Applications of Hidden Markov Chains

Applications

A profile HMM modelling a multiple sequence alignment of proteins in Pfam

HMMs can be applied in many fields where the goal is to recover a data sequence that is not immediately observable (but other data that depend on the sequence are). Applications include:

Computational finance
Single-molecule kinetic analysis
Neuroscience
Cryptanalysis
Speech recognition, including Siri
Speech synthesis
Part-of-speech tagging
Document separation in scanning solutions
Machine translation
Partial discharge
Gene prediction
Handwriting recognition
Alignment of bio-sequences
Time series analysis
Activity recognition
Protein folding
Sequence classification
Metamorphic virus detection
Sequence motif discovery (DNA and proteins)
DNA hybridization kinetics
Chromatin state discovery
Transportation forecasting
Solar irradiance variability