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Next Generation Sequencing (NGS) technologies have led to fast and inexpensive production of large amounts of biological sequence data, including nucleotide sequences and derived protein sequences. These fast-increasing volumes of data pose challenges to computational methods for annotation. Machine learning approaches, primarily supervised algorithms, have been widely used to assist with classification...
Gene regulation in eukaryotes is a very complicated and myriad procedure. It is a diverse action which include finding the protein coding regions, locating transcription factor binding sites, promoter identification and determination of cis and trans regulatory elements. Transcription factor binding prediction is very costly using experimental techniques. So computational methods can be used for prediction...
We present CARAS, a web server that allows the automatic annotation of a chloroplast genome sequence, and the visualization and editing of the annotation results interactively and in real-time. CARAS accepts a complete chloroplast genome sequence as input. First, it accurately predicts protein-coding sequences and exon-intron structures by combining the results from two types of annotation approaches:...
In this paper, we propose a new algorithm based on Fourier spectral characteristics. This technique improves the coding prediction accuracy, boosting the protein coding region and suppressing the non-coding region within the DNA sequences. We also compare this algorithm using computer simulation with commonly used techniques showing that our technique for exon region prediction provides superior properties...
Ribonucleic acid (RNA) has important structural and functional roles in the cell and plays roles in many stages of protein synthesis. The structure of RNA largely determines its function. Current physical methods for structure determination are time-consuming and expensive, thus the methods for the computational prediction of structure are necessary. Various algorithms that have been used for RNA...
Promoter identification is the first and the most important step for understanding gene transcription regulation. In this study, one new information content feature, the subsequence increment of overlapping content diversity (IOCD), is firstly presented to describe the subsequence content of plant pollII promoter. The negative datasets include five different regions of Arabidopsis thaliana complete...
The theory and methods of signal processing are becoming increasingly important in bioinformatics and systems biology. The ordinary Fourier analysis is satisfactory for the long DNA sequences to detect period-3 property, but is without impressive success for the short DNA sequences. An improved Fourier method is proposed to increase the accuracy of gene identification by amplifying period-3 behavior...
This article presents a comprehensive study on the main characteristics of a novel optimization algorithm specifically designed for simulation of protein-ligand interactions. Though design of optimization algorithms has been a research issue extensively studied by computer scientists for decades, the emerging applications in bioinformatics such as simulation of protein-ligand interactions and protein...
During the last several years, substantial progress has been made in developing high-throughput experimental techniques that produce large amounts of genomic data pertaining to molecular activities in cells. Consequently, a great deal of research is being focused on addressing important problems in molecular biology by analyzing these data using mathematical and computational approaches. Genomic signal...
Proteins function through interactions with other proteins, compounds, RNA and DNA. Prediction of protein interface sites is the key process for providing clues to the function of a protein, and is becoming increasing relevant to drug discovery. In this paper, combining the protein features with the theory of granular computing of quotient space based on protein-protein interaction sites classification...
Due to the enormous amount of data in DNA sequences to be processed, the computational complexity and speed are important issues to be considered. In this paper, a new integrative method is presented for predicting protein coding regions. We first establish a Takagi-Sugeno fuzzy model to identify the first nucleotide of a codon in coding regions, then the time-frequency characteristics of the output...
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