Getiria Onsongo

University of Minnesota–Twin Cities

Publications

Table of contents

First-author peer-reviewed papers

  1. Getiria Onsongo, Matthew D. Stone, Susan K. Van Riper, John Chilton, Baolin Wu, LeeAnn Higgins, Troy C. Lund, John V. Carlis and Timothy J. Griffin. “ LTQ-iQuant: A freely-available software pipeline for automated and accurate protein quantification of isobaric tagged peptide data from LTQ instruments” . In journal Proteomics 2010 Oct;10(19):3533-8

    • Fulltext: Link to article in Proteomics
    • Software: download software
    • Key contributions:
      • This work was the first to develope a technique for protein relative quantification that accepts user generated training data to optimize quantification algorithm.
      • Implemented the first freely available open source software for protein relative quantification on LTQ type mass spectrometry instruments.
      • Performed a comprehensive study that compares protein relative quantification on TOF/TOF versus LTQ type instruments and showed LTQ type instruments reliably identifies and quantifies more proteins.
      • Compared performance of the developed freely available software to the widely used standard commercial software and showed the new software either outperforms or produces comparable results to the commercial software.

  2. Getiria Onsongo, Hongwei Xie, Timothy J. Griffin and John V. Carlis. “ Relational operators for prioritizing candidate biomarkers in high-throughput differential expression data” . Regular paper. In ACM BCB Conference (2010).

    • Acceptance rate: 28%
    • Fulltext: PDF
    • Software: Source Code and Supplementary Data
    • Key contributions:
      • Developed a technique for prioritizing candidate disease biomarkers using information in biological pathway databases and protein-protein interaction networks to identify promising candidate biomarkers worth of follow up validation studies.
      • Implemented the technique using relational database operators.
      • Demonstrated utility of technique by prioritizing candidate diagnostic biomarkers for progression of oral cancer from pre-malignant to malignant oral lesions and identified six promising candidate biomarkers.

  3. Getiria Onsongo, Hongwei Xie, Timothy J. Griffin and John V. Carlis. “ Generating GO Slim Using Relational Database Management Systems to Support Proteomics Analysis” . Short paper. In 21st IEEE International Symposium on Computer-Based Medical Systems (2008).

    • Fulltext: PDF, Link to article in IEEE
    • Key contributions:
      • Developed operators to dynamically generate a variant to the Gene Ontology (GO) database (GO Slim) useful in analyzing results of an experiment.
      • Enable users generate custom GO Slim databases.
      • Overcomes the need to generate a new GO Slim database whenever a new version of GO database is released.

Middle-author peer-reviewed papers

  1. Hongwei Xie, Getiria Onsongo, Jonathan Popko, Ebbing P. de Jong, Jing Cao, John V. Carlis, Robert J. Griffin, Nelson L. Rhodus and Timothy J. Griffin. “ Proteomics Analysis of Cells in Whole Saliva from Oral Cancer Patients via Value-added Three-dimensional Peptide Fractionation and Tandem Mass Spectrometry ” . In journal Molecular & Cellular Proteomics 2008, Mar; 7(3): 486-98.

    • Fulltext: Link to article in PubMed
    • Summary of main contribution:
      • This paper presents a novel proteomics methods used to characterize for the first time cells contained in whole saliva from patients diagnosed with oral squamous cell cell carcinoma. Our results confirm the potential of analyzing cells in whole saliva using our proteomics method to detect salivary markers of oral cancer and possibly other conditions of the oral cavity.

  2. Ebbing P. de Jong, Hongwei Xie, Getiria Onsongo, Matthew D. Stone, Xiao-Bing Chen, Joel A. Kooren, Eric W. Refsland, Robert J. Griffin, Frank G. Ondrey, Baolin Wu, Chap T. Le, Nelson L. Rhodus, John V. Carlis and Timothy J. Griffin. “ Quantitative Proteomics Reveals Myosin and Actin as Promising Saliva Biomarkers for Distinguishing Pre-Malignant and Malignant Oral Lesions ” . In journal PLoS ONE 2010, June 17; 5(6): e11148.

    • Fulltext: Link to article in PubMed
    • Summary of main contribution:
      • In this first-of-its kind study we used advanced mass spectrometry-based quantitative proteomics analysis to identify actin and myosin as promising saliva biomarkers for distinguishing pre-malignant and malignant oral lesions. We prioritize candidate biomarkers via bioinformatics and validate actin and myosin using western blotting. We show abundances for salivary actin and myosin distinguish oral lesion types with sensitivity and specificity rivaling other non-invasive oral cancer tests.

  3. Sricharan Bandhakavi, Matthew D. Stone, Getiria Onsongo, Susan K. Van Riper and Timothy J. Griffin. “ A Dynamic Range Compression and Three-Dimensional Peptide Fractionation Analysis Platform Expands Proteome Coverage and the Diagnostic Potential of Whole Saliva ” . In journal of Proteome Research 2009, Dec; 8(12): 5590-5600.

    • Fulltext: Link to article in PubMed
    • Summary of main contribution:
      • The large dynamic range of protein abundance in saliva hinders a comprehensive identification of proteins limiting its full diagnostic potential. In this work we use an analysis platform that coupled hexapeptide libraries for dynamic range compression (DRC) with three-dimensional (3D) peptide fractionation. This approach identified 2340 proteins in whole saliva and represents the largest saliva proteomic dataset generated using a single platform analysis. These results expand the potential for whole saliva in health monitoring/diagnostics and provide a general platform for improving proteomic coverage of complex biological fluids.

  4. Matthew D. Stone, Rick M. Odland, Thomas McGowan, Getiria Onsongo, Chaunning Tang, Nelson L. Rhodus, Pratik Jagtap, Sricharan Bandhakavi and Timothy J. Griffin. “ Novel In Situ Collection of Tumor Interstitial Fluid from Head and Neck Squamous Carcinoma Reveals a Unique Proteome with Diagnostic Potential ” . In journal Clin. Proteom. 2010, Epub 25 July.

    • Fulltext: Link to article in SpringerLink
    • Summary of main contribution:
      • Tumors lack normal drainage of secreted fluids and consequently build up tumor interstitial fluid (TIF). Unlike other bodily fluids, TIF likely contains a high proportionof tumor-specific proteins with potential as biomarkers. We evaluate a novel technique using a unique ultrafiltration catheter for in situ collection of TIF and used it to generate the first catalog of TIF proteins from head and neck squamous cell carcinoma (HNSCC).

  5. Elizabeth Shoop, Paulo Casaes, Getiria Onsongo, Lisa Lesnett, Erla Osk Petursdottir, Edward Kofi Yeboah Donkor, Dennis Tkach and Michael Cosimini. “ Data exploration tools for the Gene Ontology database ” . In journal Bioinformatics. 2004, Dec 12; 20(18):3442-54.

    • Fulltext: Link to article in PubMed
    • Summary of main contribution:
      • We develop two new tools (GoGet and GoView) built as part of an extensible web application system based on Java 2 Enterprise Edition technology that improve the ability of biologists to ask biologically interesting questions of the Gene Ontology (GO) database. GoGet has a user interface that enables users to ask biologically interesting questions such as “ What are the DNA binding proteins involved in DNA repair, but not in DNA replication? ” . GoView enables users to explore the large directed acyclic graph structure of the ontologies in the GO database.

  6. Sara Mullen and Getiria Onsongo. “ Decentralized agent-based underfrequency load shedding ” . In journal Integrated Computer-Aided Engineering accepted, 2010.

    • Fulltext: Will be made available as soon as the article is published.
    • Summary of main contribution:
      • As part of the transition to a smart grid efforts are being made to decentralize control of electric power systems and modernize protection schemes that are currently in use. One specific application of distributed control is underfrequency load shedding (UFLS), which is used to restore the load/generation balance in a power system following unusual disturbances e.g., loss of a generator. UFLS is currently performed by automatically shedding preset amounts of load without situational awareness. We develop an agent-based UFLS scheme that allows for an adaptive response to emergency loading conditions. We show the amount of load shed using this new scheme is reduced considerably compared to a traditional UFLS scheme.

  7. Sricharan Bandhakavi, Young-Mi Kim, Seung-Hyun Ro, Hongwei Xie, Getiria Onsongo, Chang-Bong Jun, Do-Hyung Kim and Timothy J. Griffin. “ Quantitative Nuclear Proteomics Identifies mTOR Regulation of DNA Damage Response ” . In journal Molecular & Cellular Proteomics 2010, Feb; 9(2): 403-14.

    • Fulltext: Link to article in PubMed
    • Summary of main contribution:
      • Cellular nutritional and energy status regulates a wide range of nuclear processes important for cell growth, survival and metabolic homeostasis. Mammalian target of rapamycin (mTOR) plays a key role in the cellular responses to nutrients. However, the nuclear processes governed mTOR have not been clearly defined. Using mass spectrometry techniques, we performed quantitative proteomics analysis to identify nuclear processes in human cells under control of mTOR. Results reveal a novel functional link between mTOR and DNA Damage Response (DDR) pathways in the nucleus potentially operating as a survival mechanism against unfavorable growth conditions.

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