NIH Call for Information on Methods for 'Big Data' in Biomedical Research

The US National Institutes of Health (NIH) has just issued a call for information on software tools and analysis methods as part of their Big Data to Knowledge Initiative. Specifically, the call solicits input on needs for software and analysis methods related to data compression/reduction, data visualization, data provenance, and data wrangling for biomedical research. The closing data for responses is September 6th 2013.

Background

Biomedical research is becoming more data-intensive as researchers are generating and using increasingly large, complex, and diverse datasets. This era of 'Big Data' in biomedical research taxes the ability of many researchers to release, locate, analyze, and interact with these data and associated software due to the lack of tools, accessibility, and training. In response to these new challenges in biomedical research, and in response to the recommendations of the Data and Informatics Working Group (DIWG) of the Advisory Committee to the NIH Director (http://acd.od.nih.gov/diwg.htm), NIH has launched the trans-NIH Big Data to Knowledge (BD2K) Initiative (www.bd2k.nih.gov).

The long-term goal of the NIH BD2K Initiative is to support advances in data science, other quantitative sciences, policy, and training that are needed for the effective use of Big Data in biomedical research. (The term "biomedical" is used here in the broadest sense to include biological, biomedical, behavioral, social, environmental, and clinical studies that relate to understanding health and disease).

Details can be found here: http://grants.nih.gov/grants/guide/notice-files/NOT-HG-13-014.html

 

 

New Stata Journal 2011_1

The most recent Stata Journal Volume 11, Number 1 is now available for RLAB members in the library under M:\STATA JOURNAL.

Of interest to SERC staff in particular might be the article on Stata utilities for geocoding and generating travel time and travel distance information (A. Ozimek and D. Miles)

The full Journal contents includes:

Articles and Columns
A procedure to tabulate and plot results after flexible modeling of a quantitative Covariate (N. Orsini and S. Greenland)
Nonparametric item response theory using Stata. (J.-B. Hardouin, A. Bonnaud-Antignac, and V. S´ebille)
Visualization of social networks in Stata using multidimensional scaling (R. Corten)
Pointwise confidence intervals for the covariate-adjusted survivor function in the Cox model (M. Cefalu)
Estimation of hurdle models for overdispersed count data (H. Farbmacher)
Right-censored Poisson regression model (R. Raciborski)
Stata utilities for geocoding and generating travel time and travel distance information (A. Ozimek and D. Miles)
eq5d: A command to calculate index values for the EQ-5D quality-of-life instrument. (J. M. Ramos-Go˜ni and O. Rivero-Arias)
Speaking Stata: MMXI and all that: Handling Roman numerals within Stata (N. J. Cox)
Notes and Comments
Stata tip 94: Manipulation of prediction parameters for parametric survival regression models (T. Boswell and R. G. Gutierrez)
Stata tip 95: Estimation of error covariances in a linear model (N. J. Horton)
Stata tip 96: Cube roots (N. J. Cox)
Software Updates

For RLAB staff who do not have access to the library please contact the RLAB data manager.
For staff outside RLAB who wish to access the stata journal please go to http://www.stata-journal.com/

UCLA ATS - useful resources

UCLA Academic Technology Services website contains some useful resources including introductory courses for statistical software such as STATA, SAS and SPSS; GIS resources; as well as discussions of more advanced statistical methods. Some of the resources are restricted to UCLA, but there is a lot freely available.