utilized this ontology-building algorithm as part of a larger system to tag computer tutorials for three systems with different kinds of metadata, and index the tagged documents into a search engine. Our evaluation of the resultant search engine indicates that our automatic ontology-building algorithm is able to build relatively good-quality ontologies and utilize this ontology to effectively apply metadata to documents.
ContributorsWalliman, Garret Greg (Author) / Davulcu, Hasan (Thesis director) / Liu, Huan (Committee member) / Bazzi, Rida (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-05
Description
One of the major challenges that were yet to be solved for solid phase peptide synthesis was the lack of an efficient peptide sequencing technique that was less hazardous, easier to perform , and was more cost-effective. Sequencing peptides were held important in the field of Chemistry and Biochemistry because it aided in drug discovery, finding ligands that bind to a specific target protein and finding alternative agents in transporting molecules to its desired location. Therefore, the overall purpose of this experiment was to develop a method of solid phase sequencing technique that was more environmental friendly, sequences at a faster rate, and was more cost-effective.
ContributorsCordovez, Lalaine Anne Ordiz (Author) / Woodbury, Neal (Thesis director) / Zhao, Zhan-Gong (Committee member) / Legutki, Joseph Barten (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2014-05