printer friendly pageBIOE 279: Computational Biology: Structure and Organization of Biomolecules and Cells (BIOMEDIN 279, BIOPHYS 279, CME 279, CS 279)
Computational techniques for investigating and designing the three-dimensional structure and dynamics of biomolecules and cells. These computational methods play an increasingly important role in drug discovery, medicine, bioengineering, and molecular biology. Course topics include protein structure prediction, protein design, drug screening, molecular simulation, cellular-level simulation, image analysis for microscopy, and methods for solving structures from crystallography and electron microscopy data. Prerequisites: elementary programming background (
CS 106A or equivalent) and an introductory course in biology or biochemistry.
Terms: Win
| Units: 3
BIOMEDIN 215: Data Driven Medicine
The widespread adoption of electronic health records (EHRs) has created a new source of ¿big data¿¿namely, the record of routine clinical practice¿as a by-product of care. This graduate class will teach you how to use EHRs and other patient data to discover new clinical knowledge and improve healthcare. Upon completing this course, you should be able to: differentiate between and give examples of categories of research questions and the study designs used to address them, describe common healthcare data sources and their relative advantages and limitations, extract and transform various kinds of clinical data to create analysis-ready datasets, design and execute an analysis of a clinical dataset based on your familiarity with the workings, applicability, and limitations of common statistical methods, evaluate and criticize published research using your knowledge of 1-4 to generate new research ideas and separate hype from reality. Prerequisites:
CS 106A or equivalent,
STATS 60 or equivalent. Recommended:
STATS 216,
CS 145,
STATS 305
Terms: Aut
| Units: 3
BIOMEDIN 279: Computational Biology: Structure and Organization of Biomolecules and Cells (BIOE 279, BIOPHYS 279, CME 279, CS 279)
Computational techniques for investigating and designing the three-dimensional structure and dynamics of biomolecules and cells. These computational methods play an increasingly important role in drug discovery, medicine, bioengineering, and molecular biology. Course topics include protein structure prediction, protein design, drug screening, molecular simulation, cellular-level simulation, image analysis for microscopy, and methods for solving structures from crystallography and electron microscopy data. Prerequisites: elementary programming background (
CS 106A or equivalent) and an introductory course in biology or biochemistry.
Terms: Win
| Units: 3
BIOPHYS 279: Computational Biology: Structure and Organization of Biomolecules and Cells (BIOE 279, BIOMEDIN 279, CME 279, CS 279)
Computational techniques for investigating and designing the three-dimensional structure and dynamics of biomolecules and cells. These computational methods play an increasingly important role in drug discovery, medicine, bioengineering, and molecular biology. Course topics include protein structure prediction, protein design, drug screening, molecular simulation, cellular-level simulation, image analysis for microscopy, and methods for solving structures from crystallography and electron microscopy data. Prerequisites: elementary programming background (
CS 106A or equivalent) and an introductory course in biology or biochemistry.
Terms: Win
| Units: 3
CME 211: Software Development for Scientists and Engineers
Basic usage of the Python and C/C++ programming languages are introduced and used to solve representative computational problems from various science and engineering disciplines. Software design principles including time and space complexity analysis, data structures, object-oriented design, decomposition, encapsulation, and modularity are emphasized. Usage of campus wide Linux compute resources: login, file system navigation, editing files, compiling and linking, file transfer, etc. Versioning and revision control, software build utilities, and the LaTeX typesetting software are introduced and used to help complete programming assignments. Prerequisite: introductory programming course equivalent to
CS 106A or instructor consent.
Terms: Aut
| Units: 3
Instructors:
Peles, S. (PI)
;
Santucci, A. (PI)
;
Ammerlaan, R. (TA)
...
more instructors for CME 211 »
Instructors:
Peles, S. (PI)
;
Santucci, A. (PI)
;
Ammerlaan, R. (TA)
;
Li, R. (TA)
;
Rivet, M. (TA)
;
Wetstone, J. (TA)
CME 279: Computational Biology: Structure and Organization of Biomolecules and Cells (BIOE 279, BIOMEDIN 279, BIOPHYS 279, CS 279)
Computational techniques for investigating and designing the three-dimensional structure and dynamics of biomolecules and cells. These computational methods play an increasingly important role in drug discovery, medicine, bioengineering, and molecular biology. Course topics include protein structure prediction, protein design, drug screening, molecular simulation, cellular-level simulation, image analysis for microscopy, and methods for solving structures from crystallography and electron microscopy data. Prerequisites: elementary programming background (
CS 106A or equivalent) and an introductory course in biology or biochemistry.
Terms: Win
| Units: 3
CS 11SI: How to Make VR: Introduction to Virtual Reality Design and Development
In this hands-on, experiential course, students will design and develop virtual reality applications. You'll learn how to use the Unity game engine, the most popular platform for creating immersive applications. The class will teach the design best-practices and the creation pipeline for VR applications, and will include tangents that explore sister fields such as augmented reality and 360 video. Students will work in groups to present a final project in building an application for the Oculus Go headset. Enrollment is limited and by rolling application only. Prerequisite:
CS 106A or equivalent.
Terms: Aut, Win, Spr
| Units: 2
Instructors:
Borenstein, J. (PI)
CS 41: Hap.py Code: The Python Programming Language
The fundamentals and contemporary usage of the Python programming language. Primary focus on developing best practices in writing Python and exploring the extensible and unique parts of Python that make it such a powerful language. Topics include: data structures (e.g. lists and dictionaries) and characteristic pythonic conventions such as list comprehensions, anonymous functions, iterables, and powerful built-ins (e.g. map, filter, zip). We will also cover object-oriented design, the standard library, and common third-party packages (e.g. requests, pillow). Time permitting, we will explore modern Python-based web frameworks, data science toolkits (numpy, scipy, pandas) and project distribution. Prerequisite: 106B/X or equivalent. Application required.
Terms: Win
| Units: 2
Instructors:
Cain, J. (PI)
;
Redmond, S. (SI)
CS 43: Functional Programming Abstractions
This course explores the philosophy and fundamentals of functional programming, focusing on the Haskell language, its theoretical underpinnings, and practical applications. Topics include functional abstractions (function composition, higher-order functions), immutable data structures, type systems, and various functional design patterns (monads, etc). Prerequisites:
CS107 (or equivalent experience)
Terms: Win
| Units: 2
Instructors:
Cain, J. (PI)
CS 51: CS + Social Good Studio: Designing Social Impact Projects
Introduces students to the tech + social good space. Students work in small teams to develop high-impact projects around problem domains provided by partner organizations, under the guidance and support of design/technical coaches from industry and non-profit domain experts. Main class components are workshops, community discussions, guest speakers and mentorship. Studio provides an outlet for students to create social change through CS while engaging in the full product development cycle on real-world projects. The class culminates in a showcase where students share their project ideas and Minimum Viable Product prototypes with stakeholders and the public. Prerequisite:
CS 147, equivalent experience, or consent of instructors.
Terms: Win
| Units: 2
Instructors:
Cain, J. (PI)
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