Blog:"No-coding" Bioinformatics - learn by analyzing public domain data
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6.8 years ago
elia.brodsky ▴ 340

Over the past few months, our team has been working on courses and projects that we hope can make bioinformatics more accessible. Many courses are focused on “how” - how to install scripts, run pipelines, learn statistical methods. That’s great, but often the technical part is so early in the learning process, it prevents the student from understanding the “why” - the reason motivating a student to get through the difficult parts. Because let’s admit it, bioinformatics has plenty of “difficult parts” and they are not always the most important ones!

Introducing…. (drumroll)

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As we get ready to launch (and we’ve been telling ourselves we should be ready for a while now…), we need your help! Yes, your help is urgently needed to help millions of non-bioinformaticians get their hands on the wonderful public domain data that has been collecting dust at the NIH servers. For now, we made 2 fairly basic courses - one an introductory course and another one is all about next generation sequencing. We plan to complete courses on many other data types as well, but we first need to make sure the site is working and people outside our team can complete the courses successfully.

What needs testing:

We want to make sure that the simple technical aspects of our site function properly for our users, such as loading pages, playing videos, completing quizzes, navigating between pages, etc. We also want to that the concepts are clear to users and one can follow the course as it develops.

We will use the tester’s comments for course optimization, integrating as much feedback as possible into the design of our program. We are seeking feedback on technical bugs, course content, and are open to suggestions for improvements. After taking our courses, kindly record any information you would like to provide in our user survey here:

If you know others seeking skills development in bioinformatics and data analysis, please forward our initiative. We welcome all who are interested to join our team of beta testers.

Why you (and your friends) should care:

This is not just about science. Bioinformaticians are also known as “Data Scientists” for biomedical data. As we hear every day, data science is a fast-growing branch of the technology landscape, and with IT and analytic skills highly sought after by employers data scientists pull in hefty salaries for their expertise. According to a 2016 report from the BIO International Convention, the U.S. bioscience industry employs 1.66 million people, a figure that includes nearly 147,000 high-paying jobs created since 2001. The average annual wage for a U.S. bioscience worker reached $94,543 in 2014, a whopping $43,000 greater, on average, than the overall U.S. private sector salary. There is an urgent need for quick, cost-effective, and accurate data analysis in the field of biomedical research as well.

Russ Altman of the Altman Lab at Stanford puts it like this:

“Now there are these amazing data sets from extremely clever experimentalists who've figured out how to do things in high-throughput [experimentation], and they represent a substantial challenge to people who aren't trained in computation because it passes what I call the 'Excel barrier,’” he says. "I've been amazed at what a biologist with Excel can do, but we have now exceeded the Excel barrier in terms of the number of rows and columns and the computational powers of Excel.”

Let’s get started - we plan to make these introductory courses free forever for everyone. Hopefully, as the projects we started ( get fully integrated, we can provide many more free resources to the public. If you have an interesting dataset we should consider or would like to speak to us about your own bioinformatics course/curriculum/project, please drop us a line at

next-gen RNA-Seq sequence education • 2.0k views

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