Archive for the ‘Biostatistics’ Category


Friday, December 27th, 2013

Galaxy: Data Intensive Biology For Everyone

From the website:

Galaxy is an open, web-based platform for data intensive biomedical research. Whether on the free public server or your own instance, you can perform, reproduce, and share complete analyses.

From the Galaxy wiki:

Galaxy is an open, web-based platform for accessible, reproducible, and transparent computational biomedical research.

  • Accessible: Users without programming experience can easily specify parameters and run tools and workflows.
  • Reproducible: Galaxy captures information so that any user can repeat and understand a complete computational analysis.
  • Transparent: Users share and publish analyses via the web and create Pages, interactive, web-based documents that describe a complete analysis.

This is the Galaxy Community Wiki. It describes all things Galaxy.

Whether you are a home bio-hacker or an IT person looking to understand computational biology, Galaxy may be a good fit for you.

You can try out the public server before troubling to install it locally. Assuming you are paranoid about your bits going over the network. 😉

Methods in Biostatistics I [Is Your World Black-or-White?]

Saturday, July 13th, 2013

Methods in Biostatistics I John Hopkins School of Public Health.

From the webpage:

Presents fundamental concepts in applied probability, exploratory data analysis, and statistical inference, focusing on probability and analysis of one and two samples. Topics include discrete and continuous probability models; expectation and variance; central limit theorem; inference, including hypothesis testing and confidence for means, proportions, and counts; maximum likelihood estimation; sample size determinations; elementary non-parametric methods; graphical displays; and data transformations.

If you want more choices than black-or-white for modeling your world, statistics are a required starting point.

Pro Tips for Grad Students in Statistics/Biostatistics [Multi-Part]

Saturday, November 17th, 2012

A recounting of “pro-tips” on becoming a practicing applied statistician.

You may nod along or think some of them are “obvious.” Ask yourself, how many of these tips, adapted to your field, did you put into practice in the last week/month?

Don’t feel bad, I’m right there with you. But trying to do better.

Pro Tips for Grad Students in Statistics/Biostatistics (Part 1)

Pro Tips for Grad Students in Statistics/Biostatistics (Part 2)

Pro-tips for graduate students (Part 3)

Pro-tips for graduate students (Part 4)

Bonus question: What pro-tips would you give to students who want to pursue semantic technologies, including topic maps?