Below are topic or subject areas taught by the NIH Library. Click the topic to see a list of upcoming classes or other related content. To view our full training catalog, visit the library training calendar. We are open to your feedback and suggestions related to our training program. Please suggest a class if you do not see it listed.
NIH Library classes are taught in-person in the NIH Library training rooms, Building 10, Clinical Center, near the South Entrance or virtually. In addition to classes, self-paced online tutorials are available through a variety of vendors and our library staff.
3D printing is revolutionizing biomedical research by enabling scientists to engage in creative problem solving, build customized solutions, and develop faster prototypes of their ideas. Join us to learn about the NIH Library's free 3D Printing service and how you can utilize it by printing free online models or designing your own. Participants will understand how 3D printers work and how this technology is being applied at NIH, locate resources for 3D printing software and models, and manipulate shapes to create a basic design using TinkerCAD, a free online tool. Beginners and interested individuals with no previous experience in this area are highly encouraged to attend. Upon completion of this hands-on workshop participants will design a simple personalized keychain that they can queue for printing.Training Category: Technology Classes
The National Health and Nutrition Examination Survey (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. NHANES is a major program of the National Center for Health Statistics (NCHS), part of the Centers for Disease Control and Prevention (CDC). This introductory one-hour webinar by Dr. David Carranza, PharmD, will provide an overview of the content of NHANES and how to access the data.
Embase is a biomedical and pharmacological database covering international literature from 1947 to present. Embase includes citations and unique indexing for drugs not found in PubMed. This advanced training session will focus on using Embase for general literature searching, and will cover how to use the database’s embedded tools to design advanced queries for systematic reviews and adverse drug reactions. Participants will also learn how to combine queries to increase search precision, and how to use the PICO (population, intervention, comparison, and outcome) and the PV (Pharmacovigilance) wizards.
PubMed comprises tens of millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites. This class introduces advanced PubMed features that allow for focused searches. Participants will learn how to personalize PubMed using My NCBI, use internal PubMed vocabulary lists (MeSH) to create more efficient search strategies, truncation use, and searching with Boolean operators. Additionally, skills in applying search filters, creating subject alerts, and exporting search results to bibliographic management software such as EndNote will be discussed.
The class will start with an overview of the new data visualization tool in Partek Flow – Data Viewer, which provides more flexible and easier ways to integrate information collected from the data, that helps biologists discover biological meanings. The instructor will then go through the steps on analyzing and visualizing on CITE-Seq data using the new Data Viewer in Partek Flow. For example: data import, QA/QC, data filter and normalization, clustering analysis, dimension reduction and visualize in 2/3 D, and differential expression. Benefits: Acquire advanced knowledge of the new tools available in Partek Flow to NIH researchers for Multi-omics data analysis.Who should attend: NIH staff interested in learning advanced features and Multi-omics data analysis in Partek Flow.
Animal models are used to study the development and progression of diseases and to test new treatments. Model organisms are a subset of research organisms that serve as a proxy for understanding human biology. This introductory class will cover techniques on locating biomedical research articles, patents, NIH-funded research projects, genetic information, and print and electronic books related to animal models and model organisms. The class will also discuss the differences between animal models, research organisms, and model organisms, and will review requirements and resources for the NIH Model Organism Sharing Policy.
VSClinical is designed for researchers to efficiently process the clinical interpretation of cell variants based on Association for Molecular Pathology (AMP) and American College of Medical Genetics and Genomics (ACMG) guidelines. This class will demonstrate how VSClinical enables labs to test for both germline and somatic cell variants according to the American College of Medical Genetics (ACMG) and AMP guidelines in an automated fashion. With the VSClinical interpretation hub, participants will learn how to produce customized reports, use lab knowledge databases to streamline variant classifications, and evaluate somatic and germline cell variants.
Participants will learn how to perform analysis for ATAC-Seq/ChIP-Seq data in Partek Flow. By completing this session, attendees will acquire a working knowledge of the tools available to NIH researchers for the start to finish ATAC-Seq/ChIP-Seq data analysis.
This class focuses on structuring spreadsheet data so that it is ready for data analysis, or for importing into R or Python. By the end of this class, students should be able to: describe best practices for data entry, and formatting data in spreadsheets; list common formatting mistakes; describe different approaches for handling dates in spreadsheets; identify tips for quality control and data manipulation in spreadsheets; exporting data from spreadsheets.Training Category: Data Services Classes
This class will give you an in-depth look at tools for evidence-based clinical information. Explore our available resources and learn search tips for DynaMed (clinical decision support tool), Access Medicine (decision making tool), Cochrane (evidence to inform healthcare decisions), EBMcal (clinical criteria sets and decision tree analysis tools), and PubMed shortcuts to evidence based clinical information. Learning Objectives: become familiar with the NIH Library’s clinical resource tools and know how to use them; and do better, more efficient searching using clinical resource tools.
Publication bias refers to the phenomenon where studies with statistically significant results are much more likely to be published in peer-refereed journals than studies that report a nonsignificant conclusion. Bias develops when results are pooled from published studies alone, leading to an overestimation of the effectiveness of the intervention. In this presentation we define publication bias, how it affects the results of clinical research literature reviews, how it can be detected and minimized, and how it can be prevented.Training Category: Systematic Reviews Classes
InCites is a reporting tool that allows you to analyze and visualize the publications and citations in the Web of Science Core Collection, with indicators that help you understand the context of citation counts. This class will provide an introduction to features and indicators available in InCites, which help assess publication performance. Participants will additionally learn the strengths and limitations of this tool in bibliometric analysis. How to access InCites: https://youtu.be/-VIei9MEr38
Web of Science is a database providing access to billions of cited references, dating back to 1900 in the areas of life sciences, social sciences, arts, and humanities. Scopus is a comprehensive abstract and citation database including millions of records from journals, books, and conference proceedings. Leveraging the capability of both powerful research tools to perform bibliometric analysis can provide a wealth of publication information. This class will provide an introduction to methods in assessing individual and organizational publication performance, with an emphasis on citation analysis. Participants will additionally learn different methods to explore how bibliographical data might be analyzed and retrieved using Web of Science and Scopus.
Bibliometrics, the quantitative analysis of scientific publications, is about much more than citation counts, Impact Factors, and the H-Index. When used properly, bibliometrics can provide insight into the productivity, collaboration structures, research topics, and citation impacts of publications from laboratories, institutions, and grant portfolios. In this class, participants will learn about the opportunities and limitations of bibliometrics for portfolio analysis, the types of questions that bibliometrics can address, and some of the data sources and tools available for performing this kind of research.
Thank you for your interest in the Bioinformatics and Computational Biology Symposium 2021. Registration is now closed. Contact Candice Townsend with questions about the Symposium.Training Category: Special Events
Advances in technology have reduced the cost of single cell sequencing, opening the doors to many new areas of study including transcriptome, DNA genomics, epigenomics and microbial systems. This workshop, provided by experts from across NIH, will provide an overview of single-cell sequencing, especially in single cell RNA-seq. The workshop will also highlight tips and potential approaches to related to single-cell RNA sequencing and introduce the major methods and tools available for single-cell RNA sequencing and analysis (both commercial and open source).
9:30 a.m. | Welcome and Opening Remarks
Keith Cogdill, Director, NIH Library
9:35 a.m. | Strategies and Methods in scRNA-seq Data Analysis
Li Jia, Bioinformatician, NIH Library
Single cell sequencing has reopened the definition of a cell’s identity and the ways in which that identity is regulated by the cell’s molecular circuitry. Learn the types of studies that are well suited for single cell sequencing analysis as well as how to design a single cell experiment. This session will also walk through the steps of a Single Cell RNA-Sequence (scRNA-seq) processing, common analysis strategies, and state-of-the-art analysis methods using R.
10:40 a.m. | Avoiding Common Pitfalls in Single Cell RNA-Seq Experiments
Michael Kelly, Senior Scientist, Single Cell Analysis Facility, Frederick National Laboratory
As the use of single cell sequencing becomes increasingly common, researchers may have a false sense that the technique is immune to issues that undermine the experiment, only to find limitations at the data analysis stage. The speaker will discuss various examples of potential data issues that can arise such as variability in number of targets datapoints, low gene detection, and technical batch effects. As part of this discussion the speaker will address some strategies for how to avoid them, and what they might look like in the final dataset. The speaker will also discuss some of the approaches used during a typical single cell RNA-Seq analysis workflow to help mitigate effects on your data.
12:00 p.m. | Break (1 hour)
1:00 p.m. | The Applications of Current Single Cell Sequencing
Brian J. Henson, Senior Specialist, Illumina, Inc.
The speaker will provide an overview and demonstration of the current single-cell applications available, including RNA, ATAC, CNV, TCR, Epitope, and spatial gene expression. Several examples from the literature will be highlighted as use cases for the tools. The speaker will conclude with a practical discussion on the utility and capacity of using the single-cell applications on the NovaSeq and the NextSeq 2000 benchtop sequencers.
2:00 p.m. | Single Cell Analysis in Partek Flow
Uchenna Emechebe, Genomic Application Scientist, Partek Inc.
Demonstration from a Partek scientist who will utilize Single Cell RNA-Seq data within Partek Flow to streamline Multi-omics data analysis. This GUI-based tool helps to overcome common analysis challenges on scRNA-Seq data and has built in data visualization options.
3:00 p.m. | Identifying and Interpreting the Human Liver Cellular Landscape using OmicSoft and IPA
Eric Seiser, Senior Application Scientist, QIAGEN Bioinformatics
The speaker will provide a practical example of how they utilized publicly available scRNA-Seq data in a research study. Specifically, the speaker processed scRNA-Seq human liver data using the OmicSoft single-cell analysis pipeline to identify numerous discrete cell populations. Gene signatures from these resident cells were then analyzed in Ingenuity Pathway Analysis to determine both shared and distinct cell biology in the context of pathways, regulation, and functional characteristics. These results provide insight into hepatic cells as well as the immune microenvironment within the liver.
This course will present an overview of three biomedical business databases - Pharmaprojects, GlobalData, and PitchBook. In addition, this class will provide an overview of other business information resources and search strategies.
Biosketches are used more and more in NIH internal reports. Participants will learn how to create a Biosketch with efficiency. Participants will also learn the appropriate components needed to put their best foot forward.Training Category: Writing and Editing Classes
Learn how to use the Biomedical Translational Research Information System (BTRIS) to streamline the task of gathering and reporting active protocol data. BTRIS staff will demonstrate how to run queries in BTRIS and then guide attendees through running reports for their protocols.
You must have an established BTRIS user account for access to identified data. These accounts are given to all Principal Investigators or with permission to their designees. If you do not have an account, please complete the BTRIS Access form.
For additional information on these sessions, go to the BTRIS webpage.Training Category: BTRIS Classes
Participants will learn how to use the point-and-click interface in Partek Flow for RNA-Seq analysis to go from raw data to experimental results. By completing this session, attendees will acquire a working knowledge of the tools available to NIH researchers for the start to finish RNA-Seq data analysis.