VictorJuiz/thesis huggingface dataset:
Computational and experimental approaches to understanding mammalian gene regulation with synthetic biology

Transcriptional regulation is a key pathway cells use to regulate gene expression in response to temporal signaling, and is becoming widely used as a platform for synthetic biology applications. Transcription in mammalian cells is in large part driven by the actions of transcription factors, which consist of DNA-binding domains that recognize and bind to specific genomic locations and effector domains that recruit transcriptional machinery and chromatin regulators to activate or repress target genes. This work uses mathematical modeling and high-throughput experimental approaches to dissect the temporal and combinatorial logic of gene regulation in mammalian cells. First, we build a mathematical framework for analyzing the response of genetic circuits containing chromatin regulators to temporal signals in mammalian cell populations, elaborating on prior models in which individual cells stochastically transitioning between active, reversibly silent, and irreversibly silent gene states at constant rates over time. We analyze classical gene regulatory motifs such as feedforward and autoregulatory loops in the context of duration-dependent signaling, and find that repressive regulators with epigenetic memory can sum up and encode the total duration of their recruitment in the fraction of cells irreversibly silenced. Last, we use an information theoretic approach to show that all-or-none stochastic silencing can be used by populations to transmit information reliably and with high fidelity even in very simple genetic circuits. Second, we use a high-throughput approach to dissecting how distinct effector domains within a single transcription factor can be combined to regulate gene expression. We measure transcriptional activity for 8,400 effector domain combinations by recruiting them to reporter genes in human cells. We find that weak and moderate activation domains synergize to drive strong gene expression, while combining strong activators often results in weaker activation. In contrast, weaker repressor domains tend to average each other out, and moderate to strong repressor domains often overpower activation domains. We use this information to build a synthetic transcription factor whose function can be tuned between repression and activation independent of recruitment to target genes by using a small molecule drug. Altogether, this work helps to advance our understanding of how to build synthetic transcription factors, and how to design and model chromatin regulation-based circuits. Our hope is that these efforts will help advance mammalian synthetic biology as a tool for biological research and a reliable strategy for developing medical therapies

Keywords: Humanities and Sciences.
Advisor: Bintu Lacramioara
Bassik Michael
Kundaje Anshul
Computational and functional studies on the genomic basis of vertebrate traits

One of the most profound discoveries of modern science thus far is that the breathtakingly beautiful diversity of form and function in life is encoded by the genome. Despite major advances in genome sequencing and functional testing, there is yet much to learn about how traits are specified by underlying DNA sequence. For vertebrate genomes, linking genotypic variation to phenotypic outcome is especially challenging given that their typical size spans hundreds of megabases to several gigabases in length. In my graduate work, I contributed to efforts addressing this challenge. Each study described in this thesis involved computational analysis of vertebrate genome sequence, either in the form of whole nuclear genome assemblies or of high-throughput short-read sequencing data, to identify candidate regions associated with and hypothesized to control traits of interest. For two of the studies, including my main thesis project described in chapter 6, I also performed functional testing to evaluate the extent to which candidate regions actually contribute to the associated phenotype. Together, the efforts described in this thesis represents genotype-phenotype mapping methods to identify the protein-coding and cis-regulatory sequence basis of disease-related and naturally evolved traits that arose over the last 10s to 10s of millions of years in humans, other placental mammals, and fishes

Keywords: Medicine.
Developmental Biology.
Advisor: Bejerano Gill
Kingsley David M. (David Mark)
Fuller Margaret T.
Talbot William S.
Computational applications towards 1D van der Waals and phase change materials

This thesis focuses on the intersection of materials screening, machine learning, and ab-initio calculations, with regards to low dimensional materials - mainly 1D dimensional van der Waals wires and materials with 1D and 2D structures that are particularly suitable for phase change applications. 1D van der Waals materials are a less studied counterpart to their 2D dimensional cousins, but there exists a wide range of such 1D prototypes, including conducting wires that may be suitable as consideration for interconnect replacement candidates. We find exfoliation energies can be reasonable and of the same magnitude as their 2D layers, and evaluate their electronic property changes as we thin these wires to the 1D limit. Due to the fact there is a limited number of such materials, only a few hundred, we machine-learn to expand this composition space, training using the known compositions and using input features based on the elemental-makeup. We particularly target conductive and magnetic materials, as well as those containing transition metals and members of the chalcogen, pnictogen, and halogen families, as those are often particularly suited for chemical vapour decomposition (CVD) and chemical vapour transport (CVT) synthesis mechanisms. Previous work in the group has examined the phase changes in the transition metal dichalcogenides (TMD), and we extend this to a wider range of materials as well as changes where only the relative stacking between low-dimensional components differ. The multiple phases present can display unique dynamics, including switching mechanisms potentially relevant for phase change memory applications. We present a bottom-up screening across all crystalline material to evaluate their phase change potential. For the stacking changes, we study the 1T' and the $T_d$ transition present in select members of the transition metal dichalcogenide family. Past research has focused on the 1T, 1T' and the 2H phase transitions, where the individual 2D layers support differing structures. In contrast, the 1T' and the $T_d$ phases have the same individual layers, but a differing relative orientation that is present between the two. This type of sliding phase transition offers the potential to further reduce switching timescales. We present an analysis on the few-layer behavior of the transition metal dichalcogenide structures of 1T' and T$_d$ WTe$_2$ and MoTe$_2$ with the observation that the energy differences are far more subtle

Keywords: Humanities and Sciences.
Applied Physics.
Advisor: Jornada Felipe
Spakowitz Andrew James
Mannix Andrew J.
Computational methods and mathematical measures for population relationships

A population is the most central unit of study in population genetics. Patterns revealed by data on variation, both genetic and cultural, are important in understanding the composition and dynamics of populations. These patterns help unravel the driving forces behind evolutionary processes. Numerous statistics, mathematical models, and computational approaches have been developed to quantitatively analyze relationships within and between populations. To build upon these efforts, this dissertation investigates and devises computational methods and mathematical measures for studying various aspects of populations. Chapters 2, 3, and 4 investigate the mathematical properties of genetic diversity measures used to quantify the variation within and between populations. Chapters 5 and 6 study the challenge of cluster alignment in analyzing and visualizing population structure analysis results. Chapters 7 and 8 adapt population-genetic approaches to study the patterns of composition and change in cultural traits. Collectively, the studies conducted in the dissertation introduce tools to improve existing approaches, to devise new frameworks, and to resolve previously unaddressed issues in analyzing population relationships. The advancements also demonstrate potential applications in fields beyond population genetics.

Keywords: Engineering.
Advisor: Rosenberg Noah
Feldman Marcus
Palacios Julia
Computational modeling of axon mechanics : viscoelasticity, growth, and damage

Axons play a vital role in the function of the nervous system by carrying electrical signals between neurons and other cells. Their long and thin structure, however, makes them especially vulnerable to damage. In fact, axons are a frequent lesion site in traumatic brain injury, and diffuse axonal injury has been linked to coma, cognitive impairment, and the development of neurodegenerative disease. While loading applied at high rates and magnitudes can damage the axon, the axon exhibits different responses to mechanical loading at other loading rates and magnitudes. At physiological levels of loading, the axon deforms as a viscoelastic solid, and at intermediate levels of loading, mechanical forces can even induce growth and promote regeneration. In fact, the gradual application of tension is being explored as an avenue to promote axon regeneration in peripheral nerve repair. The success of approaches like this is dependent on knowledge of the mechanical responses of the axon - viscoelasticity, growth, and damage - as well as the thresholds separating these responses. Here, computational modeling can aid the generalization from in vitro measurements to engineering applications. In this thesis, I introduce computational models describing the complex mechanical response of the axon. First, I present a mathematical framework modeling axon viscoelasticity, growth, and damage and discuss its application in informing nerve repair strategies. Then, focusing in on damage, I introduce an image-based axon model used to pinpoint factors influencing susceptibility to injury. Finally, I discuss the application of mechanics-informed neural networks to model viscoelastic response. These computational models assemble myriad experimental measurements into frameworks that provide a comprehensive representation of axon mechanical response.

Keywords: Engineering.
Mechanical Engineering.
Advisor: Kuhl Ellen
Chaudhuri Ovijit
Goodman Miriam
Computational validity

As online learning platforms and computerized testing become more common, an increasing amount of data are collected about users. These data include, but are not limited to, response time, keystroke logs, and raw text. The desire to observe these features of the response process reflect an underly- ing interest in the cognitive processes and behaviors respondents engage in while taking tests and navigating learning platforms. Alongside this interest in response processes is an increased desire to use computational methods, artificial intelligence, and machine learning to combine this process data with traditional item response data. This dissertation attempts to advance a notion of computational validity, defined as arguments for the use and interpretation of test scores from evidence collected or analyzed using computational methods. Chapter one looks at item position effects as a threat to comparability across test forms. The presence of position effects is especially threatening to computer adaptive tests. Here a mixture item response theory model that decomposes item and person components of position effects is developed and applied to a large Brazilian college admissions exam to demonstrate its ability to both recover information about position effects in items and automatically produce comparable ability distributions across forms. Chapter two looks at data from a browser-based reading assessment and proposes drift diffusion models as a theoretically grounded way to combine response time and response accuracy data. The individual parameters estimated from the drift diffusion models are combined with scores on the browser-based assessment and used to predict scores on more expensive and time consuming measures of reading ability. This provides a line of evidence justifying the clinical and classroom use of the tool for diagnostic purposes. Chapter three looks at the issue of model selection. To make decisions from a model requires justification that the model is appropriate for the data. Current methods of model selection are well suited to make decisions on which model fits better, but not to communicate about how much better or if the degree of fit is appropriate. This paper uses a tool called the InterModel Vigorish that aims to provide measures of increases in predictive performance on an interpretable scale and extends it to polytomous item response theory models. Simulations are performed to explore what can be learned about data generating processes from this tool and then it is applied to a selection of empirical datasets. Combined, this work aims to highlight ways that modern computational methodologies can be used to improve not only assessments, but the decisions we make from them and our ability to communicate about them

Keywords: Education.
Advisor: Ruiz-Primo Maria Araceli
Domingue Ben
Yeatman Jason D.
Computer vision and robotics enable automated experimentation on drosophila behavior

The fruit fly, Drosophila melanogaster, is a widely used model animal in neuroscience and diverse fields of biological and medical domains. Increased automation of assays would greatly facilitate many aspects of research, but the implementation of automated assays has been hindered by the difficulty of handling individual flies in a mechanized way. To address this hurdle, we introduce FlyMAX (Fly Manipulation and Automated eXperimentation), a system capable of collecting adult flies without the use of anesthesia and inspecting them with machine vision, yielding a throughput over 1,000 flies daily for high-throughput assays. Our study validates that the robotic handling of flies has no adverse effects on fly health. Furthermore, the integration of deep learning-based machine vision enables real-time inspection of fly quality and phenotypes. Notably, the system allows for automated assessments of stimuli-response behavior assays on individual flies. FlyMAX offers a promising solution for enhancing the efficiency and reproducibility of insect research in various fields such as genetics, neuroscience, and drug testing.

Keywords: Engineering.
Electrical Engineering.
Advisor: Schnitzer Mark Jacob
Clandinin Thomas R. (Thomas Robert)
El Gamal Abbas A.
Pauly John (John M.)
Computer-aided high-throughput screening for the discovery of GPCR biased ligands

G protein-coupled receptors (GPCRs) constitute the largest family of membrane receptors in the human genome and play important roles in both physiology and disease. One important property of GPCRs is biased signaling, whereby ligand engagement selectively activates a subset of signaling pathways. There is great interest in the therapeutic development of biased ligands for GPCRs given that they have the potential to selectively target downstream signaling pathways of interest and treat diseases more safe and effective manner. However, the complexity of the structural and signaling properties of GPCRs has presented many challenges in developing biased ligands. Here, we introduce a novel and generalizable high-throughput screening approach for discovering biased ligands for GPCRs. Biased ligands can stabilize distinct receptor conformations, which directly affect receptor interaction with intracellular signaling proteins, resulting in different downstream signaling outcomes. Our method integrates high-throughput screening and statistical modeling to examine large mutant protein libraries and infer the ligand-receptor binding conformation based on mutation statistical patterns. The inferred binding conformations allow for efficient identification of candidate biased ligands based on their different binding interactions with the receptor. We applied our computer-aided high-throughput screening approach to search for biased ligands targeting the Complement 5a Receptor, an important GPCR involved in the immune response and cancer. Importantly, we identified a variety of biased mutants with distinct signaling properties. In the future, we aim to apply our platform to other GPCRs and promote the study and therapeutic application of GPCR biased signaling

Keywords: Engineering.
Bioengineering.
Advisor: Giaccia Amato J.
Cochran Jennifer R.
Graves Edward (Edward Elliot)
The concept of hope in the works of Hannah Arendt

This dissertation uses the works of the German-Jewish philosopher Hannah Arendt to generate hope. I situate Arendt within a milieu of 20th Century German Jews whose experiences led them to reject Hegel's philosophy of history. I argue that Arendt instead finds hope in the human capacity to assert ourselves within history and act in surprising ways, and that this secular, humanist hope offers an alternative to theological salvation narratives and to contemporary philosophy of history. I further argue that, by placing her hope in individuals and communities, Arendt continues a tradition of anti-metaphysical Jewish thought, and that her secularism and her Judaism thus reinforce one another. I explore three sources of hope in the three chapters of this dissertation: storytelling, natality, and forgiveness

Keywords: Humanities and Sciences.
German Studies.
Advisor: Eshel Amir
Pao Lea
Starkey Kathryn
Conduct Becoming and Unbecoming of Students: Public Discourses on Dating, Sexuality, Gender, and Consent at Stanford University, 1919-1941

While many consider the 1960s and 1970s to be a watershed moment when college campuses erupted with discussion of sex and consent; but that was not the first time students and their institution talked about these important topics. Utilizing archival administrative documents, student papers, and student publications of the era, Julia’s thesis explores how Stanford students of the 1920s and 1930s constructed and discussed heterosocial and heterosexual relationships, gender roles and expectations, and definitions of consent. After reconstructing the physical campus, its history with regards to coeducation, and the administration’s role in student life, the paper reveals that students engaged in a culture later coined “rating and dating,” which was intensely public facing and reliant on the conspicuous consumption of the Roaring 20s. Further, students were sexually active and open about their sexuality, both with each other and in publications. Finally, they conceived of female sexuality as a publicly determined entity, and female consent as constantly given. This culture is likely the foundations of the culture in which Brock Turner committed assault.

Keywords: Education, Higher
College student newspapers and periodicals
Sex customs
Dating (Social customs)
Sexual consent
Text
Thesis
Advisor: Olivarius Kathryn
Winterer Caroline
The consequences of hiring and job search practices for inequality

My dissertation contributes to the sociology of gender and labor markets, specifically focusing on how the job search and hiring stages contribute to gender disparities in labor market outcomes. In the first paper, Poach or Promote: Job Sorting and Earnings Inequality across U.S. Industries, I take a macro lens at the industry-quarter level to study the association between an increasingly common hiring practice -- the use of firm-external hires rather than firm-internal promotions to fill positions -- and the gender earnings gap. In the second paper, Gender Differences in the Geographic Breadth of Job Search: Examining Job Applications, I move to explore gender differences in the geography of job search to identify gender-based mechanisms on the worker supply-side of the job-matching process. In the third paper, Make it a Number: Quantification in Hiring Evaluation, I turn firmly to the demand-side and use an original experiment to investigate how hiring bias has disparate effects on men and women. These papers weave a story of women's lingering inequality in the labor market and its relationship with persistent gender bias at the hiring stage

Keywords: Humanities and Sciences.
Sociology.
Advisor: Powell Walter W.
Kiviat Barbara
Pedulla David S.
Torche Florencia
The construction of a constitutional court in an emerging democracy : the Mexican supreme court (1994-2018)

This study presents a general account of the evolution and the transformations of the Mexican Supreme Court since the major constitutional reform of 1994. To do so, this study relies on the recent literature that analyzes the concept of legal culture inside high courts to identify a characteristic of the Supreme Court that has received significantly little attention from the general literature, the coexistence in the Supreme Court of justices that developed their professional career inside the federal judiciary, the insiders, and justices that were appointed to the Supreme Court without having any previous professional experience in the federal judiciary, the outsiders. This study argues that these two types of justices, insiders and outsiders, have remarkably different views regarding the role of the Supreme Court in the political life of the country and their role as justices. In this context, this study claims that the coexistence of these two types of justices in the Supreme Court, insiders and outsiders, together with the tensions that the 1994 constitutional reform incorporated to the institutional design of the Supreme Court are essential to understand the evolution and transformations of this institution in the years since the constitutional reform of 1994.

Keywords: Law.
Advisor: Kessler Amalia D.
Meyler Bernadette
Zambrano Diego (Diego Alberto)