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NIH View of Data Science and BD2K

On September 12, 2016, Dr. Michelle Dunn from the NIH will be the distinguished speaker at the first lecture of the 2016-2017 PHDL Seminar Series. The NIH launched the Big Data to Knowledge (BD2K) initiative in 2012 to address the challenges of maximizing the use of biomedical research data. Dr. Dunn will give a retrospective of the development of data science at the NIH over the last few years, describing how it has evolved along with and in response to the development of data science in the broader scientific community. She will describe a major trans-NIH program, the Big Data to Knowledge Initiative, led by the NIH Associate Director for Data Science (ADDS), as well as the additional efforts of the ADDS office towards enabling the efficient management of biomedical Big Data. 

Michelle Dunn, PhDDr. Dunn is senior advisor for Data Science Training, Diversity and Outreach at the Office of the Associate Director for Data Science at the NIH. She leads the data science training efforts, advising on training, education and workforce development in biomedical data science. Prior to joining the NIH/OD, she was a program director at the National Cancer Institute. She received her Ph.D. in statistics from Carnegie Mellon University and her A.B. in applied mathematics from Harvard College. 

The seminar is open to the public and Grand Rounds approved.

 

2016 MIDAS Network Meeting

midas network meeting 2016

The University of Pittsburgh MIDAS Center for Excellence participated in the May 23-24, 2016 MIDAS Network Meeting in Reston, Virginia with four presentations and four posters. MIDAS investigators representing the Pitt Center of Excellence were: Donald Burke, PI, Mark Roberts, John Grefenstette, Wilbert van Panhuis, Derek Cummings (University of Florida), Logan Brooks and Roni Rosenfeld (Carnegie Mellon University), Jeanine Buchanich, and Hasan Guclu.

ages and stages poster

MIDAS uses ABM to examine if population structure is sufficient to generate area-level inequalities in influenza rates

RR adults

In New Haven County (NHC), CT, influenza hospitalization rates have been shown to increase with census tract poverty in multiple influenza seasons. In what is, to our knowledge, the first use of simulation models to examine the causes of differential poverty-related influenza rates, researchers in the Public Health Dynamics Laboratory used agent-based models with a census-informed, realistic representation of household size, age-structure, population density in NHC census tracts, and contact rates in workplaces, schools, households, and neighborhoods, and measured poverty-related differential influenza attack rates over the course of an epidemic. Simulated attack rates among adults increased with census tract poverty level. The study detected a steeper, earlier influenza rate increase in high-poverty census tracts, a finding that was corroborated with a temporal analysis of NHC surveillance data during the 2009 H1N1 pandemic. The ratio of the simulated adult AR in the highest- to lowest-poverty tracts was 33% of the ratio observed in surveillance data, leaving 67% of the inequality to be explained by other factors. Future models should quantify the capacity of individual behavioral and biological factors to generate influenza inequalities thus allowing us to prioritize interventions aimed at factors with the greatest explanatory power.

Read the paper at: http://www.biomedcentral.com/1471-2458/15/947

MIDAS’ David Galloway of the University of Pittsburgh presents Graph Databases featuring Neo4j

DaveWhen: Wednesday, September 16 at 2:00PM Eastern time

What: Dave Galloway will discuss what a graph database is and how it differs from a relational database or a document store database. He will show some examples of graph data and some even more specific examples of it pertaining to infectious disease. He will use Neo4j to show a specific example of a graph database and will use their query language, Cypher, to utilize the database. This discussion is part of an ongoing series of talks targeted toward and given by members of the MISSION 2.0 (MIDAS Software Sharing and Information Outreach Network) group.

Read more: MIDAS’ David Galloway of the University of Pittsburgh presents Graph Databases featuring Neo4j

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