Unraveling the Complexities of Life Sciences Data

The life sciences have entered into the realm of big data and data-enabled science, where data can either empower or overwhelm. These data bring the challenges of the 5 Vs of big data: volume, veracity, velocity, variety, and value. Both independently and through our involvement with DELSA Global (D...

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Veröffentlicht in:Big data 2013-03, Vol.1 (1), p.42-50
Hauptverfasser: Higdon, Roger, Haynes, Winston, Stanberry, Larissa, Stewart, Elizabeth, Yandl, Gregory, Howard, Chris, Broomall, William, Kolker, Natali, Kolker, Eugene
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container_end_page 50
container_issue 1
container_start_page 42
container_title Big data
container_volume 1
creator Higdon, Roger
Haynes, Winston
Stanberry, Larissa
Stewart, Elizabeth
Yandl, Gregory
Howard, Chris
Broomall, William
Kolker, Natali
Kolker, Eugene
description The life sciences have entered into the realm of big data and data-enabled science, where data can either empower or overwhelm. These data bring the challenges of the 5 Vs of big data: volume, veracity, velocity, variety, and value. Both independently and through our involvement with DELSA Global (Data-Enabled Life Sciences Alliance, DELSAglobal.org), the Kolker Lab ( kolkerlab.org ) is creating partnerships that identify data challenges and solve community needs. We specialize in solutions to complex biological data challenges, as exemplified by the community resource of MOPED (Model Organism Protein Expression Database, MOPED.proteinspire.org ) and the analysis pipeline of SPIRE (Systematic Protein Investigative Research Environment, PROTEINSPIRE.org ). Our collaborative work extends into the computationally intensive tasks of analysis and visualization of millions of protein sequences through innovative implementations of sequence alignment algorithms and creation of the Protein Sequence Universe tool (PSU). Pushing into the future together with our collaborators, our lab is pursuing integration of multi-omics data and exploration of biological pathways, as well as assigning function to proteins and porting solutions to the cloud. Big data have come to the life sciences; discovering the knowledge in the data will bring breakthroughs and benefits.
doi_str_mv 10.1089/big.2012.1505
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