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Accurate noise-robust classification of Bacillus species from MALDI-TOF MS spectra using a denoising autoencoder
In this study, we used a denoising autoencoder (DAE) to improve bacteria classification accuracy under noisy MS spectra conditions. We employed a denoising autoencoder approach to convert noisy MS spectra into latent variables representing molecular patterns in the original MS data, and the Random Forest method to classify bacterial strains by latent variables. Comparison of the DAE-RF with the CM method using the artificially noisy test samples showed that DAE-RF offers higher noise robustness. Hence, the DAE-RF method could be utilized for noise-robust, fast, and neat classification of Bacillus species according to MALDI...
Source: Journal of integrative bioinformatics - November 18, 2023 Category: Bioinformatics Authors: Yulia E Uvarova Pavel S Demenkov Irina N Kuzmicheva Artur S Venzel Elena L Mischenko Timofey V Ivanisenko Vadim M Efimov Svetlana V Bannikova Asya R Vasilieva Vladimir A Ivanisenko Sergey E Peltek Source Type: research

Reconstruction of the regulatory hypermethylation network controlling hepatocellular carcinoma development during hepatitis C viral infection
J Integr Bioinform. 2023 Nov 20. doi: 10.1515/jib-2023-0013. Online ahead of print.ABSTRACTHepatocellular carcinoma (HCC) has been associated with hepatitis C viral (HCV) infection as a potential risk factor. Nonetheless, the precise genetic regulatory mechanisms triggered by the virus, leading to virus-induced hepatocarcinogenesis, remain unclear. We hypothesized that HCV proteins might modulate the activity of aberrantly methylated HCC genes through regulatory pathways. Virus-host regulatory pathways, interactions between proteins, gene expression, transport, and stability regulation, were reconstructed using the ANDSyst...
Source: Journal of integrative bioinformatics - November 18, 2023 Category: Bioinformatics Authors: Evgeniya A Antropova Tamara M Khlebodarova Pavel S Demenkov Anastasiia R Volianskaia Artur S Venzel Nikita V Ivanisenko Alexandr D Gavrilenko Timofey V Ivanisenko Anna V Adamovskaya Polina M Revva Nikolay A Kolchanov Inna N Lavrik Vladimir A Ivanisenko Source Type: research

Accurate noise-robust classification of Bacillus species from MALDI-TOF MS spectra using a denoising autoencoder
In this study, we used a denoising autoencoder (DAE) to improve bacteria classification accuracy under noisy MS spectra conditions. We employed a denoising autoencoder approach to convert noisy MS spectra into latent variables representing molecular patterns in the original MS data, and the Random Forest method to classify bacterial strains by latent variables. Comparison of the DAE-RF with the CM method using the artificially noisy test samples showed that DAE-RF offers higher noise robustness. Hence, the DAE-RF method could be utilized for noise-robust, fast, and neat classification of Bacillus species according to MALDI...
Source: Journal of integrative bioinformatics - November 18, 2023 Category: Bioinformatics Authors: Yulia E Uvarova Pavel S Demenkov Irina N Kuzmicheva Artur S Venzel Elena L Mischenko Timofey V Ivanisenko Vadim M Efimov Svetlana V Bannikova Asya R Vasilieva Vladimir A Ivanisenko Sergey E Peltek Source Type: research

Reconstruction of the regulatory hypermethylation network controlling hepatocellular carcinoma development during hepatitis C viral infection
J Integr Bioinform. 2023 Nov 20. doi: 10.1515/jib-2023-0013. Online ahead of print.ABSTRACTHepatocellular carcinoma (HCC) has been associated with hepatitis C viral (HCV) infection as a potential risk factor. Nonetheless, the precise genetic regulatory mechanisms triggered by the virus, leading to virus-induced hepatocarcinogenesis, remain unclear. We hypothesized that HCV proteins might modulate the activity of aberrantly methylated HCC genes through regulatory pathways. Virus-host regulatory pathways, interactions between proteins, gene expression, transport, and stability regulation, were reconstructed using the ANDSyst...
Source: Journal of integrative bioinformatics - November 18, 2023 Category: Bioinformatics Authors: Evgeniya A Antropova Tamara M Khlebodarova Pavel S Demenkov Anastasiia R Volianskaia Artur S Venzel Nikita V Ivanisenko Alexandr D Gavrilenko Timofey V Ivanisenko Anna V Adamovskaya Polina M Revva Nikolay A Kolchanov Inna N Lavrik Vladimir A Ivanisenko Source Type: research

Accurate noise-robust classification of Bacillus species from MALDI-TOF MS spectra using a denoising autoencoder
In this study, we used a denoising autoencoder (DAE) to improve bacteria classification accuracy under noisy MS spectra conditions. We employed a denoising autoencoder approach to convert noisy MS spectra into latent variables representing molecular patterns in the original MS data, and the Random Forest method to classify bacterial strains by latent variables. Comparison of the DAE-RF with the CM method using the artificially noisy test samples showed that DAE-RF offers higher noise robustness. Hence, the DAE-RF method could be utilized for noise-robust, fast, and neat classification of Bacillus species according to MALDI...
Source: Journal of integrative bioinformatics - November 18, 2023 Category: Bioinformatics Authors: Yulia E Uvarova Pavel S Demenkov Irina N Kuzmicheva Artur S Venzel Elena L Mischenko Timofey V Ivanisenko Vadim M Efimov Svetlana V Bannikova Asya R Vasilieva Vladimir A Ivanisenko Sergey E Peltek Source Type: research

Reconstruction of the regulatory hypermethylation network controlling hepatocellular carcinoma development during hepatitis C viral infection
J Integr Bioinform. 2023 Nov 20. doi: 10.1515/jib-2023-0013. Online ahead of print.ABSTRACTHepatocellular carcinoma (HCC) has been associated with hepatitis C viral (HCV) infection as a potential risk factor. Nonetheless, the precise genetic regulatory mechanisms triggered by the virus, leading to virus-induced hepatocarcinogenesis, remain unclear. We hypothesized that HCV proteins might modulate the activity of aberrantly methylated HCC genes through regulatory pathways. Virus-host regulatory pathways, interactions between proteins, gene expression, transport, and stability regulation, were reconstructed using the ANDSyst...
Source: Journal of integrative bioinformatics - November 18, 2023 Category: Bioinformatics Authors: Evgeniya A Antropova Tamara M Khlebodarova Pavel S Demenkov Anastasiia R Volianskaia Artur S Venzel Nikita V Ivanisenko Alexandr D Gavrilenko Timofey V Ivanisenko Anna V Adamovskaya Polina M Revva Nikolay A Kolchanov Inna N Lavrik Vladimir A Ivanisenko Source Type: research

Accurate noise-robust classification of Bacillus species from MALDI-TOF MS spectra using a denoising autoencoder
In this study, we used a denoising autoencoder (DAE) to improve bacteria classification accuracy under noisy MS spectra conditions. We employed a denoising autoencoder approach to convert noisy MS spectra into latent variables representing molecular patterns in the original MS data, and the Random Forest method to classify bacterial strains by latent variables. Comparison of the DAE-RF with the CM method using the artificially noisy test samples showed that DAE-RF offers higher noise robustness. Hence, the DAE-RF method could be utilized for noise-robust, fast, and neat classification of Bacillus species according to MALDI...
Source: Journal of integrative bioinformatics - November 18, 2023 Category: Bioinformatics Authors: Yulia E Uvarova Pavel S Demenkov Irina N Kuzmicheva Artur S Venzel Elena L Mischenko Timofey V Ivanisenko Vadim M Efimov Svetlana V Bannikova Asya R Vasilieva Vladimir A Ivanisenko Sergey E Peltek Source Type: research

Reconstruction of the regulatory hypermethylation network controlling hepatocellular carcinoma development during hepatitis C viral infection
J Integr Bioinform. 2023 Nov 20. doi: 10.1515/jib-2023-0013. Online ahead of print.ABSTRACTHepatocellular carcinoma (HCC) has been associated with hepatitis C viral (HCV) infection as a potential risk factor. Nonetheless, the precise genetic regulatory mechanisms triggered by the virus, leading to virus-induced hepatocarcinogenesis, remain unclear. We hypothesized that HCV proteins might modulate the activity of aberrantly methylated HCC genes through regulatory pathways. Virus-host regulatory pathways, interactions between proteins, gene expression, transport, and stability regulation, were reconstructed using the ANDSyst...
Source: Journal of integrative bioinformatics - November 18, 2023 Category: Bioinformatics Authors: Evgeniya A Antropova Tamara M Khlebodarova Pavel S Demenkov Anastasiia R Volianskaia Artur S Venzel Nikita V Ivanisenko Alexandr D Gavrilenko Timofey V Ivanisenko Anna V Adamovskaya Polina M Revva Nikolay A Kolchanov Inna N Lavrik Vladimir A Ivanisenko Source Type: research

Accurate noise-robust classification of Bacillus species from MALDI-TOF MS spectra using a denoising autoencoder
In this study, we used a denoising autoencoder (DAE) to improve bacteria classification accuracy under noisy MS spectra conditions. We employed a denoising autoencoder approach to convert noisy MS spectra into latent variables representing molecular patterns in the original MS data, and the Random Forest method to classify bacterial strains by latent variables. Comparison of the DAE-RF with the CM method using the artificially noisy test samples showed that DAE-RF offers higher noise robustness. Hence, the DAE-RF method could be utilized for noise-robust, fast, and neat classification of Bacillus species according to MALDI...
Source: Journal of integrative bioinformatics - November 18, 2023 Category: Bioinformatics Authors: Yulia E Uvarova Pavel S Demenkov Irina N Kuzmicheva Artur S Venzel Elena L Mischenko Timofey V Ivanisenko Vadim M Efimov Svetlana V Bannikova Asya R Vasilieva Vladimir A Ivanisenko Sergey E Peltek Source Type: research

Reconstruction of the regulatory hypermethylation network controlling hepatocellular carcinoma development during hepatitis C viral infection
J Integr Bioinform. 2023 Nov 20. doi: 10.1515/jib-2023-0013. Online ahead of print.ABSTRACTHepatocellular carcinoma (HCC) has been associated with hepatitis C viral (HCV) infection as a potential risk factor. Nonetheless, the precise genetic regulatory mechanisms triggered by the virus, leading to virus-induced hepatocarcinogenesis, remain unclear. We hypothesized that HCV proteins might modulate the activity of aberrantly methylated HCC genes through regulatory pathways. Virus-host regulatory pathways, interactions between proteins, gene expression, transport, and stability regulation, were reconstructed using the ANDSyst...
Source: Journal of integrative bioinformatics - November 18, 2023 Category: Bioinformatics Authors: Evgeniya A Antropova Tamara M Khlebodarova Pavel S Demenkov Anastasiia R Volianskaia Artur S Venzel Nikita V Ivanisenko Alexandr D Gavrilenko Timofey V Ivanisenko Anna V Adamovskaya Polina M Revva Nikolay A Kolchanov Inna N Lavrik Vladimir A Ivanisenko Source Type: research

Accurate noise-robust classification of Bacillus species from MALDI-TOF MS spectra using a denoising autoencoder
In this study, we used a denoising autoencoder (DAE) to improve bacteria classification accuracy under noisy MS spectra conditions. We employed a denoising autoencoder approach to convert noisy MS spectra into latent variables representing molecular patterns in the original MS data, and the Random Forest method to classify bacterial strains by latent variables. Comparison of the DAE-RF with the CM method using the artificially noisy test samples showed that DAE-RF offers higher noise robustness. Hence, the DAE-RF method could be utilized for noise-robust, fast, and neat classification of Bacillus species according to MALDI...
Source: Journal of integrative bioinformatics - November 18, 2023 Category: Bioinformatics Authors: Yulia E Uvarova Pavel S Demenkov Irina N Kuzmicheva Artur S Venzel Elena L Mischenko Timofey V Ivanisenko Vadim M Efimov Svetlana V Bannikova Asya R Vasilieva Vladimir A Ivanisenko Sergey E Peltek Source Type: research

Reconstruction of the regulatory hypermethylation network controlling hepatocellular carcinoma development during hepatitis C viral infection
J Integr Bioinform. 2023 Nov 20. doi: 10.1515/jib-2023-0013. Online ahead of print.ABSTRACTHepatocellular carcinoma (HCC) has been associated with hepatitis C viral (HCV) infection as a potential risk factor. Nonetheless, the precise genetic regulatory mechanisms triggered by the virus, leading to virus-induced hepatocarcinogenesis, remain unclear. We hypothesized that HCV proteins might modulate the activity of aberrantly methylated HCC genes through regulatory pathways. Virus-host regulatory pathways, interactions between proteins, gene expression, transport, and stability regulation, were reconstructed using the ANDSyst...
Source: Journal of integrative bioinformatics - November 18, 2023 Category: Bioinformatics Authors: Evgeniya A Antropova Tamara M Khlebodarova Pavel S Demenkov Anastasiia R Volianskaia Artur S Venzel Nikita V Ivanisenko Alexandr D Gavrilenko Timofey V Ivanisenko Anna V Adamovskaya Polina M Revva Nikolay A Kolchanov Inna N Lavrik Vladimir A Ivanisenko Source Type: research

Accurate noise-robust classification of Bacillus species from MALDI-TOF MS spectra using a denoising autoencoder
In this study, we used a denoising autoencoder (DAE) to improve bacteria classification accuracy under noisy MS spectra conditions. We employed a denoising autoencoder approach to convert noisy MS spectra into latent variables representing molecular patterns in the original MS data, and the Random Forest method to classify bacterial strains by latent variables. Comparison of the DAE-RF with the CM method using the artificially noisy test samples showed that DAE-RF offers higher noise robustness. Hence, the DAE-RF method could be utilized for noise-robust, fast, and neat classification of Bacillus species according to MALDI...
Source: Journal of integrative bioinformatics - November 18, 2023 Category: Bioinformatics Authors: Yulia E Uvarova Pavel S Demenkov Irina N Kuzmicheva Artur S Venzel Elena L Mischenko Timofey V Ivanisenko Vadim M Efimov Svetlana V Bannikova Asya R Vasilieva Vladimir A Ivanisenko Sergey E Peltek Source Type: research

Reconstruction of the regulatory hypermethylation network controlling hepatocellular carcinoma development during hepatitis C viral infection
J Integr Bioinform. 2023 Nov 20. doi: 10.1515/jib-2023-0013. Online ahead of print.ABSTRACTHepatocellular carcinoma (HCC) has been associated with hepatitis C viral (HCV) infection as a potential risk factor. Nonetheless, the precise genetic regulatory mechanisms triggered by the virus, leading to virus-induced hepatocarcinogenesis, remain unclear. We hypothesized that HCV proteins might modulate the activity of aberrantly methylated HCC genes through regulatory pathways. Virus-host regulatory pathways, interactions between proteins, gene expression, transport, and stability regulation, were reconstructed using the ANDSyst...
Source: Journal of integrative bioinformatics - November 18, 2023 Category: Bioinformatics Authors: Evgeniya A Antropova Tamara M Khlebodarova Pavel S Demenkov Anastasiia R Volianskaia Artur S Venzel Nikita V Ivanisenko Alexandr D Gavrilenko Timofey V Ivanisenko Anna V Adamovskaya Polina M Revva Nikolay A Kolchanov Inna N Lavrik Vladimir A Ivanisenko Source Type: research

Accurate noise-robust classification of Bacillus species from MALDI-TOF MS spectra using a denoising autoencoder
In this study, we used a denoising autoencoder (DAE) to improve bacteria classification accuracy under noisy MS spectra conditions. We employed a denoising autoencoder approach to convert noisy MS spectra into latent variables representing molecular patterns in the original MS data, and the Random Forest method to classify bacterial strains by latent variables. Comparison of the DAE-RF with the CM method using the artificially noisy test samples showed that DAE-RF offers higher noise robustness. Hence, the DAE-RF method could be utilized for noise-robust, fast, and neat classification of Bacillus species according to MALDI...
Source: Journal of integrative bioinformatics - November 18, 2023 Category: Bioinformatics Authors: Yulia E Uvarova Pavel S Demenkov Irina N Kuzmicheva Artur S Venzel Elena L Mischenko Timofey V Ivanisenko Vadim M Efimov Svetlana V Bannikova Asya R Vasilieva Vladimir A Ivanisenko Sergey E Peltek Source Type: research