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  • Bibliometrics Classes
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Course Catalog

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 and Modeling Fundamentals

    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
  • Advanced PubMed

    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.

    Training Category: Databases and Searching Classes
  • Advanced Session for Partek Flow

    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.

    Training Category: Bioinformatics Classes
  • Animal Model & Model Organism Information Resources

    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.

    Training Category: Databases and Searching Classes
  • ATAC-Seq/ChIP-Seq Data Analysis in Partek Flow

    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.

    Training Category: Bioinformatics Classes
  • Best Practices for Managing Data in Spreadsheets

    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
  • Better Clinical Information Tools for Clinician Researchers

    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.

    Training Category: Databases and Searching Classes
  • Bias in Research Studies: Publication Bias

    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
  • Bibliometric Analysis Using InCites

    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

    Training Category: Bibliometrics Classes
  • Bibliometric Analysis: Using Web of Science and Scopus

    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.

    Training Category: Bibliometrics Classes
  • Bibliometrics for Portfolio Analysis

    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.

    Training Category: Bibliometrics Classes
  • Bioinformatics Single Cell Sequencing Workshop

    Overview
    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.

    Training Category: Bioinformatics Classes
  • Biomedical Business Information Resources

    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.

    Training Category: Databases and Searching Classes
  • Biosketch: Telling Your Research Stories

    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
  • BTRIS Basics for Clinical Researchers: Retrieving and Reporting Data for Active Protocols

    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.

    Class Prerequisites:
    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
  • Bulk RNA-Seq Data Analysis in Partek Flow

    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.

    Training Category: Bioinformatics Classes
  • ChIP Sequencing Data Analysis

    This training will provide an introduction to ChIP sequencing data analysis followed by a tutorial showing ChIP-seq analysis workflow and preparing participants to independently run basic ChIP-seq analysis for peak calling using a "point and click" approach on Galaxy platform. The hands-on exercise will run on a Galaxy platform using ChIP-seq data.  Participants will have a chance to: run quality control on ChIP-seq data; map raw reads to a reference genome; generate alignment statistics and check mapping quality; call peaks using MACS; annotate peaks; visualize the enriched regions.

    Training Category: Bioinformatics Classes
  • CITE-Seq Data Analysis in Partek Flow

    Attendees will learn how to use Partek Flow to identify cell subtypes using both gene and protein expression in a peripheral blood mononuclear cell (PBMC) sample using Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-Seq) technology. CITE-Seq is a multimodal single cell phenotyping method. CITE-Seq data analysis starts with importing a count matrix file, followed by QC and filtering data. Clustering analysis and dimension reduction techniques are then used to visualize and identify subtypes of cells. Differential expression detection among different subtypes will be demonstrated, followed by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Basic knowledge of Partek Flow is required.

    Training Category: Bioinformatics Classes
  • CLC Biomedical Workbench and Microbial Tools

    QIAGEN’s CLC Biomedical Genomics Workbench enables researchers to analyze NGS data without the use of command line. In this workshop, we will cover RNA-Seq and variant calling as applicable to human and other organisms. We will explore workflows within the Microbial Genomics Module, including tools for pathogen typing and metagenomics (16S and whole genome).

    Registrants will receive an email with information and instructions to install CLC Genomics Workbench before the class. Contact your systems office or TS Bioinformatics <TS-Bioinformatics@qiagen.com> for assistance with downloading the software. If you register the day before the class, you may not have time to download and properly install CLC. If you do not have the software installed, this training will be demo only.

    Training Category: Bioinformatics Classes
  • Clinical Information Decision Support Tools for Clinician Researchers

    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.

    Training Category: Databases and Searching Classes

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