Back-translation Using First Order Hidden Markov Models
نویسنده
چکیده
A Hidden Markov Model (HMM) is a well-studied, statistical model which, when given a sequence consisting of observable states, is used to try to estimate a sequence of hidden, or unknown, states. In addition to its extensive, theoretical mathematical role, such a model has realworld applications in a range of topics including speech recognition, financial modeling (e.g. stock market predicting), environmental studies (e.g. earthquake predictions, weather predictions, etc.), and behavioral studies (e.g. homicides, suicides, etc.) [6]. For the purposes of this paper, we will introduce and apply the HMM to the field of bioinformatics. Specifically, we will look into the use of HMMs, and the manipulation of their required training sets, in an attempt to more accurately back-translate a protein sequence into its original genomic coding strand. Since the focus of this paper lies mainly in training set variations, we have chosen to use a program known as Easyback for our HMM model. The plant Arabidopsis thaliana will provide the genomic data needed for our study.
منابع مشابه
Introducing Busy Customer Portfolio Using Hidden Markov Model
Due to the effective role of Markov models in customer relationship management (CRM), there is a lack of comprehensive literature review which contains all related literatures. In this paper the focus is on academic databases to find all the articles that had been published in 2011 and earlier. One hundred articles were identified and reviewed to find direct relevance for applying Markov models...
متن کاملSpeaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words
متن کامل
Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words
متن کامل
Speaker Identification in a Shouted Talking Environment Based on Novel Third-Order Circular Suprasegmental Hidden Markov Models
It is well known that speaker identification yields very high performance in a neutral talking environment; on the other hand, the performance has been sharply declined in a shouted talking environment. This work aims at proposing, implementing, and evaluating novel Third-Order Circular Suprasegmental Hidden Markov Models (CSPHMM3s) to improve the low performance of text-independent speaker ide...
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 کامل