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Technology has changed the world of biology. A generation ago, an individual researcher could design, perform and extract meaningful results from an experiment, quickly understanding what the data meant and what its implications were. These days, however, that’s just not possible.

“Today, it’s common to run experiments where the data has a lot more information in it than one person can grasp by looking at it,” says Milan Mrksich, professor of chemistry and cell and molecular biology at Northwestern University. “[Experiments] present an amount of data that no one person can look at and recognize all the information that’s there.”

This fact is the key to understanding current trends in the field.

Technology Rules

Whether the rise of technology has prompted the use of data, or the need for complex data has necessitated the use of technology, one fact is clear: Technology and biology are inextricably linked. And this comes with its own set of complications.

The first issue is that we don’t fully understand the computational tools and their limits at this point. In using the tools to learn about biology, researchers are also learning about the tools. It’s very complicated and can introduce unanticipated variables into research.

The second is that there is just too much data for one person to analyze, which means collaboration is necessary. Getting multiple perspectives on the same data can bring many valuable viewpoints to the table. Teams and researchers also often bring in a dedicated expert in analysis to make sense of the data.

“This can be challenging because the two collaborators don’t really speak the same language,” says Mrksich, noting that big data has deeply affected biology – and will continue to do so. “It’s quite a challenge.”

Getting Detailed

Because of this vastly increased new ability to analyze data and reach multiple conclusions from one experiment, the world of research biology is also becoming more diverse. New fields – like Mrksich’s field of synthetic biology – are emerging every day. This trend is making impact measures more important than ever.

“As a new field starts to gain traction and attract a larger group of researchers to work on problems that fall outside the boundaries of existing fields, a number of other developments happen,” says Mrksich. “Those include the establishment of new journals, the founding of new conference series, blogs that are started by groups that want to become the new source for their field and granting agencies releasing calls for proposals.”

Deciding where to publish can be difficult, especially in a new field with new journals. Understanding journal impact factors can help authors determine the legitimacy and influence of a publication. When deciding which journals to read, cite and submit to, researchers can look to these factors to evaluate a publication.

Blogs and other social media outlets also give rise to a whole different form of evaluation – altmetrics. Though Mrksich says that citation numbers still form the basis of understanding research impact, understanding social impact can give a bigger picture of the research in a societal context. It’s easy to get lost in the details when doing research; altmetrics give a “big-picture” view.

“Both are important because every science wants to show that research is important and significant and it can change the world,” he says. “Most researchers spend most of their time thinking hard about technical details that are important to their work, but the popular stories of science add a measure of societal impact.”

None of this can happen, though, until there are a few high-profile, highly cited papers. These seminal papers form the basis of a new field, with communities of researchers being built around them. Citations are crucial to identifying these papers, and hence to starting these communities.

“Seminal, groundbreaking work is recognized and motivates many further studies, and that leads to high citation rates,” Mrksich says.

Thomson Reuters will be discussing this and more at Experimental Biology Annual 2016 in San Diego the first week of April. Attending? Visit us at booth #1101 and attend our workshop Zika Virus: A Research Landscape Analysis Using Journals, Patents, and Datasets. Register now! Can’t attend? Please register and we'll send you a copy of the presentation slides.