Soybean 'Big Data' Online

Infrastructure promotes collaboration among researchers

SoybeansA new online data resource, the Soybean Knowledge Base (SoyKB), was unveiled by scientists at the University of Missouri. It will allow greater collaboration among international researchers, scientists and farmers to solve questions encountered in soybean research.

“Researchers essentially deposit their results from experiments into the database, and high capacity computer systems crunch the numbers to help determine results,” said Trupti Joshi, assistant research professor in computer science at Mizzou. “Their experiments become a part of the bigger picture allowing future researchers to narrow their own results.”

Gary Stacey, professor of plant sciences.

Gary Stacey, professor of plant sciences.

“Humans only can look at so many lines in an Excel spreadsheet—then it just kind of blurs,” said Gary Stacey, collaborator on the project, a professor of plant sciences in the College of Agriculture, Food and Natural Resources, and an investigator in the MU Bond Life Sciences Center. “We need these kinds of tools to be able to deal with this high-volume data. With this database, all the data is deposited and available so something that’s not valuable to me may be valuable to somebody else.”

In the era of “big data,” many scientific discoveries are being made without researchers ever stepping foot in traditional laboratories. Often, data from numerous experiments is gathered and disregarded, with only the desired results analyzed. SoyKB was developed to provide the digital infrastructure needed to store previously disregarded data to take plant science to the next level.

Collaborating for the Greater Research Good

Highly collaborative in nature, SoyKB uses computational methods developed by computer science engineers that can be used for many disciplines, such as health sciences, animal sciences, physics and genetics. Additionally, a 3D-protein modeling tool available at the website assists with researchers studying drug design. Pharmaceutical companies may test hypotheses and, in some situations, the proposed drug may yield the expected results — formulated solely by data analysis making drug design more cost effective.

Joshi-Trupti[1]

Trupti Joshi developed the free online database that assists international researchers, scientists and farmers to solve questions encountered in soybean research.

Joshi is a valued resource to the finished product because she has both a biology degree and a computer science background, or a “foot in each camp,” Stacey said.

SoyKB has turned out to be a very good public resource for the soybean community to cross reference and check the details of their findings,” Joshi said. “It can be really difficult for biologists to handle the large scope of data by themselves, and this tool allows researchers to focus more on the biology.”

SoyKB is a part of the U.S.’s $200 million “Big Data” Initiative, a program that works to improve the ability to extract knowledge and insight from large and complex collections of digital data and promises to help solve some of the nation’s most pressing challenges.

The progress of SoyKB was presented at the International Conference on Bioinformatics and Biomedicine in Shanghai. The project is funded by grants from the National Science Foundation.

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  1. Please give the source(origin) of the following soybean genotypes which are taken in my study

    EC471999
    UPSL340-A
    EC472137
    EC472143
    EC472227
    EC547191
    UPSV24
    DS9813
    JS(SH)98-22
    DS9719
    UPSL332
    PK1197
    UPSL303
    EC472129
    HIS01
    PS1024
    M1094
    PS416
    EC457321
    EC457285
    EC456646
    PK1135
    EC471292
    EC457196
    DS9814
    PS1042
    DS9801
    DS9816
    PK1251
    EC472130
    DS9819
    EC471784
    L440
    SL459
    EC457505
    EC471923
    EC471998
    EC389179
    V9
    UPSL309
    PS1374
    UPSL244
    EC457323
    EC471292

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