iPro70-FMWin: identifying Sigma70 promoters using multiple windowing and minimal features
| Autor: | Rafsan Jani, Siddiqur Rahman, Swakkhar Shatabda, Usma Aktar |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0106 biological sciences
0301 basic medicine Support Vector Machine Sigma Factor Feature selection Bacterial genome size Computational biology Biology 01 natural sciences DNA sequencing 03 medical and health sciences chemistry.chemical_compound RNA polymerase Genetics Promoter Regions Genetic Molecular Biology Internet Sequence Bacteria Promoter DNA-Directed RNA Polymerases Genomics General Medicine 030104 developmental biology ROC Curve chemistry Benchmark (computing) Algorithms Genome Bacterial Software DNA 010606 plant biology & botany |
| Zdroj: | Molecular Genetics and Genomics. 294:69-84 |
| ISSN: | 1617-4623 1617-4615 |
| DOI: | 10.1007/s00438-018-1487-5 |
| Popis: | In bacterial DNA, there are specific sequences of nucleotides called promoters that can bind to the RNA polymerase. Sigma70 ([Formula: see text]) is one of the most important promoter sequences due to its presence in most of the DNA regulatory functions. In this paper, we identify the most effective and optimal sequence-based features for prediction of [Formula: see text] promoter sequences in a bacterial genome. We used both short-range and long-range DNA sequences in our proposed method. A very small number of effective features are selected from a large number of the extracted features using multi-window of different sizes within the DNA sequences. We call our prediction method iPro70-FMWin and made it freely accessible online via a web application established at http://ipro70.pythonanywhere.com/server for the sake of convenience of the researchers. We have tested our method using a standard benchmark dataset. In the experiments, iPro70-FMWin has achieved an area under the curve of the receiver operating characteristic and accuracy of 0.959 and 90.57%, respectively, which significantly outperforms the state-of-the-art predictors. |
| Databáze: | OpenAIRE |
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