Genomics, Transcriptomics, Proteomics, and Bioinformatics
High-Throughput Biology
From sequences to systems
Modern biology relies on genome sequencing, single-cell profiling, chromatin assays, proteomics, metabolomics, and spatial technologies to connect molecular variation with phenotype. These methods generate large datasets that require careful normalization, statistical inference, batch correction, and biological interpretation. The central challenge is distinguishing signal from noise while preserving biological heterogeneity.
What does RNA-seq primarily measure?
RNA-seq sequences cDNA derived from RNA, enabling quantification of gene expression and splicing.
Correct answer: Transcript abundance and isoform usage
Why is multiple-testing correction important in omics studies?
Large-scale inference requires control of error rates such as false discovery rate.
Correct answer: Because thousands of features are tested simultaneously, inflating false positives unless corrected statistically.
Bioinformatic Analysis and Interpretation
Sequence alignment and annotation
Bioinformatics uses alignment, assembly, variant calling, motif discovery, phylogenetics, and pathway analysis to extract meaning from sequence data. Functional annotation often combines homology, conserved domains, expression patterns, and experimental evidence. Interpretation must account for reference bias, incomplete annotations, population structure, and the fact that correlation does not imply causation.
Omics Layers
Genomics
- DNA sequence and variation
- Stable across most cell types
Transcriptomics
- RNA abundance and processing
- Highly dynamic across states
Which analysis is most appropriate for inferring evolutionary relationships among homologous sequences?
Phylogenetic methods infer branching relationships from sequence variation.
Correct answer: Phylogenetic reconstruction
What is one major limitation of bulk transcriptomics?
Single-cell methods were developed in part to overcome this limitation.
Correct answer: It averages signals across heterogeneous cells, masking cell-type-specific variation.