Hidden Markov models.

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Metrics and Similarity Measures for Hidden Markov Models (1999, background): “1998) and Eddy" (Eddy 1996; 1998) are good overviews of the use of hidden Markov models in computational biology.”
The WRKY Transcription Factor Family in Model Plants and Crops (2017, methodology): “…have been greatly facilitated by (i) the development of the hidden Markov model (HMM), (ii) the implementation of HMMER software (Eddy, 2009), and (iii) the availability of HMM seeds for various gene families (Eddy, 1996), which were designed to increase the sensitivity of homology searches.”
Deep learning methods in protein structure prediction (2020, methodology): “Subsequent sources of improvement were more sensitive tools for mining evolutionary information such as PSI-BLAST [32] or HMMER [57], and the ever increasing nature of both the databases of available structures and sequences, with PSIPRED [58], based on a similar stack of FFNN to that used in PHD, a”