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Lehilahy M, Ferdi Y. Identification of exon locations in DNA sequences using a fractional digital anti-notch filter. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2022.104362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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SAVMD: An adaptive signal processing method for identifying protein coding regions. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2021.102998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Zheng Q, Chen T, Zhou W, Xie L, Su H. Gene prediction by the noise-assisted MEMD and wavelet transform for identifying the protein coding regions. Biocybern Biomed Eng 2021. [DOI: 10.1016/j.bbe.2020.12.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Sharma S, Sharma SN, Saxena R. Identification of Short Exons Disunited by a Short Intron in Eukaryotic DNA Regions. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2020; 17:1660-1670. [PMID: 30794188 DOI: 10.1109/tcbb.2019.2900040] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Weak codon bias in short exons and separation by a short intron induces difficulty in extracting period-3 component that marks the presence of exonic regions. The annotation task of such short exons has been addressed in the proposed model independent signal processing based method with following features: (a) DNA sequences have been mapped using multiple mapping schemes, (b) period-3 spectrums corresponding to multiple mappings have been optimized to enhance short exon-short intron discrimination, and (c) spectrums corresponding to multiple mapping schemes have been subjected to Principal Component Analysis (PCA) for identifying greater number of such short exons. A comparative study with other methods indicates improved detection of contiguous short exons disunited by a short intron. Apart from the annotation of exonic and intronic regions, the proposed algorithm can also complement the methods for the detection of alternative splicing by intron retention, as one of the characteristic feature for intron retention is the presence of two short exons flanking a short intron.
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Das L, Das JK, Nanda S. Detection of exon location in eukaryotic DNA using a fuzzy adaptive Gabor wavelet transform. Genomics 2020; 112:4406-4416. [PMID: 32717319 DOI: 10.1016/j.ygeno.2020.07.020] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 06/25/2020] [Accepted: 07/08/2020] [Indexed: 11/17/2022]
Abstract
The existing model-independent methods for the detection of exons in DNA could not prove to be ideal as commonly employed fixed window length strategy produces spectral leakage causing signal noise The Modified-Gabor-wavelet-transform exploits a multiscale strategy to deal with the issue to some extent. Yet, no rule regarding the occurrence of small and large exons has been specified. To overcome this randomness, scaling-factor of GWT has been adapted based on a fuzzy rule. Due to the nucleotides' genetic code and fuzzy behaviors in DNA configuration, this work could adopt the fuzzy approach. Two fuzzy membership functions (large and small) take care of the variation in the coding regions. The fuzzy-based learning parameter adaptively tunes the scale factor for fast and precise prediction of exons. The proposed approach has an immense plus point of being capable of isolating detailed sub-regions in each exon efficiently proving its efficacy comparing with existing techniques.
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Affiliation(s)
- Lopamudra Das
- School of Electronics Engineering, KIIT University, Bhubaneswar, India.
| | - J K Das
- School of Electronics Engineering, KIIT University, Bhubaneswar, India.
| | - Sarita Nanda
- School of Electronics Engineering, KIIT University, Bhubaneswar, India.
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Das L, Nanda S, Das JK. Hereditary disease prediction in eukaryotic DNA: an adaptive signal processing approach. NUCLEOSIDES NUCLEOTIDES & NUCLEIC ACIDS 2020; 39:1179-1199. [PMID: 32571139 DOI: 10.1080/15257770.2020.1780440] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
Hereditary disease prediction in eukaryotic DNA using signal processing approaches is an incredible work in bioinformatics. Researchers of various fields are trying to put forth a noninvasive approach to forecast the disease-related genes. As diseased genes are more random than the healthy ones, in this work, a comparison of the diseased gene is made against the healthy ones. An adaptive signal processing method like functional link artificial neural network-based Levenberg-Marquardt filter has been proposed in this regard. For parameter upgradation, the algorithm is modified using particle swarm optimization. Here, disease genes are discriminated from healthy ones based on the magnitude of mean square error (MSE), which is calculated through the adaptive filter. The performance of the algorithm is inspected by computing some evaluation parameters. Since accuracy is the prime concern, authors in this work have taken an attempt to improve the accuracy level compared to the existing methods. Taking the reference gene as healthy, the overall process is accomplished by categorizing the diseased and healthy targets with MSE value at a threshold of 0.012. The proposed technique predicts the test gene sets successfully.
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Affiliation(s)
- Lopamudra Das
- School of Electronics Engineering, KIIT University, Bhubaneswar, Odisha, India
| | - Sarita Nanda
- School of Electronics Engineering, KIIT University, Bhubaneswar, Odisha, India
| | - J K Das
- School of Electronics Engineering, KIIT University, Bhubaneswar, Odisha, India
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M RK, Vaegae NK. Walsh code based numerical mapping method for the identification of protein coding regions in eukaryotes. Biomed Signal Process Control 2020. [DOI: 10.1016/j.bspc.2020.101859] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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Raman Kumar M, Vaegae NK. A new numerical approach for DNA representation using modified Gabor wavelet transform for the identification of protein coding regions. Biocybern Biomed Eng 2020. [DOI: 10.1016/j.bbe.2020.03.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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Zhang X, Pan W. Exon prediction based on multiscale products of a genomic-inspired multiscale bilateral filtering. PLoS One 2019; 14:e0205050. [PMID: 30897105 PMCID: PMC6428306 DOI: 10.1371/journal.pone.0205050] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Accepted: 03/05/2019] [Indexed: 11/21/2022] Open
Abstract
Multiscale signal processing techniques such as wavelet filtering have proved to be particularly successful in predicting exon sequences. Traditional wavelet predictor is domain filtering, and enforces exon features by weighting nucleotide values with coefficients. Such a measure performs linear filtering and is not suitable for preserving the short coding exons and the exon-intron boundaries. This paper describes a prediction framework that is capable of non-linearly processing DNA sequences while achieving high prediction rates. There are two key contributions. The first is the introduction of a genomic-inspired multiscale bilateral filtering (MSBF) which exploits both weighting coefficients in the spatial domain and nucleotide similarity in the range. Similarly to wavelet transform, the MSBF is also defined as a weighted sum of nucleotides. The difference is that the MSBF takes into account the variation of nucleotides at a specific codon position. The second contribution is the exploitation of inter-scale correlation in MSBF domain to find the inter-scale dependency on the differences between the exon signal and the background noise. This favourite property is used to sharp the important structures while weakening noise. Three benchmark data sets have been used in the evaluation of considered methods. By comparison with four existing techniques, the prediction results demonstrate that: the proposed method reveals at least improvement of 4.1%, 50.5%, 25.6%, 2.5%, 10.8%, 15.5%, 11.1%, 12.3%, 9.2% and 2.4% on the exons length of 1–24, 25–49, 50–74, 75–99, 100–124, 125–149, 150–174, 175–199, 200–299 and 300–300+, respectively. The MSBF of its nonlinear nature is good at energy compaction, which makes it capable of locating the sharp variations around short exons. The direct scale multiplication of coefficients at several adjacent scales obviously enhanced exon features while the noise contents were suppressed. We show that the non-linear nature and correlation-based property achieved in proposed predictor is greater than that for traditional filtering, which leads to better exon prediction performance. There are some possible applications of this predictor. Its good localization and protection of sharp variations will make the predictor be suitable to perform fault diagnosis of aero-engine.
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Affiliation(s)
- Xiaolei Zhang
- College of Air Traffic Management, Civil Aviation Flight University of China, Guanghan, P.R. China
| | - Weijun Pan
- College of Air Traffic Management, Civil Aviation Flight University of China, Guanghan, P.R. China
- * E-mail:
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Das L, Nanda S, Das JK. An integrated approach for identification of exon locations using recursive Gauss Newton tuned adaptive Kaiser window. Genomics 2018; 111:284-296. [PMID: 30342085 DOI: 10.1016/j.ygeno.2018.10.008] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Revised: 09/11/2018] [Accepted: 10/11/2018] [Indexed: 11/27/2022]
Abstract
Identification of exon location in a DNA sequence has been considered as the most demanding and challenging research topic in the field of Bioinformatics. This work proposes a robust approach combining the Trigonometric mapping with Adaptive tuned Kaiser Windowing approach for locating the protein coding regions (EXONS) in a genetic sequence. For better convergence as well as improved accurateness, the side lobe height control parameter (β) of Kaiser Window in the proposed algorithm is made adaptive to track the changing dynamics of the genetic sequence. This yields better tracking potential of the anticipated Adaptive Kaiser algorithm as it uses the recursive Gauss Newton tuning which in turn utilizes the covariance of the error signal to tune the β factor which has been shown through numerous simulation results under a variety of practical test conditions. A detailed comparative analysis with the existing mapping schemes, windowing techniques, and other signal processing methods like SVD, AN, DFT, STDFT, WT, and ST has also been included in the paper to focus on the strength and efficiency of the proposed approach. Moreover, some critical performance parameters have been computed using the proposed approach to investigate the effectiveness and robustness of the algorithm. In addition to this, the proposed approach has also been successfully applied on a number of benchmark gene sets like Musmusculus, Homosapiens, and C. elegans, etc., where the proposed approach revealed efficient prediction of exon location in contrast to the other existing mapping methods.
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Affiliation(s)
- Lopamudra Das
- School of Electronics Engineering, KIIT University, Bhubaneswar, India.
| | - Sarita Nanda
- School of Electronics Engineering, KIIT University, Bhubaneswar, India.
| | - J K Das
- School of Electronics Engineering, KIIT University, Bhubaneswar, India.
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Ahmad M, Jung LT, Bhuiyan AA. A biological inspired fuzzy adaptive window median filter (FAWMF) for enhancing DNA signal processing. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2017; 149:11-17. [PMID: 28802326 DOI: 10.1016/j.cmpb.2017.06.021] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2016] [Revised: 05/29/2017] [Accepted: 06/23/2017] [Indexed: 06/07/2023]
Abstract
BACKGROUND AND OBJECTIVE Digital signal processing techniques commonly employ fixed length window filters to process the signal contents. DNA signals differ in characteristics from common digital signals since they carry nucleotides as contents. The nucleotides own genetic code context and fuzzy behaviors due to their special structure and order in DNA strand. Employing conventional fixed length window filters for DNA signal processing produce spectral leakage and hence results in signal noise. A biological context aware adaptive window filter is required to process the DNA signals. METHODS This paper introduces a biological inspired fuzzy adaptive window median filter (FAWMF) which computes the fuzzy membership strength of nucleotides in each slide of window and filters nucleotides based on median filtering with a combination of s-shaped and z-shaped filters. Since coding regions cause 3-base periodicity by an unbalanced nucleotides' distribution producing a relatively high bias for nucleotides' usage, such fundamental characteristic of nucleotides has been exploited in FAWMF to suppress the signal noise. RESULTS Along with adaptive response of FAWMF, a strong correlation between median nucleotides and the Π shaped filter was observed which produced enhanced discrimination between coding and non-coding regions contrary to fixed length conventional window filters. The proposed FAWMF attains a significant enhancement in coding regions identification i.e. 40% to 125% as compared to other conventional window filters tested over more than 250 benchmarked and randomly taken DNA datasets of different organisms. CONCLUSION This study proves that conventional fixed length window filters applied to DNA signals do not achieve significant results since the nucleotides carry genetic code context. The proposed FAWMF algorithm is adaptive and outperforms significantly to process DNA signal contents. The algorithm applied to variety of DNA datasets produced noteworthy discrimination between coding and non-coding regions contrary to fixed window length conventional filters.
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Affiliation(s)
- Muneer Ahmad
- College of Computer Sciences, King Faisal University, Saudi Arabia.
| | - Low Tan Jung
- Department of Computer Sciences, University Technology PETRONAS, Malaysia.
| | - Al-Amin Bhuiyan
- College of Computer Sciences, King Faisal University, Saudi Arabia.
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Zhang X, Shen Z, Zhang G, Shen Y, Chen M, Zhao J, Wu R. Short Exon Detection via Wavelet Transform Modulus Maxima. PLoS One 2016; 11:e0163088. [PMID: 27635656 PMCID: PMC5026382 DOI: 10.1371/journal.pone.0163088] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2016] [Accepted: 09/04/2016] [Indexed: 02/05/2023] Open
Abstract
The detection of short exons is a challenging open problem in the field of bioinformatics. Due to the fact that the weakness of existing model-independent methods lies in their inability to reliably detect small exons, a model-independent method based on the singularity detection with wavelet transform modulus maxima has been developed for detecting short coding sequences (exons) in eukaryotic DNA sequences. In the analysis of our method, the local maxima can capture and characterize singularities of short exons, which helps to yield significant patterns that are rarely observed with the traditional methods. In order to get some information about singularities on the differences between the exon signal and the background noise, the noise level is estimated by filtering the genomic sequence through a notch filter. Meanwhile, a fast method based on a piecewise cubic Hermite interpolating polynomial is applied to reconstruct the wavelet coefficients for improving the computational efficiency. In addition, the output measure of a paired-numerical representation calculated in both forward and reverse directions is used to incorporate a useful DNA structural property. The performances of our approach and other techniques are evaluated on two benchmark data sets. Experimental results demonstrate that the proposed method outperforms all assessed model-independent methods for detecting short exons in terms of evaluation metrics.
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Affiliation(s)
- Xiaolei Zhang
- Shantou University Medical College, Shantou, P.R. China
| | - Zhiwei Shen
- Department of Radiology, Second Affiliated Hospital of Shantou University Medical College, Shantou, P.R. China
| | - Guishan Zhang
- College of Engineering, Shantou University, Shantou, P.R. China
| | - Yuanyu Shen
- Department of Radiology, Second Affiliated Hospital of Shantou University Medical College, Shantou, P.R. China
| | - Miaomiao Chen
- Department of Radiology, Second Affiliated Hospital of Shantou University Medical College, Shantou, P.R. China
| | - Jiaxiang Zhao
- College of Electronic Information and Optical Engineering, Nankai University, Tianjin, P.R. China
- * E-mail: (JXZ); (RHW)
| | - Renhua Wu
- Department of Radiology, Second Affiliated Hospital of Shantou University Medical College, Shantou, P.R. China
- * E-mail: (JXZ); (RHW)
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