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  "Title": "Protein Feature Extraction from Profile Hidden Markov Models",
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  "Description": "Calculates a comprehensive list of features from profile\nhidden Markov models (HMMs) of proteins. Adapts and ports\nfeatures for use with HMMs instead of Position Specific Scoring\nMatrices, in order to take advantage of more accurate multiple\nsequence alignment by programs such as 'HHBlits'\n<DOI:10.1038/nmeth.1818> and 'HMMer' <http://hmmer.org>.\nFeatures calculated by this package can be used for protein\nfold classification, protein structural class prediction,\nsub-cellular localization and protein-protein interaction,\namong other tasks. Some examples of features extracted are\nfound in Song et al. (2018) <DOI:10.3390/app8010089>, Jin & Zhu\n(2021) <DOI:10.1155/2021/8629776>, Lyons et al. (2015)\n<DOI:10.1109/tnb.2015.2457906> and Saini et al. (2015)\n<DOI:10.1016/j.jtbi.2015.05.030>.",
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        "2: Autocorrelation: hmm_MB, hmm_MA, hmm_GA",
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        "Moran",
        "Geary",
        "Examples",
        "3: Covariance: hmm_AC, hmm_CC",
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        "References"
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