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A new algorithm to train hidden Markov models for biological sequences with partial labels
BACKGROUND: Hidden Markov models (HMM) are a powerful tool for analyzing biological sequences in a wide variety of applications, from profiling functional protein families to identifying functional domains. The standard method used for HMM training is either by maximum likelihood using counting when...
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| Publicado no: | BMC Bioinformatics |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2021
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7995745/ https://ncbi.nlm.nih.gov/pubmed/33771095 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-021-04080-0 |
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