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1 - 9 of 9 results for: BIOS ; Currently searching summer courses. You can expand your search to include all quarters

BIOS 226: Web3, AI, and Digital Health

This interdisciplinary course explores the convergence of Web3 technologies, artificial intelligence (AI), and their transformative impact on the field of digital health. Students will examine the potential of decentralized systems, blockchain, and smart contracts to enhance health data privacy, security, and interoperability. Through case studies and hands-on projects, they will gain insights into AI-driven solutions for personalized healthcare, remote patient monitoring, medical image analysis, and clinical decision support. Additionally, students will critically analyze ethical and regulatory considerations in the context of Web3 and AI applications, fostering a deeper understanding of the future of digital health innovation.
Terms: Win, Sum | Units: 1

BIOS 247: Whole-genome sequencing and applications: from yeast to fruit flies

Analyzing Illumina whole-genome sequencing data is an integral part of many fields of biology research, but finding and implementing a computational pipeline can be difficult for newcomers. We will provide experimental evolution data generated from our studies of yeast and fruit flies. Students will learn to process raw sequencing data, determine mutations, and plot results, including Manhattan plots. Prerequisite: some experience/background in molecular biology.
Terms: Win, Sum | Units: 2

BIOS 300: Advance 1

The goal of the course is to develop the graduate student¿s skills in science communication, active reading skills, and general career and professional development in skillsets that are vital for the success of Biosciences PhD students. Meeting will focus general Tools of Success, Laboratory Rotation expectations and developing a mentor/mentee relationship with advisors. Students will also actively participate in NSF Grant writing, Scientific Journal Article analysis, and Applied Quantitative Reasoning workshops. Lastly, students will engage with representees from on-campus resources such as the BioSci Careers office and Industry partners for post-graduate career options.
Terms: Sum | Units: 1
Instructors: Monroy, M. (PI)

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 401: Phase Separation in Biology

Cellular phase transitions underlie the formation of membrane-less compartments enabling cellular organization. While the existence of membrane-less organelles, such as nucleoli, stress granules, and Cajal bodies had been known for a long time, it had remained largely unclear until recently how they were formed, maintained, and regulated. Recent advances have shown how phase separated condensates underlie many cellular processes such as in immune response and neuronal synaptic signaling, and genome organization.Many of the available literature is difficult to follow as one needs an understanding of polymer physics, cell-biology, and biomolecular interactions to fully grasp phase separation in biology. In this course, we will start from fundamental polymeric understanding of phase separation and build from there towards phase separation of biomacromolcules in-vitro followed by in-vivo condensation and how biomolecular condensates can affect cell-biology
Terms: Sum | Units: 1

BIOS 403: Field Genomics: Long-Read Sequencing at Jasper Ridge Biological Preserve

Field Genomics is a course intended to expose advanced undergraduates/graduate students to principles of Oxford Nanopore sequencing through participating in a guided research project at Jasper Ridge Biological Preserve (JRBP). Students will have the opportunity to design and answer their own research questions - which may be specific to the biology of JRBP - via contemporary long-read sequencing techniques. These include but are not limited to collecting samples, extracting and purifying DNA libraries, sequencing using the MinION, and analyzing data.
Terms: Sum | Units: 1

BIOS 404: Time Series Analysis for Neuroscience Data Using State Space Models

This course will present the basics of state space modeling to analyze time series data that are frequently encountered in neuroscience problems. The course lectures will cover linear state space models, Markov chains, switching state space models, and algorithms for learning and inference. Students and instructors will work through practical data analysis exercises in Python in weekly labs and recitation sections.
Terms: 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
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