Global Arc

This course will provide an overview of several theoretical orientations to psychotherapy and critically evaluate how the effects of therapies are measured and studied. Cognitive-behavioral approaches to psychotherapy will be explored in depth. 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.

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 applied statistics and data science for those interested in pursuing data-driven research. The course may involve examples from any area of science, but it places a special emphasis on modern biological problems and data sets. Topics may include data wrangling, exploration and visualization, statistical programming, likelihood based inference, Bayesian inference, bootstrap, EM algorithm, regularization, statistical modeling, principal components analysis, multiple hypothesis testing, and causality. The statistical programming language R will be extensively used 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.

How have religious traditions addressed the relationship between human and non-human animals, and between non-human animals and the divine? What is the connection between representations of dominion over animals in religious texts, and the subjugation of women, the "racial" other, and marginalized peoples? Our focus will be on the ways in which non-human animals, real or imagined, have figured in the religious and moral traditions, as well as the cultural practices, of the Middle East and the west, from ancient times to the present. Course includes guest speakers and engagement with animal welfare groups that focus on religion/animal welfare.

A survey of themes central to theologies in the period from Augustine to the end of the Middle Ages, issues of theological method, genre, and linguistic medium; doctrines of God, the Trinity, Incarnation and grace; the place of the Bible and its interpretation in medieval theology. Throughout all of these, it will be necessary to bear in mind in general terms, and explore in each of these texts in some detail, a series of overarching, and governing, connections: between the theological and the 'mystical', contemplation and action, intellectual enquiry and holiness, knowledge and love.