 Bloom filters in bioinformatics

Bloom filters are a probabilistic data structure used for efficiently testing whether an element is a member of a set. They are particularly useful in scenarios where space efficiency is a priority and where false positives are acceptable but false negatives are not. In the context of bioinformatics, Bloom filters have several important applications, including: 1. **Sequence Data Handling**: With the massive amounts of genomic and metagenomic data generated by sequencing technologies, storage and processing efficiency is paramount.