C. Titus Brown, a bioinformatician at the University of California, Davis, participated in a January workshop at Caltech on “The Paper of the Future,” and wrote about the experience on his blog. Here, he expands on how academic publishing may change in the years to come.
It’s been nearly a decade since Eric Welsh first noticed some weirdness with Microsoft Excel. A senior staff scientist in the Cancer Informatics Core at the H. Lee Moffitt Cancer Center and Research Institute in Tampa, Florida, Welsh was using Microsoft’s venerable spreadsheet application to view mouse and human gene expression data, the better to sort and understand the numbers. But a quick glance revealed the import hadn’t gone exactly as planned. “Excel would screw them up every time,” he says.
How so? When data are imported into Excel, the program works hard to figure out what kind of value each cell holds. Most of the time, Excel is smart enough to do that correctly, and values like ‘BRCA1’ and ‘12345’ are converted into text and integers, as expected. But “Excel is a little too smart for its own good,” Welsh says. If a cell reads “SEPT7,” the program assumes the author meant to write a date, and converts it automatically. It also sometimes translates what appear be numbers in scientific notation – say, ‘2310009E13’ – into actual scientific notation (‘2.31E+13’). The problem is, those two terms are neither dates nor numbers – they are proper names, scientifically speaking: gene names, sample identifiers or accession numbers. And by autoconverting them, those names are lost, or at least, obscured.
https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-5-80
Today we feature Animesh Shukla, a biotechnologist from Meerut Institute of Engineering and Technology in Uttar Pradesh, India who went to Carnegie Mellon University and Indiana University of Bloomington in the USA for PhD. Animesh, who works as a scientist designing ELISA assay kits for Meso Scale Diagnostics now, says planning ahead of time for a postdoctoral career could open up several doors in the land of opportunities.
My school teacher Jessy Kuruvilla sparked my interest in biology. She used to explain the subject in such an interesting way that I still remember many things she taught us. I don’t remember much of any other subject. In high school I was interested in both biology and physics (specifically fluid dynamics). I never used to score really high marks in these subjects but had very good understanding of the basics.
I used to catch and collect live and dead insects or small animals and used to look at them. Some of my friends used to make fun of me (they still do) but that is what friends are for! Continue reading
There has always been an emphasis on the generation of novel data in science. Being a scientist involves progressing from observation to hypothesis to experiment to output. In the past, a combination of scarce data to look at and low throughput machinery to make more has led to limited experimental outcomes.
Atma Ivancevic
Jungwoo Ryoo, Pennsylvania State University
Big data is increasingly becoming part of everyday life. Network security companies use it to improve the accuracy of their intrusion detection services. Dating services use it to help clients find soulmates. It can enhance the efficiency and accuracy of fraud detection, in turn helping protect your personal finances.
“Big data” is a catchall term for any data set of exceedingly large volume. It could be transaction information at a credit card company, invoice data at an online retailer, meteorological measurements from a weather station. All these data sets have unique characteristics that make it extremely difficult to use conventional computing technologies and techniques to store and process them for analysis. Their variety is daunting, and high velocity is required to handle them in a timely manner.
Organizations in any field can use big data to enhance their effectiveness, which is why there are seemingly unlimited career opportunities in big data these days. The big data industry is growing fast, with the market predicted to grow at a compound annual growth rate of 23.1 percent over the 2014-2019 period.
So who is going to store, manage and process all this information? Well, why not you? Companies are starved for people with this kind of expertise. Big data is a growth industry and people from a variety of academic backgrounds can find successful careers in this area.
Guest contributor Daniela Quaglia
{credit}Image credit: SCIENTIFIC DATA/LUDIC GROUP{/credit}
Big data is here to stay. As scientists, we stand to benefit by being part of this exciting revolution. At the second Publishing Better Science through Better Data conference, held in London on October 23rd, Dr. Ewan Birney, joint associate director of the European Bioinformatics Institute (EBI), and Dr. Timo Hannay, founder of SchoolDash (a website that provides statistics about schools in England), walked us through some of the opportunities that arise from working with big data.
Opportunities in biology
Birney spoke about how the increase in big data is influencing the way we do biology. He promised to give the audience “an EBI centric view of the world”. I’m glad he did, because every scientist wanting to use big data should understand how EBI can help them.
EBI takes data provided by laboratories and stores, verifies, classifies and shares it. This approach means that a wealth of molecular-biology data, from DNA sequences to full systems (such us biomolecular pathways and metabolomics data), can be found in one place. As most scientists do not want to have to work from shared data in their raw form, the institute also works with the scientific community to convert original data into useful formats. Data from the Human Genome Project provides a compelling example of how such transformations can benefit the community — as Birney pointed out, not even the most experienced researchers want to analyse such complex raw data. Continue reading
