Bioinformatics

Bioinformatics combines biology, computer science, and statistics to analyze biological data.

Key Areas

Transcriptomics

Gene expression analysis using RNA-Seq:

$\text{RPKM}=\frac{\text{reads mapped to gene}\times 10^9}{\text{total reads}\times \text{gene length}}$

Single-Cell Analysis

Challenge: dealing with zero inflation in scRNA-seq data.

Applications

• Cancer genomics - understanding tumor heterogeneity
• Drug discovery - identifying therapeutic targets
• Personalized medicine - tailoring treatments

Connections

• Uses Machine Learning for prediction and classification
• Causal Inference helps identify regulatory relationships
• High Dimensional Statistics addresses the $p\gg n$ problem