A new algorithm to train hidden Markov models for biological sequences with partial labels
Abstract 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 count...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2021-03-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12859-021-04080-0 |