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dc.contributor.authorAlbalawi, Fahad
dc.contributor.authorChahid, Abderrazak
dc.contributor.authorGuo, Xingang
dc.contributor.authorAlbaradei, Somayah
dc.contributor.authorMagana-Mora, Arturo
dc.contributor.authorJankovic, Boris R.
dc.contributor.authorUludag, Mahmut
dc.contributor.authorVan Neste, Christophe Marc
dc.contributor.authorEssack, Magbubah
dc.contributor.authorLaleg-Kirati, Taous-Meriem
dc.contributor.authorBajic, Vladimir B.
dc.date.accessioned2019-08-27T06:28:45Z
dc.date.available2019-08-27T06:28:45Z
dc.date.issued2018-11-15
dc.identifier.urihttp://hdl.handle.net/10754/656616
dc.descriptionPolyA_Predicion_LRM_DNN is a novel method for predicting poly(A) signal (PAS) in human genomic DNA. It first utilizes signal processing transforms (Fourier-based and wavelet-based), statistics and position weight matrix PWM to generate sets of features that can help the poly(A) prediction problem to perform better due to the different aspects that these features offer. Then, it uses deep neural networks DNN and Logistic Regression Model (LRM) to distinguish between true PAS and pseudo PAS efficiently. This repository contains scripts which were used to generate three sets of features, namely: signal processing-based, statistics-based and PWM-based features. Then, we use these features to train and then test the DNN and LRM models.
dc.description.sponsorshipThis work has been supported by the King Abdullah University of Science and Technology (KAUST) Base Research Fund (BAS/1/1606-01-01) to VBB, (BAS/1/1627-01-01) to TMLK, and KAUST Office of Sponsored Research (OSR) under Awards No CARF – FCC/1/1976-17-01.
dc.publisherGitHub
dc.relation.urlhttps://github.com/EMANG-KAUST/PolyA_Prediction_LRM_DNN
dc.rightsMIT License Copyright (c) 2018 Estimation Modeling and ANalysis Group (EMAN) Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
dc.rights.urihttps://github.com/EMANG-KAUST/PolyA_Prediction_LRM_DNN/blob/master/LICENSE
dc.subjectPoly(A) signals
dc.subjectDeep learning
dc.subjectMachine learning
dc.subjectSignal processing
dc.subjectComputer science
dc.subjectBioinformatics
dc.titleCode for: PolyA Prediction using Logistic Regression Model (LRM) and Deep Neural Networks (DNN)
dc.typeSoftware
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.contributor.departmentComputer Science Program
dc.contributor.departmentComputational Bioscience Research Center (CBRC)
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.institutionTaif University, Electrical Engineering, Taif, 21944, Saudi Arabia.
dc.contributor.institutionSaudi Aramco, EXPEC-ARC, Drilling Technology Team, Dhahran, 31311, Saudi Arabia.
dc.contributor.institutionGhent University, Center for Medical Genetics Ghent (CMGG), B-9000, Ghent, Belgium.
kaust.personAlbalawi, Fahad
kaust.personChahid, Abderrazak
kaust.personGuo, Xingang
kaust.personAlbaradei, Somayah
kaust.personMagana-Mora, Arturo
kaust.personJankovic, Boris R.
kaust.personUludag, Mahmut
kaust.personVan Neste, Christophe Marc
kaust.personEssack, Magbubah
kaust.personLaleg-Kirati, Taous-Meriem
kaust.personBajic, Vladimir B.
kaust.grant.numberBAS/1/1606-01-01
kaust.grant.numberBAS/1/1627-01-01
kaust.grant.numberFCC/1/1976-17-01
display.relations<b>Is Supplement To:</b> <br/> <ul> <li><i>[Article]</i> <br/> Albalawi F, Chahid A, Guo X, Albaradei S, Magana-Mora A, et al. (2019) Hybrid model for efficient prediction of poly(A) signals in human genomic DNA. Methods. DOI: <a href="https://doi.org/10.1016/j.ymeth.2019.04.001">10.1016/j.ymeth.2019.04.001</a> HANDLE: <a href="http://hdl.handle.net/10754/631950">10754/631950</a></li></ul>


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