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New App Helps Data-Overload Looming over Neuroscientists

By BiotechDaily International staff writers
Posted on 20 Aug 2013
Neuroscientists gathered their data, before the digital age, in the library similar to the rest of the population. However, the field’s upsurge has created nearly two million scientific articles—more information than investigators can research during their whole lives.

A University of California, Los Angeles (UCLA; USA) group of scientist has devised research maps. Armed with an online application (app), the maps help neuroscientists rapidly scan what is already known and plan their next study. The August 8, 2013, issue of the journal Neuron described the findings.

“Information overload is the elephant in the room that most neuroscientists pretend to ignore,” explained lead investigator Dr. Alcino Silva, a professor of neurobiology at the David Geffen School of Medicine at UCLA and of psychiatry at the Semel Institute for Neuroscience and Human Behavior. “Without a way to organize the literature, we risk missing key discoveries and duplicating earlier experiments. Research maps will enable neuroscientists to quickly clarify what ground has already been covered and to fully grasp its meaning for future studies.”

Dr. Silva collaborated with Anthony Landreth, a former UCLA postdoctoral fellow, to create maps providing simplified, interactive, simplified, and unbiased summaries of findings designed to help neuroscientists in picking what to study next. As a testing foundation for their maps, the researchers centered on cellular and molecular cognition findings.

UCLA programmer Dr. Darin Gilbert Nee also created a web-based app to help scientists expand and interact with their field’s map. “We founded research maps on a crowd-sourcing strategy in which individual scientists add papers that interest them to a growing map of their fields,” explained Dr. Silva, who started working on the problem nearly 30 years ago as a graduate student, and coauthored with Dr. Landreth an upcoming Oxford Press book on the topic. “Each map is interactive and searchable; scientists see as much of the map as they query, much like an online search.”

According to Dr. Silva, the map allows scientists to narrow in and out of areas that interest them. Researchers, by tracking published findings, can determine what is missing and target valuable research to follow up. “Just as a GPS map offers different levels of zoom, a research map would allow a scientist to survey a specific research area at different levels of resolution—from coarse summaries to fine-grained accounts of experimental results,” said Dr. Silva. “The map would display no more and no less detail than is necessary for the researcher's purposes.”

Each map encodes data by categorizing them into classification and scoring the weight of its evidence based on vial criteria, such as reproducibility and convergence, when different experiments point to a single conclusion. The scientist’s next phase will be to automate the map creation process. As scientists publish articles, their findings will automatically be added to the research map representing their field.

According to Dr. Silva, automation could be achieved by using journals’ publication process to divide an article’s findings into smaller chapters to build nanopublications. Publishers would employ a software plugin to render future papers machine-readable.

A more direct approach would add distinct fields into the templates for journal article submission. The data resulting from these fields could be published to a public database, which would provide the foundation for research maps. “Western societies invest an enormous amount into science, and research maps will optimize that investment,” noted Dr. Silva. “One day, we will look back on the pre-map era of experiment planning with the same incredulity we now reserve for research conducted prior to statistics.”

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University of California, Los Angeles



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