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1 - 10 of 24 results for: BIOS ; Currently searching offered courses. You can also include unoffered courses

BIOS 200: Foundations in Experimental Biology

This course is divided into two 3-week cycles. During the first cycle, students will be developing a 2-page original research proposal, which may be used for NSF or other fellowship applications. In the second cycle, students will work in small teams and will be mentored by faculty to develop an original research project for oral presentation. Skills emphasized include: 1) reading for breadth and depth; 2) developing compelling, creative arguments; 3) communicating with the spoken and written word; 4) working in teams. Important features of the course include peer assessment, interactive joint classes, and substantial face-to-face discussion with faculty drawn from across the Biosciences programs. Shortened autumn quarter class; class meets during weeks 1 through 8 of the quarter.
Terms: Aut | Units: 5

BIOS 201: Next Generation Sequencing and Applications

Usher in the golden age of biological discovery with next generation sequencing (NGS) through its wide spectrum of applications. Modules include general introduction of Next Generation Sequencing (NGS) technologies, applications of these sequencing technologies, caveats and comparisons with previous approaches, analysis and interpretation of sequencing data, principles of tools and resources and practical ways to utilize them, and features and pitfalls. Prerequisite: background in molecular biology.
Terms: Win | Units: 2
Instructors: Li, J. (PI)

BIOS 204: Practical Tutorial on the Modeling of Signal Transduction Motifs

Basics of ordinary differential equation modeling of signal transduction motifs, small circuits of regulatory proteins and genes that serve as building blocks of complex regulatory circuits. Morning session covers numerical modeling experiments. Afternoon session explores theory underpinning that day's modeling session. Modeling done using Mathematica, Standard Edition provided to enrolled students.
Terms: Aut | Units: 3
Instructors: Ferrell, J. (PI)

BIOS 205: Introduction to R for Data Analysis

Autumn quarter enrollment limited to ADVANCE students; instructor consent required for enrollment. Topics include: basics of R (widely used, open-source programming and data analysis environment) programming language and data structures, reading/writing files, graphics tools for figure generation, basic statistical and regression operations, survey of relevant R library packages. Interactive format combining lectures and computer lab. For course and enrollment information, see https://web.stanford.edu/~sbagley2/bios205/
Terms: Aut | Units: 1
Instructors: Bagley, S. (PI)

BIOS 221: Modern Statistics for Modern Biology (STATS 366)

Application based course in nonparametric statistics. Modern toolbox of visualization and statistical methods for the analysis of data, examples drawn from immunology, microbiology, cancer research and ecology. Methods covered include multivariate methods (PCA and extensions), sparse representations (trees, networks, contingency tables) as well as nonparametric testing (Bootstrap, permutation and Monte Carlo methods). Hands on, use R and cover many Bioconductor packages. Prerequisite: Minimal familiarity with computers.
Terms: Sum | Units: 3
Instructors: Holmes, S. (PI)

BIOS 225: Diversity and Inclusion in Science

Introduction to the social science literature on factors contributing to gender disparities in the scientific workplace (e.g. implicit bias and stereotype threat). Discussions focus on steps that individuals and institutions can take to promote the advancement of women and other underrepresented groups in science, and thus promote the advancement of science.
Terms: Win | Units: 1
Instructors: Goodman, M. (PI)

BIOS 242: Writing Compelling Fellowships and Career Development Awards

An overview of principles and fundamentals for writing competitive fellowships (e.g. NIH F31, F32) and career development awards (e.g. NIH K Awards). Topics include: developing specific aims and career development plans; using the review criteria to inform writing; timelines and resources. Participants develop proposals through guided exercises with an emphasis on in-class peer review and focused faculty feedback.
Terms: Aut | Units: 2
Instructors: Botham, C. (PI)

BIOS 254: DataLucence::Images

Increasingly, research in the biosciences involves data in digital formats and scientists spend a significant fraction of their time building and using software to harvest insight from digital data. A central goal of this course is to expose students to concepts adopted from computer science and data science regarding data management, data curation, and analytical workflows for analyzing digital data. We will focus on digital images since this image type is used in diverse sub-fields in the biosciences. The course will consist of a two-day workshop/lab¿SoftwareCarpentry¿and six DataLucence::Images+Hackathon class meetings.
Terms: Aut | Units: 2

BIOS 256: Sculptural Data Illustrations

Mini-course. Students will use learn make and print 3D models of their data to use as a focal point when describing their project. We will teach the students how to use Autocad and Blender to process existing data sets and students are encouraged to bring their own data. We strive to make wearable models to enable instant mini-lectures any place and anytime.
Terms: Win, Spr | Units: 1

BIOS 257: HIV: The Virus, the Disease, the Research

Mini-Course. Medical students, graduate students in biological sciences, undergraduate students with strong biological background. Topics: Immunopathogenesis, immune deficits, opportunistic infections including TB, and malignancies; Genomics viral genetic analyses that have traced the origin of HIV-1 and HIV-2 to primates, dated the spread of infection in humans, and characterized theevolution of virus within infected individuals; Antiretroviral drug development identification of drug targets, structure-based drug design, overcoming drug resistance; Challenges of vaccine development; Public health strategies.
Terms: Sum | Units: 1
Instructors: Shafer, R. (PI)
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