A Novel Fast Algorithm for Exon Prediction in Eukaryotic Genes using Linear Predictive Coding Model and Goertzel Algorithm based on the Z-Curve

نویسندگان

  • Hamidreza Saberkari
  • Mousa Shamsi
  • Hamed Heravi
  • Mohammad Hossein Sedaaghi
چکیده

Punctual identification of protein-coding regions in Deoxyribonucleic Acid (DNA) sequences because of their 3-base periodicity has been a challenging issue in bioinformatics. Many DSP (Digital Signal Processing) techniques have been applied for identification task and concentrated on assigning numerical values to the symbolic DNA sequence and then applying spectral analysis tools such as the short-time discrete Fourier transform (ST-DFT) to locate periodicity components. In this paper, first, the symbolic DNA sequences are converted to digital signal using the Z-curve method, which is a unique 3-D plot to illustrate DNA sequence and presents the biological behavior of DNA sequence. Then a novel fast algorithm is proposed to investigate the location of exons in DNA strand based on the combination of Linear Predictive Coding Model (LPCM) and Goertzel algorithm. The proposed algorithm leads to increase the

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Performance Improvement of the Goertzel Algorithm in Estimating of Protein Coding Regions Using Modified Anti-notch Filter and Linear Predictive Coding Model

The aim of this paper is to improve the performance of the conventional Goertzel algorithm in determining the protein coding regions in deoxyribonucleic acid (DNA) sequences. First, the symbolic DNA sequences are converted into numerical signals using electron ion interaction potential method. Then by combining the modified anti-notch filter and linear predictive coding model, we proposed an ef...

متن کامل

A Novel LSSVM Based Algorithm to Increase Accuracy of Bacterial Growth Modeling

Background: The recent progress and achievements in the advanced, accurate, and rigorously evaluated algorithms has revolutionized different aspects of the predictive microbiology including bacterial growth.Objectives: In this study, attempts were made to develop a more accurate hybrid algorithm for predicting the bacterial growth curve which can also be ...

متن کامل

تخمین مکان نواحی کدکننده پروتئین در توالی عددی DNA با استفاده پنجره با طول متغیر بر مبنای منحنی سه بعدی Z

In recent years, estimation of protein-coding regions in numerical deoxyribonucleic acid (DNA) sequences using signal processing tools has been a challenging issue in bioinformatics, owing to their 3-base periodicity. Several digital signal processing (DSP) tools have been applied in order to Identify the task and concentrated on assigning numerical values to the symbolic DNA sequence, then app...

متن کامل

Harmonics Estimation in Power Systems using a Fast Hybrid Algorithm

In this paper a novel hybrid algorithm for harmonics estimation in power systems is proposed. The estimation of the harmonic components is a nonlinear problem due to the nonlinearity of phase of sinusoids in distorted waveforms. Most researchers implemented nonlinear methods to extract the harmonic parameters. However, nonlinear methods for amplitude estimation increase time of convergence. Hen...

متن کامل

A Novel QSAR Model for the Evaluation and Prediction of (E)-N’-Benzylideneisonicotinohydrazide Derivatives as the Potent Anti-mycobacterium Tuberculosis Antibodies Using Genetic Function Approach

Abstract A dataset of (E)-N’-benzylideneisonicotinohydrazide derivatives as a potent anti-mycobacterium tuberculosis has been investigated utilizing Quantitative Structure-Activity Relationship (QSAR) techniques. Genetic Function Algorithm (GFA) and Multiple Linear Regression Analysis (MLRA) were used to select the descriptors and to generate the correlation QSAR models that relate the Mi...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2013