GeNOSA: inferring and experimentally supporting quantitative gene regulatory networks in prokaryotes

Chen, Yi Hsiung; Yang, Chi; Tseng, Ching‐Ping; Huang, Hsien Da; Ho, Shinn-Ying

doi:10.1093/bioinformatics/btv075

Cited by 10 publications

(7 citation statements)

References 36 publications

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“…The IBCGA can efficiently solve large-scale feature selection problems and is useful for deriving an optimised SVM model 34 , 35 . The intelligent evolutionary algorithm is good at solving large parameter optimisation problems, such as inferring roles within a large-scale quantitative gene regulatory work 36 .…”

Section: Methodsmentioning

confidence: 99%

PredCRP: predicting and analysing the regulatory roles of CRP from its binding sites in Escherichia coli

Tsai

Wang

Yang

et al. 2018

Sci Rep

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Cyclic AMP receptor protein (CRP), a global regulator in Escherichia coli, regulates more than 180 genes via two roles: activation and repression. Few methods are available for predicting the regulatory roles from the binding sites of transcription factors. This work proposes an accurate method PredCRP to derive an optimised model (named PredCRP-model) and a set of four interpretable rules (named PredCRP-ruleset) for predicting and analysing the regulatory roles of CRP from sequences of CRP-binding sites. A dataset consisting of 169 CRP-binding sites with regulatory roles strongly supported by evidence was compiled. The PredCRP-model, using 12 informative features of CRP-binding sites, and cooperating with a support vector machine achieved a training and test accuracy of 0.98 and 0.93, respectively. PredCRP-ruleset has two activation rules and two repression rules derived using the 12 features and the decision tree method C4.5. This work further screened and identified 23 previously unobserved regulatory interactions in Escherichia coli. Using quantitative PCR for validation, PredCRP-model and PredCRP-ruleset achieved a test accuracy of 0.96 (=22/23) and 0.91 (=21/23), respectively. The proposed method is suitable for designing predictors for regulatory roles of all global regulators in Escherichia coli. PredCRP can be accessed at https://github.com/NctuICLab/PredCRP.

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Section: Methodsmentioning

confidence: 99%

PredCRP: predicting and analysing the regulatory roles of CRP from its binding sites in Escherichia coli

Tsai

Wang

Yang

et al. 2018

Sci Rep

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“…To construct the COVID-Pred method, IBCGA was used for feature selection. IBCGA is a well-known feature selection algorithm that has been used for solving biological problems such as cancer survival predictions, − protein function predictions, and modeling gene regulatory networks. , IBCGA is an efficient global optimization technique with an intelligent evolutionary algorithm (IEA) to select a small set of informative features from a large pool of candidate features while optimizing the prediction performance. COVID-Pred utilized the SVM classifier for distinguishing the HCoV and n HCoV.…”

Section: Methodsmentioning

confidence: 99%

Identification and Characterization of Species-Specific Severe Acute Respiratory Syndrome Coronavirus 2 Physicochemical Properties

Sathipati

2021

J. Proteome Res.

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There is an urgent need to elucidate the underlying mechanisms of coronavirus disease (COVID-19) so that vaccines and treatments can be devised. Severe acute respiratory syndrome coronavirus 2 has genetic similarity with bats and pangolin viruses, but a comprehensive understanding of the functions of its proteins at the amino acid sequence level is lacking. A total of 4320 sequences of human and nonhuman coronaviruses was retrieved from the Global Initiative on Sharing All Influenza Data and the National Center for Biotechnology Information. This work proposes an optimization method COVID-Pred with an efficient feature selection algorithm to classify the species-specific coronaviruses based on physicochemical properties (PCPs) of their sequences. COVID-Pred identified a set of 11 PCPs using a support vector machine and achieved 10-fold cross-validation and test accuracies of 99.53% and 97.80%, respectively. These findings could provide key insights into understanding the driving forces during the course of infection and assist in developing effective therapies.

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“…Second, this study used data from GISAID until a certain period (May 2021) and therefore inclusion of data after the cutoff date could have further added to the significance of PCPs. (Tsai et al, 2020;Chen et al, 2015). IBCGA uses an intelligent evolutionary algorithm (IEA) to select a small set of informative features while optimizing predictive performance.…”

Section: Limitations Of the Studymentioning

confidence: 99%

Tracking the amino acid changes of spike proteins across diverse host species of severe acute respiratory syndrome coronavirus 2

Sathipati¹,

Shukla²,

Ho³

2022

iScience

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GeNOSA: inferring and experimentally supporting quantitative gene regulatory networks in prokaryotes

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 10 publications

References 36 publications

PredCRP: predicting and analysing the regulatory roles of CRP from its binding sites in Escherichia coli

PredCRP: predicting and analysing the regulatory roles of CRP from its binding sites in Escherichia coli

Identification and Characterization of Species-Specific Severe Acute Respiratory Syndrome Coronavirus 2 Physicochemical Properties

Tracking the amino acid changes of spike proteins across diverse host species of severe acute respiratory syndrome coronavirus 2

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