کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4496930 1623923 2011 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
BacPP: Bacterial promoter prediction—A tool for accurate sigma-factor specific assignment in enterobacteria
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک علوم کشاورزی و بیولوژیک (عمومی)
پیش نمایش صفحه اول مقاله
BacPP: Bacterial promoter prediction—A tool for accurate sigma-factor specific assignment in enterobacteria
چکیده انگلیسی

Promoter sequences are well known to play a central role in gene expression. Their recognition and assignment in silico has not consolidated into a general bioinformatics method yet. Most previously available algorithms employ and are limited to σ70-dependent promoter sequences. This paper presents a new tool named BacPP, designed to recognize and predict Escherichia coli promoter sequences from background with specific accuracy for each σ factor (respectively, σ24, 86.9%; σ28, 92.8%; σ32, 91.5%; σ38, 89.3%, σ54, 97.0%; and σ70, 83.6%). BacPP is hence outstanding in recognition and assignment of sequences according to σ factor and provide circumstantial information about upstream gene sequences. This bioinformatic tool was developed by weighing rules extracted from neural networks trained with promoter sequences known to respond to a specific σ factor. Furthermore, when challenged with promoter sequences belonging to other enterobacteria BacPP maintained 76% accuracy overall.


► Promoter recognition and prediction in silico has not consolidated into a general bioinformatics method yet.
► Most previously available algorithms employ and are limited to σ70-dependent promoter sequences.
► This paper presents a new tool named BacPP, designed to recognize and predict E. coli promoter sequences from background with specific accuracy for each σ factor (respectively, σ24, 86.9%; σ28, 92.8%; σ32, 91.5%; σ38, 89.3%, σ54, 97.0%; and σ70, 83.6%).
► For promoter sequences belonging to other enterobacteria, BacPP maintained 76% accuracy overall.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Theoretical Biology - Volume 287, 21 October 2011, Pages 92–99
نویسندگان
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