The Challenge of Modern Day Science

 :: Posted by American Biotechnologist on 10-14-2014

In recent years, there have been incredible advances in scientific tools available at our disposal. As a result, the rate of scientific discovery and the amount of data produced by molecular biologists and proteomic specialists has been astounding. Projects such as the Cancer Genome Atlas and the ENCODE Project have generated billions of data points and provide opportunities for original researchers and other investigators to use these results in their own work to advance our knowledge of biology and biomedicine. This data explosion has challenged scientists and funding agencies to come up with new models for dealing with this massive amount of data in the most efficient way possible.

In order to tackle this challenge, the National Institute of Health (NIH), has created a Big Data to Knowledge (BD2K) initiative to enable biomedical research as a digital research enterprise, to facilitate discovery and support new knowledge, and to maximize community engagement. So far this year, the NIH has invested $32 Million in BD2K with an additional $624 Million expected to be injected into the project by the year 2020.

According to NIH director Francis S. Collins:

Mammoth data sets are emerging at an accelerated pace in today’s biomedical research and these funds will help us overcome the obstacles to maximizing their utility. The potential of these data, when used effectively, is quite astounding.

Note Dr. Collins’ use of the words “when used effectively.” Effective use and analysis of massive data sets requires open collaboration between scientists across various disciplines and nationalities. Governments play a critical role in facilitating such collaboration and science-friendly collaborative policies are not always forthcoming. Furthermore, lack of data standards for many types of data, and the low adoption of data standards across the research community has also proven to be a significant obstacle to the efficient used of Big Data. In addition, many scientists also do not have the opportunity or facility to use big data and have not been trained in the computational skills to access and analyze large data sets.

Let’s hope that the recent grants awarded by the NIH strengthen the effective use of Big Data so that the time and effort spent in creating this data does not go to waste.

Talk Nerdy to Me

 :: Posted by American Biotechnologist on 10-13-2014

Advanced Topics in Cell Sorting

 :: Posted by American Biotechnologist on 10-09-2014

In this webinar, Dan Fox of Propel Labs explores the principles of cell sorting including the theory of droplet cell sorting, how to assess cell sorter performance, and how sorting speed influences results. Dan also discusses the S3™ Cell Sorter’s unique sorting modes, the sort mode process and logic, and how the S3 Sorter simplifies the science of cell sorting.

Health Benefits of Coffee Genetically Dependent

 :: Posted by American Biotechnologist on 10-08-2014

Another day, another study on the health benefits or detriments of habitual coffee drinking. Good for you. Bad for you. Good for your heart, bad for your kidneys. Good for your kidneys, bad for your heart…You get the drift. It seems like there are two distinct camps that have lined up behind each opinion. In the “coffee is healthy” camp you have the coffee lovers and in the other camp are the non-coffee drinkers. As a coffee consumer, I have ignored much of the negative research and have helped spread the positive findings about the benefits of high caffeine consumption to all of my family and friends. However, according to a new large-scale study led by Harvard School of Public Health and Brigham and Women’s Hospital researchers, the debate can now be settled by genetics.

Read the full story on the Harvard University website.

A Neural Portrait of the Human Mind

 :: Posted by American Biotechnologist on 10-06-2014

Watch this very cool video to find out how researcher Nancy Kanwischer used MRI techniques to identify the region of the brain that is responsible for facial recognition. It took years of research and a tremendous amount of self sacrifice, but the results are incredible.