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Biomedicine and Big Data Analyzing spatio-temporal patterns in biomedical data Normal Stif f Wavy

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Biomedicine and Big Data. Normal. Analyzing spatio -temporal patterns in biomedical data. Stiff. Wavy. My Research Group. Dr. Chakra Chennubhotla Ph.D. Computer Science University of Toronto. Shannon Quinn B.S. Computer Science Georgia Tech. Andrej Savol B.S. Applied Mathematics - PowerPoint PPT Presentation

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Page 1: Biomedicine and Big Data

Biomedicine and Big DataAnalyzing spatio-temporal patterns in biomedical data

Normal

Stiff

Wavy

Page 2: Biomedicine and Big Data

My Research GroupDr. Chakra ChennubhotlaPh.D. Computer ScienceUniversity of Toronto

Andrej SavolB.S. Applied MathematicsUniversity of Pittsburgh

Virginia BurgerM.S. MathematicsUniversity of Vienna

Shannon QuinnB.S. Computer ScienceGeorgia Tech

Page 3: Biomedicine and Big Data

Our MissionHigh-throughput biomedical data

analysis

Page 4: Biomedicine and Big Data

Problem and SolutionBiomedical and biological data

are BIGMapReduce! C0 C1 C2 C3

M0

M1

M2

M3

IO0 IO1 IO2 IO3

R0 R1

FO0

FO1

chunks

mappers

Reducers

Map

Pha

seR

educ

e Ph

ase Shuffling Data

Page 5: Biomedicine and Big Data

Specifically…

Clustering!

Page 6: Biomedicine and Big Data

RequirementsJavaApache Hadoop or Amazon EC2Apache MahoutComfortable with linear algebra

◦Ax = b◦X = UΣUT

Hive, HBase, Giraph, GraphLab, etc optional but awesome

Page 7: Biomedicine and Big Data

Final ThoughtsDistributed computing

◦Open source development◦Programming at scale

Large project management◦Software engineering principles,

toolsBiomedical context

◦Biological data is huge◦Diagnostics: helping people

Page 8: Biomedicine and Big Data

Questions? Comments? [email protected] || spq1

@pitt.edu

mailto:[email protected]
mailto:[email protected]
mailto:[email protected]
mailto:[email protected]

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