Big Bioinformatics and Healthcare Analytics without Big Hassles

(Recorded on December 11, 2013) | Access Today  

Sponsored by   Pardigm4 





Researchers and analysts just want to do fast, interactive exploratory analytics—without regard for the size, heterogeneity, or complexity of the data.

Big Data solutions generally don’t support the mathematical sophistication needed by bioinformaticians and healthcare researchers. Analysts are forced to think about selecting data, about whether their data fits in memory, about parallelism, and about formatting and transporting data into a math package.

There’s another way, one that lets analysts readily share, access, and analyze rich data as well as use their favorite analytical languages and have it transparently scale up to Big Data volumes. Paradigm4 presents a webinar about SciDB—the massively scalable, open source, array database with native complex analytics, integrated with R and Python—for bioinformatics and healthcare informatics problems.

Learn how SciDB lets you: 

  • Explore multi-dimensional data sets interactively
  • Do complex math in-database—without being constrained by memory limitations
  • Offload large computations to a commodity hardware cluster—on-premise or in a cloud
  • Use R and Python to analyze SciDB arrays as if they were R or Python objects.
  • Share data among users, with multi-user data integrity guarantees and version control

Speakers include: 

 Kasif       Professor Simon Kasif, Ph.D.    
     Biomedical Engineering, Boston University 
 Lewis       Bryan Lewis, Ph.D. Applied Math    
     Chief Data Scientist, Paradigm4 
 Alex Poliakov 

     Alex Poliakov    
     Solutions Architect, Paradigm4 


(Recorded on December 11, 2013) | Access Today