Hands on Training in Bioinformatics for Beginners
October 1-4,2019
Where?
National Institutes of Health
9000 Rockville Pike
Building 60, Room 162
Bethesda, MD 20892, USA
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.
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.
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 Educational 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: R, Perl, Python
- Platforms: EMBOSS, UGENE, H2O, Galaxy
For more information and registration, please visit the following page: Information and Registration
