Global Arc

This course will explore how people believe and how what they believe impacts their behavior. How do people change their beliefs? What factors facilitate the endorsement of conspiracy theories? How do people influence each other's beliefs during communication? How do beliefs propagate through social networks? This course will also explore a multidisciplinary framework to understand the endorsement and propagation of true and false beliefs through social networks. One three-hour seminar.

This course will provide an overview of several theoretical orientations to psychotherapy and critically evaluate how the effects of therapies are measured and studied. Application of research findings to clinical practice will be examined closely, including issues related to psychotherapy integration and the treatment of diverse populations in various settings. The course will also include reviews of the current state of psychotherapy research for a number of psychological disorders and consider current controversies in the area of treatment outcome research. One three-hour seminar.

This seminar explores parallels between human cognition and ideas in probability and statistics, with an emphasis on statistical machine learning. Minds and machines face similar computational problems, meaning that we can develop new hypotheses about human cognition by seeing how those problems are solved in computer science and statistics and find new challenges for AI and machine learning by studying human cognition.

An overview of research topics and methods in quantitative biology through reading and discussion of primary literature. Students read two papers weekly, each showcasing how modern experimental and analytical techniques are applied to address basic questions in biology with a strong focus on big data. Students examine the achievements and impact of each study, present context and background, dissect experimental and analytical approaches, and highlight remaining challenges. Topics range from gene regulation and organellar dynamics to virology and cancer genomics. Prereqs: MOL 214 or equivalent or permission of the instructors.

Advances in molecular biology and computation have propelled the study of genomics forward, including how genes are organized and how their regulation manifests complex phenotypes. A hallmark of genomics is the production and analysis of large data sets. This course will pair an overview of genomics with practical instruction in the analytical techniques required to use it in research and medicine. We will start with a primer on genetics and an introduction to programming using Python. The goal of this course is to provide a foundation for understanding the data heavy experiments that are increasingly common in biomedical research.

This course establishes a foundation in statistical modeling of genomic data. There is an emphasis on applications in population genetics, gene expression, and human genomics. There is also an emphasis on careful consideration and development of statistical models. Statistical topics may include probabilistic and theoretical models, likelihood based inference, Bayesian inference, principal components analysis, multiple hypothesis testing, and causality. The statistical programming language R is utilized to explore methods and analyze data.

This interdisciplinary course provides a broad overview of computational and experimental approaches to decipher genomes and characterize molecular systems. We focus on methods for analyzing "omics" data, such as genome and protein sequences, gene expression, proteomics and molecular interaction networks. We cover algorithms used in computational biology, key statistical concepts (e.g., basic probability distributions, significance testing, multiple testing correction, performance evaluation), and machine learning methods which have been applied to biological problems (e.g., classification techniques, hidden Markov models, clustering).

Aging is a fascinating biological phenomenon because it seems inevitable, yet recent research suggests that longevity can be manipulated through genetics and environment. Moreover, aging is the major risk factor for a host of chronic and neurological diseases; thus, understanding the molecular regulation of aging will be critical in addressing these health issues in the future. We will explore the current state of the field, including genetic discoveries of longevity mutants, cell biological and metabolic characterization of aging animals, and genomic and computational analyses used to uncover molecular mechanisms that control longevity.

This course introduces students to the interdisciplinary study of religion and its engagement with society and culture. We will identify where and how religion operates in the public conversation, especially in, but not limited to, the United States. Classes will be focused around topics that intersect with religion in the public conversation such as place, media, race, body, art, and ethics. Students will develop recognition of the different ways people use religion to construct meaning, boundaries, and identity and will demonstrate the ability to engage in informed dialogue around issues of religion.

When the Reverend Martin Luther King, Jr. took inspiration from Gandhi's Hindu doctrine of [ahimsa], he was drawing upon many centuries of "East-West" dialogue. Gandhi himself owed the idea in large part to Tolstoy, who for his part had found his Christian beliefs reshaped through studying Asian religions. This course traces an intellectual history of the modern doctrine of nonviolence, emphasizing its emergence through transnational, multi-religious dialogue. Topics include nonviolence in Jainism, Buddhism and Hinduism; Hume and Spinoza; Max Müller; Theosophy and South Asian religious reformers; Transcendentalism; Tolstoy, Gandhi, and King.