NIH Training Library
NIH Training Library
Joelle Mornini, joelle.mornini@nih.gov
Events by this organizer
Topic
All
Artificial Intelligence / Machine Learning
Bioinformatics Software
Bulk RNA-Seq
Cancer
Cloud
Data Management
Data Resources
Data Science
Flow Cytometry
Genomics
Image Analysis
Microbiome
NCI Genomic Data Commons
NIDAP
NIH High Performance Unix Cluster Biowulf
Omics
Pathway Analysis
Programming
Proteomics
Sequencing Technologies
Single Cell RNA SEQ
Single Cell Technologies
Spatial Transcriptomics
Statistics
Transcriptomics
Variant Analysis
Format
All
Class
Distinguished Speaker
Lecture
Seminar
Webinar
Workshop
Event Organizer
All
BTEP
BYOB
CBIIT
CCR Single Cell Analysis and Sequencing Facilities
CDSL
Data Science Seminar Series
Data Sharing and Reuse Seminar Series
Earl Stadtman Investigator Program
FNL Science and Technology Group
Frederick Faculty Seminar Series
HPC Biowulf
Laboratory of Cell Biology (LCB)
Molecular Discovery Seminar Series
NCI
NCI and the Society for Immunotherapy of Cancer (SITC)
NCI CCR Liver Cancer Program (LCP)
NCI Containers and Workflows Interest Group
NCI Data Science Learning Exchange
NCI Genomic Data Commons
NCI SS/SC
NHGRI
NHLBI
NHLBI Proteomics Core
NIA
NIA Artificial Intelligence Lecture Series
NIAID
NICHD
NIDA
NIDCR
NIH
NIH HPC
NIH Metabolomics Scientific Interest Group
NIH Office of Data Science Strategy (ODSS)
NIH STRIDES
NIH Training Library
NIH.AI
Office of Cancer Clinical Proteomics Research
Qlucore
Scientific Library at Frederick
Single Cell Users Group
Systems Biology Interest Group
The NIH Metabolomics Interest Group
Past & Future Events
All
Only Past Events
Only Future Events
may
11may10:00 am11:00 amIntroduction to R and RStudio
Event Details
This is the first class in the NIH Library Introduction to R Series. This class provides a basic overview of the functionality of R programming language and RStudio. R is a programming
more
Event Details
This is the first class in the NIH Library Introduction to R Series. This class provides a basic overview of the functionality of R programming language and RStudio. R is a programming language and open source environment for statistical computing and graphics. The R class series is a comprehensive collection of training sessions offered by the NIH Library Data Services and Bioinformatics programs that is designed to teach non-programmers how to write modular code and to introduce best practices for using R for data analysis and data visualization. Each class uses both evidence-based best practices for programming and practical hands-on lessons.
By the end of this class, students should be able to: list reasons for using R; describe the purpose of the RStudio Script, Console, Environment, and Plots panes; describe the various methods for finding help on R and RStudio; organize files and directories for a set of analyses as an R Project; define the following terms as they relate to R: object, assign, comment, call, function, and arguments; and assign values to objects in R.
Students are encouraged to install R and RStudio before the class so that they can follow along with the instructor. Please bring your laptop with R and RStudio installed.
Register Here
RegisterTime
(Wednesday) 10:00 am - 11:00 am
Location
Online
Organizer
NIH Training LibraryNIH Training LibraryJoelle Mornini, joelle.mornini@nih.gov
25may1:00 pm4:00 pmRNA Seq Analysis Training
Event Details
This training will provide an introduction to RNA-seq data analysis followed by tutorials showing the use of popular RNA-seq analysis packages and preparing participants to independently run basic RNA-Seq analysis
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Event Details
This training will provide an introduction to RNA-seq data analysis followed by tutorials showing the use of popular RNA-seq analysis packages and preparing participants to independently run basic RNA-Seq analysis for expression profiling. The exercise will run on the Galaxy platform using Illumina paired-end RNA-seq data.
Participants will have a chance to: run quality control check on sequencing data; align the sequencing reads to a reference genome; generate alignment statistics and check mapping quality; measure abundance of transcripts; perform differential expression analysis; and visualize the output of RNA-seq analyses.
Register Here
RegisterTime
(Wednesday) 1:00 pm - 4:00 pm
Location
Online
Organizer
NIH Training LibraryNIH Training LibraryJoelle Mornini, joelle.mornini@nih.gov
june
09jun10:00 am11:00 amMetaCore Introductory Training
Event Details
For the Introductory Training we will cover basic topics such as: MetaCore overview; how to use MetaCore as a knowledge mining tool; how to upload data; running functional enrichments and
Event Details
For the Introductory Training we will cover basic topics such as: MetaCore overview; how to use MetaCore as a knowledge mining tool; how to upload data; running functional enrichments and exploring pathway maps; and running workflows.
Register Here
RegisterTime
(Thursday) 10:00 am - 11:00 am
Location
Online
Organizer
NIH Training LibraryNIH Training LibraryJoelle Mornini, joelle.mornini@nih.gov
15jun10:00 am3:00 pmIngenuity Pathway Analysis (IPA)
Event Details
Learn how to get started on using QIAGEN’s Ingenuity Pathway Analysis (IPA) to quickly identify biological relationships, mechanisms, pathways, functions and diseases most relevant to experimental datasets. IPA is cited
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Event Details
Learn how to get started on using QIAGEN’s Ingenuity Pathway Analysis (IPA) to quickly identify biological relationships, mechanisms, pathways, functions and diseases most relevant to experimental datasets. IPA is cited in tens of thousands of peer-reviewed articles. The class will demonstrate how to explore IPA’s knowledge & discovery tools to relate the most recent literature findings to your research. The demo session will mainly focus on biological interpretation of expression data but will also cover multi-omics analysis including variant data and phosphoproteomics.
Getting Started: fundamentals of IPA; overview of key features; search & pathway building; advanced search; building & editing pathways; using Build & Overlay tools. Dataset Analysis: data upload & analysis; interpretation of gene, transcript, protein & metabolite data; pathway analysis & canonical pathways; downstream effects & interpreting the heat map; causal regulators and their directional effect on genes, functions and diseases across multiple time points or doses; interpreting networks; comparison & multiple observations analysis; miRNA and isoform analysis; BioProfiler: define relationships between molecule activity and diseases/processes in the literature. Q & A session: A QIAGEN Ingenuity Field Applications Scientist will be available to answer individual questions or discuss specific projects.
Register Here
RegisterTime
(Wednesday) 10:00 am - 3:00 pm
Location
Online
Organizer
NIH Training LibraryNIH Training LibraryJoelle Mornini, joelle.mornini@nih.gov
16jun10:00 am11:00 amMetaCore Advanced Session
Event Details
For the Advanced Training, topics covered depend upon survey results: find key hubs using over-connectivity analysis; using Microarray repository for gene comparisons against public data; building networks with MetaCore; constructing
Event Details
For the Advanced Training, topics covered depend upon survey results: find key hubs using over-connectivity analysis; using Microarray repository for gene comparisons against public data; building networks with MetaCore; constructing your own pathway maps; performing toxicogenomic analysis in MetaCore; analyzing and building networks with miRNA and mRNA data; analyzing multi-omics data (RNA-seq, proteomics, metabolomics, etc).
Register Here
RegisterTime
(Thursday) 10:00 am - 11:00 am
Location
Online
Organizer
NIH Training LibraryNIH Training LibraryJoelle Mornini, joelle.mornini@nih.gov
21jun10:00 am11:00 amUsing Key Pathway Advisor for Pathway Analysis
Event Details
Key Pathway Advisor (KPA) is a web application for biological pathway analysis of OMICs data. This session will demonstrate using KPA to: explore the biological meaning of data; predict key
Event Details
Key Pathway Advisor (KPA) is a web application for biological pathway analysis of OMICs data. This session will demonstrate using KPA to: explore the biological meaning of data; predict key protein activity changes that could be the root cause of gene expression alterations; understand how biological pathways are impacted by data; create hypotheses about new targets, mechanisms of action, biomarkers and disease associations; and align results with current knowledge of biomarkers and drug targets. Bioinformatics experience is not required to use this tool.
Register Here
RegisterTime
(Tuesday) 10:00 am - 11:00 am
Location
Online
Organizer
NIH Training LibraryNIH Training LibraryJoelle Mornini, joelle.mornini@nih.gov