Education: Training in Bioinformatics for Beginners @ NIH

Vijayaraj Nagarajan • December 4, 2018
Education: Training in Bioinformatics for Beginners @ NIH
January 15-18, 2019
National Institutes of Health
9000 Rockville Pike
Building 60, Room 162
Bethesda, MD 20892, USA
https://faes.org/biotech82

BACKGROUND
Bioinformatics (Computational Biology) is a must skill required in every modern biomedical research lab. Installing and configuring a wide variety of computational biology tools is a cumbersome task that requires software engineering skills. This hands-on training course will introduce participants to a comprehensive set of bioinformatics concepts, tools and techniques, using a cloud based, all-in-one, fully loaded linux desktop (with windows like graphical user interface) machine, that comes with hundreds of popular computational biology (bioinformatics) tools required for a successful modern biomedical research lab.

OBJECTIVES
The participants will be provided with end-to-end hands-on training, along with introduction to basic concepts, in using popular tools and techniques for sequence analysis, structure analysis, function prediction, biological database searching, "omics" data analysis, pathway analysis, data visualization, data curation and integration, linux, R, perl and scripting basics.
HIGHLIGHTS

Participants will use a Graphic User Interface based Linux Desktop environment, specially configured for bioinformatics analysis in the Amazon Cloud.

Training provided by experienced active NIH researchers

Cookbook style bound manual for all exercises

Direct, after training support through exclusive forum membership

Continuing Education Credits
HANDS-ON SKILLS & TOOLS TAUGHT

Databases: NCBI-ENTREZ, UniProt, PDB, STRING, Others

Sequence analysis and function predictions: EMBOSS suite & others

Local Alignment: EMBOSS-WATER

Global Alignment: EMBOSS-NEEDLE

Similarity search: NCBI BLAST, PSI-BLAST

Multiple sequence alignment: Clustal Omega, MUSCLE, MAFFT

Phylogenetics: MrBayes, MEGA, FigTree and Dendroscope

Motif finding, analysis: MEME suite

Structure prediction, visualization & analysis: PyMOL, Chimera, iTASSER

Transcriptome analysis: NCBI GEO, Tuxedo tools, R

Enrichment analysis: DAVID

Pathway analysis: Cytoscape

Programming: Linux, R, Perl, Python

Platforms: EMBOSS, UGENE, H2O, Galaxy

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BACKGROUND

OBJECTIVES

HIGHLIGHTS

HANDS-ON SKILLS & TOOLS TAUGHT

Discussion forums: Education: Training in Bioinformatics for Beginners @ NIH

Start a new thread: