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Archive for the ‘Health Sciences’ Category

Webinar: Collaborations between Libraries and Disaster Organizations Part 2

Tuesday, August 30th, 2016


From the DISASTR-OUTREACH-LIB email list:

WHEN:  Thursday, September 8, 2016 at 1:30 pm ET

WHO CAN PARTICIPATE:  The Disaster Information Specialist monthly webinar is free and open to everyone – please spread the word and invite others in your organizations, send to your email lists, and post to your social media accounts.

TOPIC and SPEAKERS:  Tania Bardyn and her team from the University of Washington Health Sciences Library will present about their current Disaster Health Information Outreach and Collaboration Project. The Library, in partnership with the Washington State Department of Health, Office of Emergency Preparedness and Response and the Washington State Emergency Management Division, developed a mobile application (app) for Android devices called Response & Recovery App in Washington (RRAIN Washington) to improve access to National Library of Medicine (NLM) disaster information resources in Washington State.  This is a follow-on project to the RRAIN app created in 2014 for iPhone and iPad devices.

Also, Sarah Carnes, a virtual intern with the NLM Disaster Information Management Research Center, will present about her project “Design and Delivery of an Outreach Strategy to Increase Awareness of Disaster Information Resources.” She will present on the process she used to design a program for Massachusetts public libraries to increase awareness and use of disaster information resources. She will also discuss how she delivered the strategy and synthesized their feedback to refine the strategy and accompanying products.



Meeting URL:

Event Password: 1234

For more information on this and past meetings, see


NIH BD2K has 5 new RFPs. Check ‘em out PDQ!

Monday, August 29th, 2016

Hello Network members – are you gearing up to support Big Data initiatives at your institution? There are funds available to those who are from the Big Data to Knowledge (BD2K) group at NIH that can support for efforts. Main BD2K funding page (see past funded projects as well). jb

Big Data to Knowledge (BD2K) Community-Based Data and Metadata Standards Efforts (R24) RFA-ES-16-010 10/19/2016
Early Stage Development of Technologies in Biomedical Computing, Informatics, and Big Data Science (R01) PA-14-155 04/06/2017
Extended Development, Hardening and Dissemination of Technologies in Biomedical Computing, Informatics and Big Data Science (R01) PA-14-156 04/06/2017
Early Stage Development of Technologies in Biomedical Computing, Informatics, and Big Data Science (R43/R44) PA-14-154 05/08/2017
Early Stage Development of Technologies in Biomedical Computing, Informatics, and Big Data Science (R41/R42) PA-14-157 05/08/2017

Free webinar on the concepts of deep learning and as it relates to machine learning techniques on Sept 8th at 1pm MT / 2pm CT

Monday, August 29th, 2016

Dear Network members – Please consider inviting others who might be interested in this topic.

On September 8, there will be an hour-long overview of deep learning
followed by a half hour for questions.
Title: Overview of Deep Learning in Healthcare
Date: Sept 8, 2016 from 1pm – 2:30pm MT / 2pm – 3:30pm CT
Location: Via webcast open to all; no registration required.

Abstract: Machine Learning (ML) has become a core technology underlying many modern applications, especially in healthcare. Machine learning techniques provide powerful methods for analyzing large data sets, such as medical images, electronic health records, and genomics.  Recent advances in Deep Learning (DL) provide an analysis framework that can be used to
automatically classify images and objects with  (and occasionally exceeding) human-level accuracy.  A key advantage of Deep Learning is its ability to perform unsupervised feature extraction over massive data sets making big data part of the solution — not the problem.  Deep Learning is rapidly becoming a key tool at many of the top technology companies around
the world.
The talk will introduce DL in the broader context of machine learning and discuss critical factors driving the success of DL with examples of how deep learning is advancing healthcare.  We will also outline development and deployment workflows for building powerful DL solutions and provide an overview of relevant open source tool kits, companies, and products.  We
will wrap up with a short demo of NVIDIA’s DIGITS training system for rapidly prototyping your own deep learning applications.


MedPrint: Medical Serials Print Preservation Program

Friday, August 26th, 2016

indexThe NLM and NN/LM are continuing their initiative to sustain  access to print biomedical literature through the MedPrint – the medical serials print retention program. NN/LM member institutions across the country have committed to the program, but more participants are needed. If your library has  a print serials collection it may be eligible to participate. Learn more about the program and requirements here!  [jh]




BD2K Research Education Curriculum Development Funding Opportunity

Thursday, August 25th, 2016

Dear Network members – If your library has a computer science degree program, this might be an opportunity for you.

The NIH Research Education Program (R25) supports research education activities in the mission areas of the NIH.  The over-arching goal of this BD2K  R25 program is to support educational activities that complement and/or enhance the training of a workforce to meet the nation’s biomedical, behavioral and clinical research needs.

To accomplish the stated over-arching goal, this FOA will support creative educational activities with a primary focus on     Curriculum or Methods Development  in Big Data Science to augment current institutional curricula for the training of predoctoral level biomedical scientists and provide concentrated instruction in the tools, approaches and quantitative analysis concepts in data science. To facilitate the integration of data science into biomedical curricula nationally, this FOA seeks to support a cohort of institutions that will work collaboratively and collectively to produce curricular materials that are findable, accessible, interoperable, and reusable (FAIR).

More about the announcement


NCBI Minute Webinar: Downloading Genome Data from the NCBI FTP Site

Thursday, August 25th, 2016

Dear Network members!

Do you work with your genomics department or simply want to know how to download genomic sequences for your favorite species to your computer? Read on to learn more!

The next NCBI Minute webinar will teach attendees how to use the Web and the command line to quickly access and download genomic sequence and annotation files for a species, metagenome or taxonomic group of interest.

Date and time: Wednesday, August 31, 2016 12:00 PM EDT

Register here

After registering, you will receive a confirmation email with information about attending the webinar. After the live presentation, the webinar will be uploaded to the NCBI YouTube channel. Any related materials will be accessible on the Webinars and Courses page; you can also learn about future webinars on this page.

Useful Links:
* NCBI YouTube channel:
* Webinars and Courses:

The above post comes from:

ncbi-announce mailing list


Review of MedlinePlus from BYU Librarian

Tuesday, August 23rd, 2016

MedlinePlus: Worth Its Weight in Gold is a review of MedlinePlus by Greg Nelson, Chemical and Life Science Librarian at Brigham Young University. He highlights his favorite areas of the site and why he includes MedlinePlus in library instruction sessions. To read the review, visit Inside Science Resources, ALA ACRL Science and Technology Section’s blog.


NYU School of Medicine seeking medical librarians to pilot data management education materials…prepare to get your data geek on!

Friday, August 19th, 2016

Dear Data Enthusiasts! 

NYU School of Medicine is seeking medical librarians to pilot education materials developed with funds the Big Data to Knowledge Initiative at NIH.

The purpose of this two part program is to facilitate medical librarians ability to teach research data management concepts at their institutions.

The pilot is recruiting for Part 1, which consists of roughly 3 contact hours where students will be walked through 7 models focusing on the practice and culture of research and best practices of research data management.  

Part 2, not currently available, will focuses on a teaching toolkit that includes slides, scripts, and evaluation materials medical librarians can use to teach an in-person intro class on research data management.  

Students can start taking the modules right away but registration is required. Students are asked to email Kevin Read  or Alisa Surkis to confirm your participation or if you have any questions.


PMC Updates

Wednesday, August 17th, 2016

PMC (PubMed Central) has rolled out the following updates. For details about these improvements see the New in PMC site:

  1. Search Result Filters: On all search results pages, you will now see filters (similar to PubMed’s filters) on the left-hand side that allow you to filter your results by article attributes, publication date, research funder, and search fields.
  2. Reference List Display:  Using related article data available in PMC, articles that cite papers that have been either retracted or named in a Findings of Research Misconduct and not yet retracted, will now include a red hyperlink to the relevant notice directly from the articles reference list. /ch

Request for Information (RFI): Metrics to Assess Value of Biomedical Digital Repositories

Monday, August 15th, 2016

Is your library involved in biomedical digital repositories? Is your library interested in getting involved in biomedical digital repositories? This RFI gives more than a glimpse into what the National Institutes of Health goals are in this area of health information access.  This is a real opportunity for libraries to get in on the ground floor to shape future funding….read on!  jb

“Increasing access to digital research data presents significant scientific opportunities to enhance return on investment, expand accountability, and accelerate discovery and progress. To seize these opportunities, data must be managed and shared appropriately; shared data must be citable to make clear their origin and allow the authors of the data to accrue recognition; and the importance of infrastructure, such as data repositories, must be appreciated. Data often must be considered in conjunction with other related digital objects including experimental and analytical workflows, standards, data annotations, and software that act on data. As such, shared data should conform to the FAIR principles, i.e., findable, accessible, interoperable, and reusable (

The goal for NIH data management and sharing is to make publicly-funded data broadly accessible to support reuse, reproducibility and discovery while simultaneously balancing the costs and benefits. The many aspects of the data landscape must be considered in implementation of the new NIH data sharing policies. In addition to the current RFI, an RFI on NIH Data Sharing Strategies will be released in the near future to collect the community’s input on these topics.”

Full announcement.