Results for BIOS

The course will focus on computational approaches to ensure that all data, code, and analyses can be captured in a reproducible workflow, to be confirmed and replicated by you in the future, by other members of your team, and by reviewers and other researchers. We will cover how to satisfy FAIR principles, version control, how to create a git repository, utilize Github and how to create a reproducible dataset. Prerequisites: Basic knowledge of R. Recommended (not required): EPI 202 or 261/262, STATS 60, or MS&E 125.

This course will provide students with an overview of current technologies related to the development of small molecules and neutralizing antibodies. Delivered via classroom instruction and a workshop, these modules will aim to increase the fundamental understanding of drug development terminology and processes, combined with real-world examples of discovery therapeutics and technologies developed for translation to clinic. Emphasis will be made on the development of small molecules that can cross the blood-brain barrier and show potential for translation in clinic. Focus will also be put on the screening of antibody targets followed by target validation, target profile development and preclinical evaluation. The workshop will focus on computational molecular docking which is an excellent tool that will help reduce the attrition rate during the drug development process and lead identification studies. Active engagement of the students during the workshop is expected based on the need to install specific software and completion of assigned tasks (computational docking). Students are expected to bring personal laptops to class on day 1 and 2 to perform docking exercises.

This mini-course offers a series of lectures and hands-on labs to discuss the development and reporting of reproducible quantitative LC-MS/MS molecular assays using a triple quadrupole. We will discuss chromatography and mobile phase selection, mass spectrometry parameters and selection of fragment ions, and the reporting and interpretation of published methods. Additionally we will cover the use of internal standards and sample preparation, and normalization methods for reproducible data analysis. Students will have the opportunity to work with a mass spectrometer and will design a cohesive plan for a targeted assay of an example molecule in their research.

A variety of stem cells harbor different properties appropriate for various types of research. We will cover the molecular characteristics of totipotent, pluripotent, multipotent, and unipotent stem cells. This knowledge will form the foundation for us to explore the use of stem cells in developmental biology and translation research. As an application, we will focus on genome editing technologies and in vitro models of cardiovascular disease.

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.

Focus on designing and analyzing effective proteomics experiments using mass spectrometry and critically evaluating published mass spectrometry-based studies and datasets. Introduces students to the instrumentation, experimental strategies, and computational methods used for identifying and quantifying proteins and protein post-translational modifications using mass spectrometry. Topics include comparative evaluation of mass spectrometer instrument configurations, tandem mass spectrum interpretation, relative and absolute quantitation, and proteome-scale data set analysis. Laboratory time will focus on sample preparation methods, real-time data acquisition, and data analysis software and techniques. Note: Students should sign up for the morning lecture and one of two lab sections in the afternoon.

Everyone has fears presenting in front of a crowd. But with practice, self-awareness and preparation you can put those fears aside and make a real impact with your message. Utilizing professional theater practices and tricks, this course is a deep dive into what makes a presentation work. Get a chance to explore your own presentation style and address your questions and challenges with public speaking in a safe and fun space. The course is taught by Michileen Marie Oberst, a Professional director and actor in the Bay Area whose background includes teaching at the Tony Award winning TheatreWorks Silicon Valley.

This 3-week course will help students understand how lifestyle and wellness choices impact physiology using a data-driven approach powered by wearable technology. Each student will be given an Oura ring to use during the course. On Mondays and Wednesdays, we will learn evidence-based practices for mental health and well-being, and on Fridays engineers from Oura, Apple, and Fitbit will teach the students about wearable data sensors and analysis. Students will assess their own smartwatch data to look at real-time physiological responses to wellness interventions such as exercise, awareness meditation, laughter yoga, and inquiry-based stress reduction. This course will bring in academic experts and popular wellness leaders. Last year's teachers included Byron Katie, Deepak Chopra, MD, Madan Kataria, MD the founder of Laughter Yoga, Michael Snyder, PhD, James Doty, PhD, Lindsay Briner, and George Slavich, PhD, to learn about cutting edge research and innovation in mental health, and to experience these practices firsthand through immersive workshops. The capstone project of the course will involve analyzing your own personal wearable device data to quantify the physiological impact of BIOS 237. Due to the high demand for this unique three-week course, we are accepting students on a first-come, first-served basis. Complete and confirm the form promptly to secure your spot: https://forms.gle/TRMRJJ1qHA8MypF79 Learn more at engineeringwellness.stanford.edu.

This mini-course will explore the ¿What¿ and ¿Why¿ of sleep, with emphasis on the role of sleep in human health and wellbeing. Sleep is universal in Nature, but there is still no consensus on its function. Over 3 weeks, students will study the foundations of sleep science through a combination of lecture and discussion of published research articles. The course will approach the topic of sleep and health from multiple levels¿ brain, body, mind, and society. Topics will include: sleep and circadian physiology, sleep science methodologies, functions of sleep, and the impact of social factors on sleep health.

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.

Publishing research findings is a vital part of the scientist skill set. With the advent of big data and machine learning, understanding the key principles of analyzing, visualizing, and publishing data is becoming increasingly important. This course covers practical skills which are typically only learned in practice or specialized workshops. Topics include the importance, ethics, and pitfalls of data cleaning, analysis, visualization, reporting, and publishing.

This mini-course is designed to equip graduate students and postdocs with essential skills for ensuring reproducibility in computational research. Through practical exercises and interactive sessions, participants will learn best practices, tools, and techniques for doing open and reproducible research. Topics covered include version control, containerization, data management, workflows, and documentation strategies. This course empowers students to overcome challenges associated with reproducibility, fostering rigorous scientific inquiry, and enhancing the credibility and impact of their computational work, while also exploring the primary causes and consequences of irreproducibility in research. Participants will gain valuable insights and practical experience in achieving computational reproducibility across various domains, including biology. Prerequisites: Basic familiarity with programming (e.g., Python, R); Basic knowledge of Unix/Linux Bash

This 3-week mini-course will dive into the biology of non-model organisms, and the approaches we can use to study them. Traditionally in Biology, model organisms have been used to answer new questions. Yet, studying a more diverse array of organisms can lead to new discoveries. We will explore the world of non-model Biology through a series of short lectures, primary literature discussions, talks from experts working on non-model organisms, and some practical sessions including a field sampling. No prerequisites required.

In an intensive 1-day format, students learn the fundamentals for writing competitive fellowships, i.e. NIH NRSA fellowships (F30, F31, F32). Topics include developing specific aims; outlining research and career development plans; and using the review criteria to inform writing. Students develop early drafts of the 1-page specific aims, NIH biosketch, and training plan, and receive feedback from instructor. Students are expected to be in the early stages of writing a fellowship proposal.

This 3-week mini-course will cover a variety of topics related to science and art including scientific illustration, the visual sensory perception of art, how art impacts the brain, and the similarities and differences between science and art. The class will be a combination of lectures, discussions, and art labs. No previous art experience is necessary.

Tailored lectures and case studies lead to a practical final project. Leaders from local firms and companies will help you gain insight into the biotechnology industry, the skills and experiences necessary to succeed, and the various roles and responsibilities within the industry. Coursework is divided into 4 sections: Introductory Material: The first segment consists of two lectures and introduces the biotechnology company life cycle along with introductory concepts in finance. Venture Capital and Private Equity: The second segment consists of three lectures devoted to venture capital finance and private equity where students will learn the basic mechanics of raising capital. nPublic Finance: The third segment consists of the interpretation of financial statements, construction of company forecasts, and evaluating business value from such projections. Final Project: The final lecture will conclude with student presentations on their final projects.

This mini-course will introduce students to the basic concepts and methods of biostatistics and how they are applied to analysis and interpretation of data in clinical research. Topics will include: Study designs: Observational studies and Clinical trials, Bias and confounding during study design and analysis phases, Hypothesis formulation and Power analysis, Data collection and management, Descriptive and Inferential statistics, Hypothesis testing: Data analysis, interpretation, and presentation, Role of Research Rigor and reproducibility. Students will learn how to use statistical software to analyze data and draw conclusions from their analyses. They will also learn how to communicate their findings to others in a clear and concise way.

Design a fulfilling and impactful vision for your career and life as a whole. The primary purpose of the class is to develop a perspective and align your attitudes, actions and experiences with your values, priorities, and your own ultimate definition of victory for living an extraordinary life. A practical guide for career development, this class will provide training through conversations, self-analysis, and writing exercises on career direction, communication, and the development and leveraging of relationships skills that are central to success in any career as a scientist. We will examine what it means (and what it takes) to succeed in a variety of life domains, including money, health, career, relationships, and physical fitness as well as personal growth. We will dig into the darker side of being human, exploring phenomena like negative character traits, fears, hauntings, and regrets. Ultimately, we want you to gain insight into who you are, what you want most, and how you might inadvertently and unwittingly get in your own way. We want you to learn how to confront the most vexing issues in your life, learn from them, and eventually transform your relationship to them. Course Structure: The course consists of ten intensive, flipped-classroom sessions designed to help you develop the skills and knowledge--and, more importantly, the insight and capacity--to be more strategic and effective in how you lead your life. It requires a willingness to be introspective and to consider personal feedback and constructive confrontation. Enrollment is capped at 30 learners, all of whom will be provided subscriptions to Inner.U which will serve as an electronic textbook and supported by a team of three faculty facilitators.