N4: A precise and highly sensitive promoter predictor using neural network fed by nearest neighbors

Abstract

Promoters, the genomic regions proximal to the transcriptional start sites (TSSs) play pivotal roles in determining the rate of transcription initiation by serving as direct docking platforms for the RNA polymerase II complex. In the postgenomic era, correct gene prediction has become one of the biggest challenges in genome annotation. Species-independent promoter prediction tools could also be useful in meta-genomics, since transcription data will not be available for microorganisms which are not cultivated. Promoter prediction in prokaryotic genomes presents unique challenges owing to their organizational properties. Several methods have been developed to predict the promoter regions of genomes in prokaryotes, including algorithms for recognition of sequence motifs, artificial neural networks, and algorithms based on genome's structure. However, none of them satisfies both criteria of sensitivity and precision. In this work, we present a modified artificial neural network fed by nearest neighbors based on DNA duplex stability, named N4, which can predict the transcription start sites of Escherichia coli with sensitivity and precision both above 94%, better than most of the existed algorithms.

Mobilizable Rolling-Circle Replicating Plasmids from Gram-Positive Bacteria: A Low-Cost Conjugative Transfer

“…Although many algorithms have been developed for the prediction of promoters in bacterial genomes (125–126), definitive identification of promoter sequences requires the use of several experimental approaches, both in vivo and in vitro (127). Among these approaches, the use of promoter-probe plasmid vectors facilitates the identification of sequence elements that are essential for promoter activity.…”

Bacterial Promoter Features Description and Their Application on E. coli in silico Prediction and Recognition Approaches

“…By using an ANN architecture fed by difference in DNA stability values between upstream and downstream regions in vicinity of known TSS, Askary et al (2009) presented an approach named N4 devoted to E. coli TSS prediction. In this paper, the ANN input sequence slides a 414-nucleotides window with sliding size of one nucleotide.…”

“…At this moment, the challenges are to analyze the available sequences and to locate TSS, promoters and other regulatory sequences (Askary et al, 2009). The purpose of this review is to provide a brief survey of promoter sequences characteristics and the advances of computer algorithms for their analysis and prediction.…”

IntergenicDB: a database for intergenic sequences

“…Apart from it, there are specific databases dedicated to store elements involved in prokaryotic gene regulation process as, RegulonDB [5], EcoGene [6], among others. The databases available have been provided input data for both motif discover [7] and predict genomic elements [2, 8, 9, 10] approaches. However, none of these databases provide an easy-to-use way to download only intergenic regions within their biological information associated.…”