Performance Comparison between Profiles from Hidden Markov Models and from Pseudocount Method
نویسندگان
چکیده
Remote homolog detection is one of the main issues in bioinformatics, and the profile-profile comparison is one of the most effective approaches. Recently, we have proposed a novel profile, match-node profile, constructed via profile HMM [6]. To evaluate the performance of match-node profile, we construct the profile by two popular HMM packages, HMMER [2] and SAM [4], and compared the performance of match-node profile for the remote homolog detection with that of a representative profile-profile method, COMPASS [5], in which the profile is constructed by a psedocount method.
منابع مشابه
Improving Phoneme Sequence Recognition using Phoneme Duration Information in DNN-HSMM
Improving phoneme recognition has attracted the attention of many researchers due to its applications in various fields of speech processing. Recent research achievements show that using deep neural network (DNN) in speech recognition systems significantly improves the performance of these systems. There are two phases in DNN-based phoneme recognition systems including training and testing. Mos...
متن کاملComparing the Bidirectional Baum-Welch Algorithm and the Baum-Welch Algorithm on Regular Lattice
A profile hidden Markov model (PHMM) is widely used in assigning protein sequences to protein families. In this model, the hidden states only depend on the previous hidden state and observations are independent given hidden states. In other words, in the PHMM, only the information of the left side of a hidden state is considered. However, it makes sense that considering the information of the b...
متن کاملAn Adaptive Approach to Increase Accuracy of Forward Algorithm for Solving Evaluation Problems on Unstable Statistical Data Set
Nowadays, Hidden Markov models are extensively utilized for modeling stochastic processes. These models help researchers establish and implement the desired theoretical foundations using Markov algorithms such as Forward one. however, Using Stability hypothesis and the mean statistic for determining the values of Markov functions on unstable statistical data set has led to a significant reducti...
متن کاملSpeech enhancement based on hidden Markov model using sparse code shrinkage
This paper presents a new hidden Markov model-based (HMM-based) speech enhancement framework based on the independent component analysis (ICA). We propose analytical procedures for training clean speech and noise models by the Baum re-estimation algorithm and present a Maximum a posterior (MAP) estimator based on Laplace-Gaussian (for clean speech and noise respectively) combination in the HMM ...
متن کاملComparison of artificial neural network and multivariate regression methods in prediction of soil cation exchange capacity (Case study: Ziaran region)
Investigation of soil properties like Cation Exchange Capacity (CEC) plays important roles in study of environmental reaserches as the spatial and temporal variability of this property have been led to development of indirect methods in estimation of this soil characteristic. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data...
متن کامل