Notes from ICR researcher Jyoti Choudhary

[malvikasharan]

Who is a typical Ph.D. candidate, what do they already know about data science?

• most of our students come with biological science degrees or masters
• most have very little informatics.

What data types would they work with?

• General -omics data such as genomics, transcriptomics including single-cell, metabolomics, and proteomics (including arrays or cytof)
• They are interested in screening genetic or drugs/target
• They may work with protein Interactions, post-translational modifications data
• In some cases, they also handle clinical data (cancer)

what would they like to learn through data training and what would be an ideal training curriculum for them look like

• Good practices of data management and structures
• Regulations and governance of data
• Data analysis of gene/protein lists – curation and cross-referencing to other datasets -data wrangling
• Protein bioinformatics – structure and sequence-based analysis
• Coding in R or python