`Our results show that TMHMM is currently the best performing transmembrane prediction program.' A. Krogh, B. Larsson, G. von Heijne, and E. L. L. Sonnhammer. Predicting transmembrane protein topology with a hidden Markov model: Application to complete genomes. Journal of Molecular Biology, 305 (3):567-580, January 2001.

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隐马尔可夫模型（英語： Hidden Markov Model ；縮寫： HMM ），或稱作隐性马尔可夫模型，是统计 模型，用来描述一个含有隐含未知参数的马尔可夫过程。其难点是从可观察的参数中确定该过程的隐含参数。

2022年4月8日 · We introduce DeepTMHMM, a deep learning protein language model-based algorithm that can detect and predict the topology of both alpha helical and beta barrels proteins with unprecedented accuracy. DeepTMHMM scales to proteomes and covers all domains of life, which makes it ideal for metagenomics analyses.

2006年11月27日 · TMHMM is a membrane protein topology prediction method based on a hidden Markov model. It predicts transmembrane helices and discriminate between soluble and membrane proteins with high degree of accuracy. Users can submit as many as 4000 protein sequences in FASTA format each time.

A Hidden Markov Model (HMM) can be used to explore this scenario. We don't get to observe the actual sequence of states (the weather on each day). Rather, we can only observe some outcome generated by each state (how many ice creams were eaten that day). ormallyF, an HMM is a Markov model for which we have a series of observed outputs x= fx 1;x ...

2025年2月2日 · What is a Hidden Markov Model (HMM)? A statistical model called a hidden markov model is used to describe systems that change between states with specific probabilities. The reason it is called “hidden” is that although the states produce observable outputs or emissions, they are not directly observable.

2004年9月22日 · Results: We describe an iterative version of the T-HMM algorithm, and evaluate its performance for the detection of distant homologs. Significant improvement over other commonly used methods is found. Availability: The software (C++, Perl) is available from the corresponding author.

In this section, we discuss the hidden Markov model or HMM, which is a state space model in which the hidden states are discrete, so x t ∈ {1, …, n s}. The observations may be discrete, y t ∈ {1, …, n y}, or continuous, y t ∈ R s n, or some combination, as we illustrate below. More details can be found in e.g., [CMR05, Fra08, Rab89].

2024年12月17日 · 隐马尔可夫模型（Hidden Markov Model, HMM）是一种统计模型，用于描述一个含有隐含未知参数的马尔可夫过程。 在 HMM 中，状态并不是直接可见的，但受状态影响的某些变量则是可见的。