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Hidden Markov Models are used in bioinformatics to model biological sequences statistically. They are particularly useful in predicting the secondary and tertiary structure of proteins, as well as in gene prediction and other sequence alignments.

The FASTA algorithm is used for database sequence comparisons. It performs a heuristic search for local alignments by finding and evaluating the significance of high-scoring segment pairs.

Clustal is a widely-used algorithm for multiple sequence alignment of DNA or protein sequences. It creates alignments by first performing pairwise alignments and then constructing a profile that allows for aligning other sequences to the profile sequentially.

The Smith-Waterman algorithm performs local sequence alignment to determine similar regions between two nucleotide or protein sequences. It can also be used for database similarity searching and is often used to identify characteristic patterns.

BLAST is an algorithm for comparing primary biological sequence information. It is used for finding regions of similarity between biological sequences, which can help in identifying homologous sequences and inferring functional and evolutionary relationships.