BIO/CSC295 2011F, Class 22: Project Kickoff

Overview:
* Short review of project issues.
* Time to work on projects!
  * Discuss reviews
  * You need data to work with!
    * Training
    * Test
    * Exploratory
  * There are "literatures"
    * On the biology side
    * On the bioinformatics side

Admin:
* Discussion of drops and such.
* Change in schedule: Time for you to discuss reviews in your groups 
  and then start to respond.
* What form should your reviews be?  Whatever is easier for you.  
  Paper or email.
* Thursday: Visit in class by Jillian Goetz '10.
* Thursday at 4:15: Chats with Jillian Goetz
* EC Thursday at noon: Biology seminar on cool stuff
* EC for Swim Meet Saturday @ 1pm in RKO
* EC for first meeting of G-FOSS Club 4:15 next Monday
  * Goals to be determined - Do we build a new project, do we support
    an existing project, how do we support an existing project?
    * Geek speek: i18n is always a good thing to do; as is a11y
* EC for Latin-American festival on Friday
* EC for another installment of FreeSound concert series; punk
  Gardner 9pm Saturday, but only if you abstain from alcohol all day
  Saturday, including the party
* EC for Fetish Harris, but only if you abstain from alcohol all day
  Saturday, including the party
* EC for Collegium Concert Sunday at 2pm

Thoughts about your proposals
* Beginning of class issues: 
  * Do a thorough literature search.  
    * Search both biology and bioinformatics literature.
    * It is hard to frame an approach without contextualizing it  and
      understanding the context.
  * Data, data, and more data.
* The better sense you have of your project and its context, the more
  successful you will be.
* Typical form for a project proposal 
  * Some background; What is the domain; Why is it important; What have
    people already done.
  * What is the central question you are addressing
  * Methods - What are the steps you'll do?  How do you get between these
    steps?
  * Example
* Other things 
  * Break it down into sections with headers
    * Help yourself organize things
    * Help your reader understand how you've organized things
  * Define your terms carefully
  * Clarity on data sets (perhaps even including sources)
* Submitted project
  * Research paper
  * Reflections
* Can we share code?
  * Of course, provided you cite.
* Make sure to cite in general.
  * Including sources of data and common algorithms.

Post-wandering reflections.
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