Identification of promoter through stochastic approach

Jabid, Taskeed; Anwar, Firoz; Baker, Syed Murtuza; Shoyaib, Mohammad

doi:10.1109/iccitechn.2007.4579366

Cited by 2 publications

(3 citation statements)

References 17 publications

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“…TATA-box and CAAT-box generally appears around −10 and −35 positions if transcription start site is assumed to start at position +1, yet the exact position of these consensus sequences are inconsistent. [21,22] Also, TTG-box and GC-box are variously spread in promoter region. [23] • Content sensors: These are concerned with the presence of certain patterns what often produce difference in bases composition between regulatory and non-regulatory regions.…”

Section: Type Of Information Usedmentioning

confidence: 99%

“…[5,50] In bioinformatics, applications of SVM includes splice site prediction, promoter prediction, host-pathogen separation. [51][52][53] The method explained in [22] uses statistical data for classification of promoter instead of features like TATA boxes, CAAT boxes and CpG islands. Sensitvity and specificity values attained using tetramer frequencies of bases is above 80%, still there is an opportunity for enhancement in the accuracy obtained.…”

Section: Support Vector Machinementioning

confidence: 99%

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A Review of Computational Intelligence Methods for Eukaryotic Promoter Prediction

Singh

Kaur

Goel

2015

Nucleosides, Nucleotides and Nucleic Acids

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In past decades, prediction of genes in DNA sequences has attracted the attention of many researchers but due to its complex structure it is extremely intricate to correctly locate its position. A large number of regulatory regions are present in DNA that helps in transcription of a gene. Promoter is one such region and to find its location is a challenging problem. Various computational methods for promoter prediction have been developed over the past few years. This paper reviews these promoter prediction methods. Several difficulties and pitfalls encountered by these methods are also detailed, along with future research directions.

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Section: Type Of Information Usedmentioning

confidence: 99%

Section: Support Vector Machinementioning

confidence: 99%

A Review of Computational Intelligence Methods for Eukaryotic Promoter Prediction

Singh

Kaur

Goel

2015

Nucleosides, Nucleotides and Nucleic Acids

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show abstract

“…Although, the internal information-based methods for promoter prediction can explore other features. Using slides windows is possible to extract distribution statistics from nucleotides in a subsequence [16,17,18]. Besides, there are the analysis of structural properties features.…”

Section: Introductionmentioning

confidence: 99%

CapsProm: A Capsule Network For Promoter Prediction

Moraes¹,

Luz²,

Moreira³

2021

Preprint

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Locating the promoter region in DNA sequences is of paramount importance in the field of bioinformatics. This is a problem widely studied in the literature, however, not yet fully resolved. Some researchers have presented remarkable results using convolution networks, that allowed the automatic extraction of features from a DNA chain. However, a universal architecture that could generalize to several organisms has not yet been achieved, and thus, requiring researchers to seek new architectures and hyperparameters for each new organism evaluated. In this work, we propose a versatile architecture, based on capsule network, that can accurately identify promoter sequences in raw DNA data from seven different organisms, eukaryotic, and prokaryotic. Our model, the CapsProm, could assist in the transfer of learning between organisms and expand its applicability. Furthermore the CapsProm showed competitive results, overcoming the baseline method in five out of seven of the tested datasets (F1score). The models and source code are made available at https://github.c om/lauromoraes/CapsNet-promoter.

show abstract

Identification of promoter through stochastic approach

Cited by 2 publications

References 17 publications

A Review of Computational Intelligence Methods for Eukaryotic Promoter Prediction

A Review of Computational Intelligence Methods for Eukaryotic Promoter Prediction

CapsProm: A Capsule Network For Promoter Prediction

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