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11 - 18 of 18 results for: BIOS ; Currently searching spring courses. You can expand your search to include all quarters

BIOS 400: (Hidden) Bias in Bioscience

This mini-course will explore how bias influences science at different levels, from entire fields to individual experiments. Students will learn about how biases in biological research limit scientific productivity and knowledge. Classes will consist of short lectures and student-led discussions using case studies from pain research, plus examples from students? own research fields. The class will prioritize active learning and self-examination, and will include a small final project. The goal of the class is for students to come away with a deeper understanding of scientific bias and use that information to critique their own science and dogmas in their field.
Terms: Spr, Sum | Units: 1

BIOS 406: Microfluidics and Organ-on-a-chip in Biomedicine

In this mini-course, we delve into the cutting-edge realm of microfluidics, covering governing physics for fluid flow, various microfabrication techniques and their applications in biomedicine. Topics include microfluidics for cell/particle separation, micromixers, droplet-based microfluidics, and organ-on-a-chip technology. You will gain a deep understanding of the fundamental principles, get knowledge about different microfluidic devices, and explore the world of organ-on-a-chip models for drug screening and disease modeling. This mini-course also includes a hands-on laboratory session where you will have the opportunity to fabricate microfluidic devices and get familiar with experimental setup.
Terms: Spr, Sum | Units: 1

BIOS 407: Essentials of Deep Learning in Medicine

This course delves into the fundamental principles of Deep Learning within the medical field, designed to offer a thorough yet accessible introduction to how these advanced models function, are developed, and are currently transforming healthcare practices. The curriculum covers key areas including neural network architecture, computer vision, natural language processing, convolutional neural networks, alongside classification and regression techniques, aiming to provide students with a solid foundation and intuitive insight into the workings of deep learning applications in medicine.In addition to the core content, participants will have the opportunity to engage with expert-led discussions on the latest advancements and future directions at the intersection of artificial intelligence and medicine.
Terms: Spr, Sum | Units: 1
Instructors: Tanner, J. (PI)

BIOS 409: Brain Dynamics and Connectivity

The course will introduce large-scale spatiotemporal patterns in the neural activities of human brain and their relevance to cognitive functions and neurological diseases. whole-brain neural activities, which can be measured by fMRI or M/EEG, do not fluctuate randomly, but form specific spatiotemporal patterns that are highly reproducible across different conscious states, and are often referred to as functional networks. In the course, the students will learn some of the state-of-art methods of capturing these patterns and evaluate their significance in normal and abnormal brain functions. Zoom attendance is possible but in-person attendance is recommended. There will be in-class practice involving coding and data manipulation, attending in person allows the instructor to help the students debug at the site.
Terms: Spr | Units: 1
Instructors: Lyu, D. (PI)

BIOS 410: Health Innovations for Equity: The basics of design and innovation to create impact

If you?re looking to use your Biosciences knowledge or interests in engineering and medicine to create health innovations that solve some of the world?s most pressing health problems. This course will give you the tools and skills you need to start this process. The course will focus on the basics of user research, design and prototyping for innovations that can have an impact on health equity outcomes. We will take an interdisciplinary approach to solving these problems, and discuss how to build collaborative and inclusive partnerships for health innovations
Terms: Spr | Units: 1
Instructors: Brown, C. (PI)

BIOS 412: Antibody Anywhere All at Once: An Introduction to Techniques in Immunology

This 2-week mini course will provide an introduction to commonly used techniques in immunology. Students will gain the confidence and relevant background to understand current immunology literature and design/analyze their own experiments. Topics for discussion will include flow cytometry, cytokine/antibody assays, animal models, specific sequencing pipelines, and more. Classes will be lecture-based with the opportunity to explore applications of these techniques related to students? own research interests. As this will be an introductory course, all immunology backgrounds are welcome.
Terms: Spr | Units: 1

BIOS 415: Responsible Sharing of Human Research Data

This 3-week mini-course is intended for graduate students and postdocs who are interested in learning how to responsibly share their research data. Through this course, participants will build an in-depth understanding of the benefits of and challenges to sharing research data from human subjects and the current regulatory landscape of research data sharing (e.g., Common Rule, HIPAA, and the new NIH Data Management and Sharing Policy), including data de-identification. By the end of the course, participants will have developed their own plan for data sharing.
Terms: Spr | Units: 1
Instructors: Jwa, A. (PI)

BIOS 416: Matrix Methods and Applications in Biology

Matrix methods provide powerful tools for understanding and managing ecological systems and are frequently used for analysis of population dynamics. This course is intended to introduce matrix model calculus and its implications within an ecological context. This six-day course will be divided into lectures and workshops focused on simplifying matrix methods and for researchers to apply their gained skills on a set of data. Biologists with individual based data (i.e., life history transitions) are encouraged to sign-up. The course is computational based and all levels of RStudio are welcome.
Terms: Spr | Units: 1
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