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BioSunMS: a plug-in-based software for the management of patients information and the analysis of peptide profiles from mass spectrometry.

Cao Y, Wang N, Ying X, Li A, Wang H, Zhang X, Li W - BMC Med Inform Decis Mak (2009)

Bottom Line: Here we presented a plug-in-based software, BioSunMS, for both the management of patients information and serum peptide profiles-based statistical analysis.By integrating all functions into a user-friendly desktop application, BioSunMS provided a comprehensive solution for clinical researchers without any knowledge in programming, as well as a plug-in architecture platform with the possibility for developers to add or modify functions without need to recompile the entire application.BioSunMS provides a plug-in-based solution for managing, analyzing, and sharing high volumes of MALDI-TOF or SELDI-TOF MS data.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center of Computational Biology, Beijing Institute of Basic Medical Sciences, Taiping Road 27, Haidian district, Beijing 100850, PR China. labs.net@gmail.com

ABSTRACT

Background: With wide applications of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS), statistical comparison of serum peptide profiles and management of patients information play an important role in clinical studies, such as early diagnosis, personalized medicine and biomarker discovery. However, current available software tools mainly focused on data analysis rather than providing a flexible platform for both the management of patients information and mass spectrometry (MS) data analysis.

Results: Here we presented a plug-in-based software, BioSunMS, for both the management of patients information and serum peptide profiles-based statistical analysis. By integrating all functions into a user-friendly desktop application, BioSunMS provided a comprehensive solution for clinical researchers without any knowledge in programming, as well as a plug-in architecture platform with the possibility for developers to add or modify functions without need to recompile the entire application.

Conclusion: BioSunMS provides a plug-in-based solution for managing, analyzing, and sharing high volumes of MALDI-TOF or SELDI-TOF MS data. The software is freely distributed under GNU General Public License (GPL) and can be downloaded from http://sourceforge.net/projects/biosunms/.

Show MeSH
The screen shot of ROC curve. The ROC curve is used to evaluate the performance of model. The demonstrated example provides the ROC curves for classifiers constructed from SVM, KNN and Naive Bayes methods, respectively, and the correspondent areas under the ROC Curve are 0.94, 0.963 and 0.926.
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Figure 5: The screen shot of ROC curve. The ROC curve is used to evaluate the performance of model. The demonstrated example provides the ROC curves for classifiers constructed from SVM, KNN and Naive Bayes methods, respectively, and the correspondent areas under the ROC Curve are 0.94, 0.963 and 0.926.

Mentions: The fourth step in the workflow is to analyze the experimental results for identification of potential biomarkers and early diagnosis. BioSunMS provides the Wizard for general users, including extraction of MS peaks, construction of m/z matrix, sample classification and sample prediction. Advanced users can process and analyze the MS data in the Data Analysis Perspective. After building a Support Vector Machine (SVM) model on the training dataset and make prediction on the test dataset, BioSunMS uses a Receiver Operation Characteristic (ROC) curve to assess the models performance (Figure 5).


BioSunMS: a plug-in-based software for the management of patients information and the analysis of peptide profiles from mass spectrometry.

Cao Y, Wang N, Ying X, Li A, Wang H, Zhang X, Li W - BMC Med Inform Decis Mak (2009)

The screen shot of ROC curve. The ROC curve is used to evaluate the performance of model. The demonstrated example provides the ROC curves for classifiers constructed from SVM, KNN and Naive Bayes methods, respectively, and the correspondent areas under the ROC Curve are 0.94, 0.963 and 0.926.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2654546&req=5

Figure 5: The screen shot of ROC curve. The ROC curve is used to evaluate the performance of model. The demonstrated example provides the ROC curves for classifiers constructed from SVM, KNN and Naive Bayes methods, respectively, and the correspondent areas under the ROC Curve are 0.94, 0.963 and 0.926.
Mentions: The fourth step in the workflow is to analyze the experimental results for identification of potential biomarkers and early diagnosis. BioSunMS provides the Wizard for general users, including extraction of MS peaks, construction of m/z matrix, sample classification and sample prediction. Advanced users can process and analyze the MS data in the Data Analysis Perspective. After building a Support Vector Machine (SVM) model on the training dataset and make prediction on the test dataset, BioSunMS uses a Receiver Operation Characteristic (ROC) curve to assess the models performance (Figure 5).

Bottom Line: Here we presented a plug-in-based software, BioSunMS, for both the management of patients information and serum peptide profiles-based statistical analysis.By integrating all functions into a user-friendly desktop application, BioSunMS provided a comprehensive solution for clinical researchers without any knowledge in programming, as well as a plug-in architecture platform with the possibility for developers to add or modify functions without need to recompile the entire application.BioSunMS provides a plug-in-based solution for managing, analyzing, and sharing high volumes of MALDI-TOF or SELDI-TOF MS data.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center of Computational Biology, Beijing Institute of Basic Medical Sciences, Taiping Road 27, Haidian district, Beijing 100850, PR China. labs.net@gmail.com

ABSTRACT

Background: With wide applications of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS), statistical comparison of serum peptide profiles and management of patients information play an important role in clinical studies, such as early diagnosis, personalized medicine and biomarker discovery. However, current available software tools mainly focused on data analysis rather than providing a flexible platform for both the management of patients information and mass spectrometry (MS) data analysis.

Results: Here we presented a plug-in-based software, BioSunMS, for both the management of patients information and serum peptide profiles-based statistical analysis. By integrating all functions into a user-friendly desktop application, BioSunMS provided a comprehensive solution for clinical researchers without any knowledge in programming, as well as a plug-in architecture platform with the possibility for developers to add or modify functions without need to recompile the entire application.

Conclusion: BioSunMS provides a plug-in-based solution for managing, analyzing, and sharing high volumes of MALDI-TOF or SELDI-TOF MS data. The software is freely distributed under GNU General Public License (GPL) and can be downloaded from http://sourceforge.net/projects/biosunms/.

Show MeSH