UNRAVELING THE COMPLEXITIES OF LIFE SCIENCES DATA

被引:33
|
作者
Higdon, Roger [1 ,2 ,3 ,4 ]
Haynes, Winston [1 ,2 ,3 ,4 ]
Stanberry, Larissa [1 ,2 ,3 ,4 ]
Stewart, Elizabeth [1 ,4 ]
Yandl, Gregory [1 ,2 ,4 ]
Howard, Chris [4 ,5 ]
Broomall, William [2 ,3 ,4 ]
Kolker, Natali [2 ,3 ,4 ]
Kolker, Eugene [1 ,2 ,3 ,4 ,6 ,7 ]
机构
[1] Seattle Childrens Res Inst, Ctr Dev Therapeut, Bioinformat & High Throughput Anal Lab, Seattle, WA 98101 USA
[2] Seattle Childrens Res Inst, Ctr Dev Therapeut, High Throughput Anal Core, Seattle, WA 98101 USA
[3] Seattle Childrens, Predict Analyt, Seattle, WA USA
[4] Data Enabled Life Sci Alliance DELSA Global, Seattle, WA USA
[5] Seattle Childrens Res Inst, Ctr Dev Therapeut, Seattle, WA 98101 USA
[6] Univ Washington, Dept Biomed Informat & Med Educ, Seattle, WA 98195 USA
[7] Univ Washington, Dept Pediat, Seattle, WA 98195 USA
基金
美国国家科学基金会;
关键词
INTENSIVE SCIENTIFIC DISCOVERY; MASS-SPECTROMETRY PEPTIDE; PROTEIN IDENTIFICATION; STAPHYLOCOCCUS-AUREUS; ORTHOLOGOUS GROUPS; EXPRESSION; MODEL; SEQUENCE; BIOLOGY; PHARMACOGENOMICS;
D O I
10.1089/big.2012.1505
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页码:42 / 50
页数:9
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