Objectives of course (Click here for why)

• Understand how bioinformatics lets us view biology in a new light
• Computer programming, the most basic tool

At whom is the course aimed?

• Bioinformatics majors
• Those who wish to explore bioinformatics as a career option
• Those who wish to add bioinformatics to their intellectual tool box

Strategies (Click on individual items for more explanation)

• Guided tours through many current uses of bioinformatics
• Problem sets
• Collaborative research with members of the scientific community
• Teaching high school biology students

Plausibly Asked Questions (PAQs):

What about me? I don't know anything about computer programming!

What about me? I don't know anything about molecular biology!

What about ME? I DO know {molecular biology|computer programming}.
Am I going to be bored out of my mind?

What is bioinformatics anyway?

• Molecular biology
• Computer science
• Biostatistics
• (others)

 
• Those who wish to use this proficiency as an entry point into bioinformatics

Weekly events

• Focus on a specific scientific problem taken from the literature or from experience
• Introduction of a commonly used bioinformatics tool that can solve the problem
• Explanation of molecular biology concepts necessary to understand the problem
• Explanation of computer programming concepts necessary to construct, modify, and thereby understand the tool
• Problem sets designed to introduce new concepts, integrate them within a real life context, and to solve the problem at hand

What about me? I don't know anything about computer programming!

First of all, programming is a lot easier than you think, so long as you don't have to worry about complicated user interfaces. Second, a little knowledge can go a long way. There's quite a lot you can do through simple programs or modifying programs written by others. We will focus on learning how to understand what the critical part of the program is trying to do to the extent that you can change it to do what you want it to do. The course will isolate portions of a program for you to play with, reducing the flow of concepts to a manageable rate.

What about me? I don't know anything about molecular biology!

Fortunately, molecular biology is basically simple, because biological molecules tend to behave the way the world of our daily acquaintance behaves. While there is an incredible amount of molecular biology you COULD learn, you need to know very little of it to understand what's behind a specific biological problem. We'll feed you that little bit each week, and by the end of the semester you'll see that there are core concepts you run across time and again, and there are specific facts that you can readily learn as needed and forget when the time has passed.

What about ME? I DO know {molecular biology | computer programming}.
Am I going to be bored out of my mind?

I doubt it. You who know molecular biology will serve as course TA's to help those who don't. Likewise, you who know computer programming will serve as course TA's for those new to that art. It is doubtful that ANYone will know all of the molecular biology concepts required to understand all the scientific problems, and many of the algorithms we'll cover will be new even to the computer adept. So, as is often the case, those acting as TA's will be ahead of the students by reason of general background rather than a specific knowledge of the problems at hand, and through the act of teaching, the TA's may learn more than the students.

In addition, there will be problems that require joint expertise, requiring the meeting of minds geared towards biology and minds geared towards computers. Problem solving with others of diverse backgrounds may be useful in achieving one objective of the course: to encourage all students to speak and understand the various languages of bioinformatics.

What is bioinformatics anyway?
One plausible definition:

The application of information technology to the study of biological problems

Biological problems include understanding the behavior of a cell, the progress of a disease, or the functioning of an ecosystem. Information technology include the tools that have been developed to analyze and manipulate large data sets, such as genomic sequences, determination of levels of RNA transcripts or proteins, and enzymatic activities. Data may be approached from the top down, parsing and analyzing the huge amount of data to produce quantities that we can more easily grasp, or from the bottom up, combining derived quantities according to a model to try to recreate a complex part of reality.