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Skip to main content. Get your Wikispaces Classroom now:. The easiest way to manage your class. 1 What Python Can Do for You. Why We Program; What We're Learning; What We're Not. The Very Basics: Hello, World! Variables, and Printing. 2 Organizing and Storing Data. Lists, Dictionaries, Tuples, and Sets. Tests, Loops, and Escapes. 3 Making the Computer Make Decisions. Fancy Data Structures: Nested Loops. Reading and Writing from Files. 4 Reading, Writing, Using LOTS of Data; and Using Other People's Code.

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intro-prog-bioinfo-2013 - Session 2.2

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Skip to main content. Wikispaces Classroom is now free, social, and easier than ever. Try it today. Tests, Loops, and Escapes. Using range() in a loop. Nested for loops for complex data structures. Indexing loops with enumerate(). Loop control and escapes with continue. If the protein is located in the membrane, tell me. Q: What's the magic word there? Indeed, the if. Allow your programs to make decisions on their own. Loop and the while. In principle, anything you can do with one you should be able to d...

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intro-prog-bioinfo-2013 - Session 4.2

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Skip to main content. Try Wikispaces Classroom now. Brand new from Wikispaces. Interactive Python: Running code as we go along. So that's it. You're done. We've taught you all the core programming concepts that you'll need for the next week and a half, as well as for most of your life as a person who programs. Every language worth using will have some version of integers, floats, strings, lists, if/else, loops of some kind, and functions. A program (fill the cauldron) gone wrong! One of the ways that we ...

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intro-prog-bioinfo-2013 - Session 5.2

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Skip to main content. Get your Wikispaces Classroom now:. The easiest way to manage your class. Beyond learning to code: Maintaining and Writing programs. Some genomics work has been done on bicyclomycin (BCM) treatment of. What we decided to do was the simplest thing that could possibly work: Look at the transcriptome in three different concentrations of BCM, at two different time points after treatment. Then, we do RNAseq on each of those samples. This is problem isn't specific to just scientists, and ...

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intro-prog-bioinfo-2013 - Session 1.1

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Skip to main content. Try Wikispaces Classroom now. Brand new from Wikispaces. First Morning, Introductions, and Lesson Plans. Your instructors are: Peter Combs, Aisha Ellahi, Debbie Thurtle, Diana Koulechova, Mike Lawson, and Josh Schraiber. Your teaching assistants for the first week are:. Expectations for the course. Navigating the UNIX shell. Viewing the content of files. How to get help. Welcome to the QB3 Introduction to Programming for Bioinformatics bootcamp! 2) What we are not going to cover.

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intro-prog-bioinfo-2013 - home

http://intro-prog-bioinfo-2013.wikispaces.com/home

Skip to main content. Wikispaces Classroom is now free, social, and easier than ever. Try it today. 1 What Python Can Do for You. Why We Program; What We're Learning; What We're Not. The Very Basics: Hello, World! Variables, and Printing. 2 Organizing and Storing Data. Lists, Dictionaries, Tuples, and Sets. Tests, Loops, and Escapes. 3 Making the Computer Make Decisions. Fancy Data Structures: Nested Loops. Reading and Writing from Files. Functions, Modules, and Code Reuse. Numpy, Scipy, and Pylab.

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Curriculum Vitae - Peter Combs

http://www.combslab.net/curriculum-vitae

The Hamming Test (2013). 149; Curriculum Vitae. Peter A. Combs. 378G Stanley Hall, MC 3220. Berkeley, CA 94705. University of California, Berkeley, CA. PhD in Biophysics. 2009-Present. Anticipated Graduation date Winter 2014. Dissertation Title: Genome-wide Spatial Patterning Data Reveal Mechanisms of Gene Regulation; Advisor: Michael Eisen. Princeton University, Princeton, NJ. AB in Physics. With certificate in Quantitative and Computational Biology. Head Teaching Assistant, The Summer Science Program.

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de la Torre Laboratory | SFSU Department of Biology

http://archaea.sfsu.edu/links.html

San Francisco State University. De la Torre Lab. Images from the field. Nitrogen cycle at high temperature. Sacramento and San Joaquin rivers. Old Lab Files *. San Francisco, CA 94132. Last Update: 13 AUG 2010. KorfLab (UC Davis) Unix and PERL Primer for Biologists. Beginning PERL (by Simon Cozen). QB3 Python Course (2013 edition). Summer Course on Microbial Oceanography. Woods Hole Microbial Diversity Course. Woods Hole Course on Strategies and Techniques for Analyzing Microbial Population Structures.

crackingthebiocode.github.io

Resources for learning computer programming

http://crackingthebiocode.github.io/program.html

2014 Professional Development Session. How do I get started learning a programming language? There are a number of different ways you can build proficiency in computer programming. Additionally, there are many different programming languages. You may ask: "what is the best language to learn? Or: "what is the best way to become a good programmer? This page contains links to several resources for learning computational biology skills. Bootcamps for scientific computing organized at many locations. The Summ...

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Skip to main content. Get your brand new Wikispaces Classroom now. And do "back to school" in style. This is a student-run introductory programming class for biologists at UC Berkeley. The course was taught over a period of two weeks, 9am-5pm, with a one-hour lecture, followed by 2.5 hours of exercises, lunch, another 1-hour lecture, and 2.5 more hours of exercises. 1: UNIX and Perl 1. Introduction to linux(LT): navigation, basic commands, piping/redirection. Perl Hello World, Variables, I/O (JF). Module...

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QB3 Python Bioinformatics Course 2010 - home

Skip to main content. QB3 Python Bioinformatics Course 2010. QB3 Python Bioinformatics Course 2010. 1 What Python Can Do for You. Why we program; what we're learning; what we're not. The very basics: Hello, World! Variables, and Printing. 2 Organizing and Storing Data. Lists, Dictionaries, Tuples, and Sets. 3 Making the Computer Make Decisions. Logical tests and the Nature of Truth. 4 Reading, Writing, Using LOTS of Data; and Using Other People's Code. Files: Readin' 'Em and Writin' 'Em. Turn off "Gettin...

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QB3 Python Bioinformatics Course 2011 - home

Skip to main content. Wikispaces Classroom is now free, social, and easier than ever. Try it today. QB3 Python Bioinformatics Course 2011. QB3 Python Bioinformatics Course 2011. 1 What Python Can Do for You. Why We Program; What We're Learning; What We're Not. The Very Basics: Hello, World! Variables, and Printing. 2 Organizing and Storing Data. Lists, Dictionaries, Tuples, and Sets. 3 Making the Computer Make Decisions. Logical Tests and the Nature of Truth. Files: Readin' 'Em and Writin' 'Em.

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QB3 Python Bioinformatics Course 2012 - home

Skip to main content. Get your Wikispaces Classroom now:. The easiest way to manage your class. QB3 Python Bioinformatics Course 2012. QB3 Python Bioinformatics Course 2012. 1 What Python Can Do for You. Why We Program; What We're Learning; What We're Not. The Very Basics: Hello, World! Variables, and Printing. 2 Organizing and Storing Data. Lists, Dictionaries, Tuples, and Sets. Tests, Loops, and Escapes. 3 Making the Computer Make Decisions. Fancy Data Structures: Nested Loops. Numpy, Scipy, and Pylab.

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intro-prog-bioinfo-2013 - home

Skip to main content. Get your Wikispaces Classroom now:. The easiest way to manage your class. 1 What Python Can Do for You. Why We Program; What We're Learning; What We're Not. The Very Basics: Hello, World! Variables, and Printing. 2 Organizing and Storing Data. Lists, Dictionaries, Tuples, and Sets. Tests, Loops, and Escapes. 3 Making the Computer Make Decisions. Fancy Data Structures: Nested Loops. Reading and Writing from Files. 4 Reading, Writing, Using LOTS of Data; and Using Other People's Code.

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intro-prog-bioinfo-2014 - home

Skip to main content. Wikispaces Classroom is now free, social, and easier than ever. Try it today. 1 What Python Can Do for You. Why We Program; What We're Learning; What We're Not. The Very Basics: Hello, World! Variables, and Printing. 2 Organizing and Storing Data. Lists, Dictionaries, Tuples, and Sets. Tests, Loops, and Escapes. 3 Making the Computer Make Decisions. Fancy Data Structures: Nested Loops. Reading and Writing from Files. Functions, Modules, and Code Reuse. Numpy, Scipy, and Pylab.

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