Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
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- Creators: Laubichler, Manfred
Description
Systems biology studies complex biological systems. It is an interdisciplinary field, with biologists working with non-biologists such as computer scientists, engineers, chemists, and mathematicians to address research problems applying systems’ perspectives. How these different researchers and their disciplines differently contributed to the advancement of this field over time is a question worth examining. Did systems biology become a systems-oriented science or a biology-oriented science from 1992 to 2013?
This project utilized computational tools to analyze large data sets and interpreted the results from historical and philosophical perspectives. Tools deployed were derived from scientometrics, corpus linguistics, text-based analysis, network analysis, and GIS analysis to analyze more than 9000 articles (metadata and text) on systems biology. The application of these tools to a HPS project represents a novel approach.
The dissertation shows that systems biology has transitioned from a more mathematical, computational, and engineering-oriented discipline focusing on modeling to a more biology-oriented discipline that uses modeling as a means to address real biological problems. Also, the results show that bioengineering and medical research has increased within systems biology. This is reflected in the increase of the centrality of biology-related concepts such as cancer, over time. The dissertation also compares the development of systems biology in China with some other parts of the world, and reveals regional differences, such as a unique trajectory of systems biology in China related to a focus on traditional Chinese medicine.
This dissertation adds to the historiography of modern biology where few studies have focused on systems biology compared with the history of molecular biology and evolutionary biology.
This project utilized computational tools to analyze large data sets and interpreted the results from historical and philosophical perspectives. Tools deployed were derived from scientometrics, corpus linguistics, text-based analysis, network analysis, and GIS analysis to analyze more than 9000 articles (metadata and text) on systems biology. The application of these tools to a HPS project represents a novel approach.
The dissertation shows that systems biology has transitioned from a more mathematical, computational, and engineering-oriented discipline focusing on modeling to a more biology-oriented discipline that uses modeling as a means to address real biological problems. Also, the results show that bioengineering and medical research has increased within systems biology. This is reflected in the increase of the centrality of biology-related concepts such as cancer, over time. The dissertation also compares the development of systems biology in China with some other parts of the world, and reveals regional differences, such as a unique trajectory of systems biology in China related to a focus on traditional Chinese medicine.
This dissertation adds to the historiography of modern biology where few studies have focused on systems biology compared with the history of molecular biology and evolutionary biology.
ContributorsZou, Yawen (Author) / Laubichler, Manfred (Thesis advisor) / Maienschein, Jane (Thesis advisor) / Creath, Richard (Committee member) / Ellison, Karin (Committee member) / Newfeld, Stuart (Committee member) / Arizona State University (Publisher)
Created2016
Description
Computational tools in the digital humanities often either work on the macro-scale, enabling researchers to analyze huge amounts of data, or on the micro-scale, supporting scholars in the interpretation and analysis of individual documents. The proposed research system that was developed in the context of this dissertation ("Quadriga System") works to bridge these two extremes by offering tools to support close reading and interpretation of texts, while at the same time providing a means for collaboration and data collection that could lead to analyses based on big datasets. In the field of history of science, researchers usually use unstructured data such as texts or images. To computationally analyze such data, it first has to be transformed into a machine-understandable format. The Quadriga System is based on the idea to represent texts as graphs of contextualized triples (or quadruples). Those graphs (or networks) can then be mathematically analyzed and visualized. This dissertation describes two projects that use the Quadriga System for the analysis and exploration of texts and the creation of social networks. Furthermore, a model for digital humanities education is proposed that brings together students from the humanities and computer science in order to develop user-oriented, innovative tools, methods, and infrastructures.
ContributorsDamerow, Julia (Author) / Laubichler, Manfred (Thesis advisor) / Maienschein, Jane (Thesis advisor) / Creath, Richard (Committee member) / Ellison, Karin (Committee member) / Hooper, Wallace (Committee member) / Renn, Jürgen (Committee member) / Arizona State University (Publisher)
Created2014
Description
Abortion is a controversial topic internationally. Most current debates about abortion concern when, if at all, it should be legal. However, researchers have shown many times that after an abortion ban, maternal and infant mortalities rise significantly, as women who seek out abortions do so regardless of abortion legality. So, is it possible to reduce abortions in a population without delegalizing abortion and, if so, how? Why do some countries have higher abortion rates than others in the presence of the same law?This dissertation answers both questions. First, I present historical evidence in the first comprehensive comparative analysis of all 15 post-Soviet countries, which have very similar abortion laws originating from the Union of Soviet Socialist Republics (USSR). Second, I use those findings to build the first agent-based model (ABM) of unintended pregnancies in a hypothetical artificial population.
USSR was the only country in the world to complete its demographic transition through abortion instead of modern contraception, and the Soviet government passed the first law in the world to allow abortion upon request in 1920. After the USSR dissolution in 1991, post-Soviet countries maintained very similar abortion laws, but had very different abortion rates for most years. Analysis of fertility data from post-Soviet countries shows that the prevalence of some specific contraceptive methods, namely the rhythm method (r = 0.82), oral pill (r = 0.56), and male condom (r = 0.51) are most strongly correlated with high abortion rates, and that sex education is a factor that reduces the rates in otherwise similar countries (p = 0.02).
The ABM shows that even basic sex education results in fewer abortions than no sex education or abstinence-based sex education (p < 0.01). In scenarios without sex education, basic quality of post-abortion contraceptive counseling (PACC) is better than no PACC or low-quality PACC at reducing abortions (p < 0.01). Still, the higher the quality of sex education or PACC, the fewer abortions in the artificial population. The ABM is adaptive and policy makers can use it as a decision-support tool to make evidence-based policy decisions regarding abortion, and, potentially, other sociobiological phenomena with some adjustments to the code.
ContributorsZiganshina Lienhard, Dina A. (Author) / Maienschein, Jane (Thesis advisor) / Gaughan, Monica (Thesis advisor) / Laubichler, Manfred (Committee member) / Ellison, Karin (Committee member) / Arizona State University (Publisher)
Created2023