The SIG Beat



The Fibrosis Scientific Interest Group is a new initiative that provides a forum for individuals from NIH and the extramural community to discuss basic, translational, and clinical research related to fibrosis. Trainees, basic laboratory researchers, and clinicians from academic institutions and medical centers are welcome to join this group. The Fibrosis SIG will meet monthly to organize seminars and engage in interactive discussions focusing on members’ interests related to fibrosis. The inaugural meeting will be held on Wednesday, September 7, 4:00–5:00 p.m., in CRC conference room 5-2550, Building 10. For more information and/or to join the SIG’s LISTSERV, contact one of the moderators: Resat Cinar (NIAAA; or Bernadette Gochuico (NHGRI;


“Of the many mysterious human illnesses that science has yet to unravel, ME/CFS has proven to be one of the most challenging,” said NIH Director Francis S. Collins in October 2015 when announcing the new intramural and extramural initiatives to determine the cause of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and identify clinically meaningful treatments. Recent efforts to describe ME/CFS have identified post-exertional malaise as the key defining symptom of ME/CFS. Although the serious, debilitating effect of ME/CFS symptoms have on the estimated one million afflicted Americans is self-evident, there remains much controversy over its potential cause. To date, there is no experimental evidence proving causality that has withstood scientific scrutiny.

The ME/CFS SIG seeks to provide a forum in which to disseminate and discuss clinical and scientific information about ME/CFS. It is open to all interested intramural and extramural investigators seeking to learn more about ME/CFS, and the SIG hopes to foster new research collaborations across the NIH campus. The SIG is led by NINDS Clinical Director Avi Nath, who is the primary investigator of the Intramural ME/CFS initiative, and moderated by lead associate investigator Brian Walitt (NINR). The ME/CFS SIG will present a bimonthly seminar series with presentations by internal and outside experts and may include additional lectures, seminars, panel discussions, journal discussions, collaboration.

For more information and notices of meetings and events, join the LISTSERV ( or contact Brian Walitt at


The goal of the Data Science in Biomedicine SIG is to foster the growing community of biomedical data scientists at NIH through improving communications, providing a forum for scientific discussions, and catalyzing collaborations. The Data Science in Biomedicine SIG will work with established SIGs and community groups that focus on components of data science to coordinate activities and increase awareness of opportunities in data science. This interest group will engage intramural and extramural scientists by meeting quarterly on campus, sometimes with other SIGs. The group will host a seminar series featuring NIH and outside speakers, organize an annual poster session, and collect user input on workshops and courses needed at NIH. Additional activities depend on the interests of the group. To join the SIG, add your name to the NIH-DATASCIENCE-L LISTSERV at Announcements will be posted at For questions, contact Ben Busby at

This SIG is being co-sponsored by the Office of the Associate Director for Data Science, the NIH Library, and the National Library of Medicine.

NOTE: The recently established Research Repositories and Patient Registries SIG will be incorporated under the Data Science in Biomedicine SIG. Please register for the NIH-DATASCIENCE-L LISTSERV described above.


The goal of the Statistics SIG is to foster and support the growing community of statisticians at NIH. The scientific focus is on statistical methods commonly used in the design and analysis of clinical trials and in explorations in epidemiology and population science, as well as on biomedical science more broadly. These topics include but are not limited to the examination of large datasets, analysis of data from new technologies (for example, high-dimensional “omics” data), risk assessment and prediction, quantitative approaches to precision medicine, adaptive methodology in clinical trials, causal inference, meta-analysis, and analysis in the face of complexities such as time-varying effects, missing values, and multiplicities. This new SIG will enable lively and productive discussions among and within statistical groups and others interested in the application of statistics at the NIH.

The SIG will meet quarterly. To join the SIG, add your name to the STATISTICS-NIH-L LISTSERV at Announcements will be posted at

The SIG is co-sponsored by the NIH Office of the Director and NCI. For questions, contact Tammy Massie (


The Text Mining SIG will provide a community for NIH researchers who use text mining (the automated extraction of information from text) in their work and would like to learn more about what is being done in this area across the campus. The SIG seeks to identify text-mining researchers and others at NIH as well as tools that have been developed here and can be used by others. The SIG will provide several networking opportunities a year for participants to publicize their work and learn about others’ research. Specifically, the SIG will host a session at the Data Science SIG poster session and a series of short talks, and it would like to host a half-day or one-day workshop on using existing text-mining resources. Additionally, the SIG will host a clearinghouse of descriptions of text-mining tools that are available and can be used on campus or can be promoted more widely. The Text Mining SIG intends to work closely with the Data Science in Biomedicine Interest Group to provide domain expertise about text mining as a specific discipline within data science. If you’re interested in joining the Text Mining SIG distribution list, e-mail Lena Pons at


This SIG is being incorporated under the Data Science in Biomedicine SIG. Members of the Research Repositories and Patient Registries SIG should register for the NIH-DATASCIENCE-L LISTSERV described above.