Computing for biological data.
WHAT IT IS
The application of computational methods to biological data, particularly sequence data.
WHAT PROBLEMS IT ADDRESSES
Assembling genomes from fragments Comparing sequences to find similarity Identifying genes and their function Analysing gene expression Studying variation between individuals and populations Analysing protein structure
WHY COMPUTATION IS NECESSARY
The data volumes are enormous, and the patterns are not visible by inspection.
WHAT A GENOME SEQUENCE IS, COMPUTATIONALLY
A very long string over a small alphabet.
WHAT THAT MEANS
Much of the field is string algorithms at scale.
WHAT SEQUENCE ALIGNMENT DOES
Finds correspondence between sequences, allowing for insertions, deletions and substitutions.
WHY IT MATTERS
Similarity suggests shared ancestry or shared function.
WHAT THE PRACTICAL TOOLS ARE
Established search and alignment programs Pipelines combining many tools Public databases of sequences and annotations
WHAT LANGUAGES DOMINATE
Python and R for analysis, with performance-critical tools in compiled languages.
WHAT SKILLS ARE REQUIRED
Programming, statistics, and enough biology to know what the question means.
