The field of biologic research is particularly concerned with understanding nature's complex dynamics. From deducing anatomical structures to studying behavioral patterns, evolutionary theory has developed greatly beyond the simple notions proposed by Charles Darwin. However, because it rarely considers the concept of complexity, modern evolutionary theory retains some descriptive weakness. This project represents an explorative approach for considering complexity and whether it plays an active role in the development of biotic systems. A novel theoretical framework, titled the Genesis Mechanism, was formulated reconsidering the major tenets of evolutionary theory to include complexity as a universal tendency. Within this framework, a phenomenon, referred to as "social transitioning," occurs between higher orders of complexity. Several potential properties of social transitions were proposed and analyzed in order to validate the theoretical concepts proposed within the Genesis Mechanism. The successful results obtained through this project's completion help demonstrate the scientific necessity for understanding complexity from a more fundamental, biologic standpoint.

This project focuses on the history of how teratogens, or agents which have the potential to cause birth defects, have been understood and tested for teratogenic potential in the US over the twentieth century. Prior to this time, teratogen studies were primarily concerned with cataloguing defects rather than exploring possible causes. At the turn of the twentieth century, experimental teratogen studies with the aim of elucidating mechanisms commenced. However, these early studies did not aim to discover human pregnancy outcomes and ways to prevent them, but simply focused on the results of exposing pregnant mammals to various physical and chemical insults. My project documents the change in understanding of teratogens over the twentieth century, the advancement of testing methods, and the causes of these advancements. Through the Embryo Project at Arizona State University (embryo.asu.edu), a digital encyclopedia for topics related to embryology, development, and reproductive medicine, I wrote ten encyclopedic articles that focused on chemical mechanisms of various teratogens, testing limitations in animal models, and legal and regulatory responses to well-known teratogens. As an extension of my previous work, this project bridges the current gap in research and focuses on contextualizing major events in the field of teratology to determine how these events led to various shifts in the understanding of birth defects and their causes, and how those conceptual shifts led to the creation of teratological testing guidelines. Results show that throughout the twentieth century, there are four distinct shifts in the understanding of teratogens: the first being 1900-1945, the second being 1946-1960, the third being 1961-1980, and the fourth being 1981-2000.

Influenza has shown its potential to affect and even kill millions of people within an extremely short time frame, yet studies and surveys show that the general public is not well educated about the facts about influenza, including prevention and treatment. For this reason, public perception of influenza is extremely skewed, with people generally not taking the disease as seriously as they should given its severity. To investigate the inconsistencies between action and awareness of best available knowledge regarding influenza, this study conducted literature review and a survey of university students about their knowledge, perceptions, and action taken in relationship to influenza. Due to their dense living quarters, constant daily interactions, and mindset that they are "immune" to fairly common diseases like influenza, university students are a representative sample of urban populations. According to the World Health Organization (WHO), 54% of the world's population lived in cities as of 2014 (Urban population growth). Between 2015 and 2020, the global urban population is expected to grow 1.84% per year, 1.63% between 2020 and 2025, and 1.44% between 2025 and 2030 (Urban population growth). Similar projections estimate that by 2017, an overwhelming majority of the world's population, even in less developed countries, will be living in cities (Urban population growth). Results of this study suggest possible reasons for the large gap between best available knowledge and the perceptions and actions of individuals on the other hand. This may lead to better-oriented influenza education initiatives, more effective prevention and treatment plans, and generally raise excitement and awareness surrounding public health and scientific communication.

Pressure from fiduciary duty leads agents within organizational systems to make decisions that result in positive feedback loops that often have inimical unintended consequences. The current corporate climate that often puts the bottom line ahead of environmental and social concerns in the name of fiduciary duty is doing so based on a revised interpretation of the term that is clearly to the benefit of the corporations. It is important to note that this modern interpretation is a radical misinterpretation of the intent of the law as our forefathers defined it. However, in spite of the fact that the modern interpretation is leading to inimical unintended consequences, providing the systems agents with the proper training and tools necessary to recognize the cost benefit of implementing sustainable solutions may mitigate some of these positive feedback loops and their associated unintended consequences. By developing tools based on sustainable frameworks we may be able to return these organizations to the original intent of fiduciary duty, which was designed to encourage investment in organizations that worked for the public benefit. A concept that is remarkably similar to the triple bottom line framework that many sustainability professionals advocate on behalf of today.

Studies in neocortical neurogenesis have experienced an explosive growth since the early 2000s, measured by the increasing number of publications each year. I examine here the influence of Arnold Kriegstein in the field using Topic Modeling, a set of algorithms that can be applied to a collection of texts to elucidate the central themes of said collection. Using a Java-based software called MALLET, I obtained data for his corpus, and compared it to the texts of other researchers in the field. This latter collection, which I dub "General Corpus", was separated by year from 2000 to 2014. I found that Kriegstein's most frequently discussed topic concerned highly unique terms such as GABA, glutamate, and receptor, which did not appear in any of the primary topics of the General Corpus. This was in contrast to my initial hypothesis that Kriegstein's importance stemmed from his examination of different phenomena that constitute the broader aspect of neocortical neurogenesis. I predicted that the terms in Kriegstein's primary topic would appear many times throughout the topics of the General Corpus, but it was not so, aside from the common ones such as neurons, cortical, and development. Taken in tandem with NIH Reporter data, these results suggest that Kriegstein obtains a large amount of research funding because his studies concern unique topics when compared to others in the field. The implications of these findings are especially relevant in a world where funding is becoming increasingly difficult to come by.

This dissertation begins to lay out a small slice of the history of morphological research, and how it has changed, from the late 19th through the close of the 20th century. Investigators using different methods, addressing different questions, holding different assumptions, and coming from different research fields have pursued morphological research programs, i.e. research programs that explore the process of changing form. Subsequently, the way in which investigators have pursued and understood morphology has witnessed significant changes from the 19th century to modern day research. In order to trace this shifting history of morphology, I have selected a particular organ, teeth, and traced a tendril of research on the dentition beginning in the late 19th century and ending at the year 2000. But even focusing on teeth would be impossible; the scope of research on this organ is far too vast. Instead, I narrow this dissertation to investigation of research on a particular problem: explaining mammalian tooth morphology. How researchers have investigated mammalian tooth morphology and what counts as an explanation changed dramatically during this period.

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.

The study of wasp societies (family Vespidae) has played a central role in advancing our knowledge of why social life evolves and how it functions. This dissertation asks: How have scientists generated and evaluated new concepts and theories about social life and its evolution by investigating wasp societies? It addresses this question both from a narrative/historical and from a reflective/epistemological perspective. The historical narratives reconstruct the investigative pathways of the Italian entomologist Leo Pardi (1915-1990) and the British evolutionary biologist William D. Hamilton (1936-2000). The works of these two scientists represent respectively the beginning of our current understanding of immediate and evolutionary causes of social life. Chapter 1 shows how Pardi, in the 1940s, generated a conceptual framework to explain how wasp colonies function in terms of social and reproductive dominance. Chapter 2 shows how Hamilton, in the 1960s, attempted to evaluate his own theory of inclusive fitness by investigating social wasps. The epistemological reflections revolve around the idea of investigative framework for theory evaluation. Chapter 3 draws on the analysis of important studies on social wasps from the 1960s and 1970s and provides an account of theory evaluation in the form of an investigative framework. The framework shows how inferences from empirical data (bottom-up) and inferences from the theory (top-down) inform one another in the generation of hypotheses, predictions and statements about phenomena of social evolution. It provides an alternative to existing philosophical accounts of scientific inquiry and theory evaluation, which keep a strong, hierarchical distinction between inferences from the theory and inferences from the data. The historical narratives in this dissertation show that important scientists have advanced our knowledge of complex biological phenomena by constantly interweaving empirical, conceptual, and theoretical work. The epistemological reflections argue that we need holistic frameworks that account for how multiple scientific practices synergistically contribute to advance our knowledge of complex phenomena. Both narratives and reflections aim to inspire and inform future work in social evolution capitalizing on lessons learnt from the past.

Analysis of social networks has the potential to provide insights into wide range of applications. As datasets continue to grow, a key challenge is the lack of a widely applicable algorithmic framework for detection of statistically anomalous networks and network properties. Unlike traditional signal processing, where models of truth or empirical verification and background data exist and are often well defined, these features are commonly lacking in social and other networks. Here, a novel algorithmic framework for statistical signal processing for graphs is presented. The framework is based on the analysis of spectral properties of the residuals matrix. The framework is applied to the detection of innovation patterns in publication networks, leveraging well-studied empirical knowledge from the history of science. Both the framework itself and the application constitute novel contributions, while advancing algorithmic and mathematical techniques for graph-based data and understanding of the patterns of emergence of novel scientific research. Results indicate the efficacy of the approach and highlight a number of fruitful future directions.