Year |
Citation |
Score |
2019 |
Hartman P, Beckman K, Silverstein K, Yohe S, Schomaker M, Henzler C, Onsongo G, Lam HC, Munro S, Daniel J, Billstein B, Deshpande A, Hauge A, Mroz P, Lee W, et al. Next generation sequencing for clinical diagnostics: Five year experience of an academic laboratory. Molecular Genetics and Metabolism Reports. 19: 100464. PMID 30891420 DOI: 10.1016/J.Ymgmr.2019.100464 |
0.333 |
|
2017 |
Chambers MC, Jagtap PD, Johnson JE, McGowan T, Kumar P, Onsongo G, Guerrero CR, Barsnes H, Vaudel M, Martens L, Grüning B, Cooke IR, Heydarian M, Reddy KL, Griffin TJ. An Accessible Proteogenomics Informatics Resource for Cancer Researchers. Cancer Research. 77: e43-e46. PMID 29092937 DOI: 10.1158/0008-5472.Can-17-0331 |
0.587 |
|
2016 |
Onsongo G, Baughn LB, Bower M, Henzler C, Schomaker M, Silverstein KA, Thyagarajan B. CNV-RF Is a Random Forest-Based Copy Number Variation Detection Method Using Next-Generation Sequencing. The Journal of Molecular Diagnostics : Jmd. PMID 27597741 DOI: 10.1016/J.Jmoldx.2016.07.001 |
0.305 |
|
2016 |
McGowan T, Johnson J, Jagtap P, Onsongo G, Guerrero C, Griffin T. A multi-omics visualization platform (MVP) plug-in for Galaxy-based applications F1000research. 5. DOI: 10.7490/F1000Research.1112723.1 |
0.486 |
|
2016 |
Japtap P, Onsongo G, Guerrero C, Johnson J, McGowan T, Andrews M, Griffin T. Proteogenomics in Galaxy: Identifying novel ‘constellations’ of proteoforms using transcriptomic and proteomic data F1000research. 5. DOI: 10.7490/F1000Research.1112709.1 |
0.554 |
|
2014 |
Jagtap PD, Johnson JE, Onsongo G, Sadler FW, Murray K, Wang Y, Shenykman GM, Bandhakavi S, Smith LM, Griffin TJ. Flexible and accessible workflows for improved proteogenomic analysis using the Galaxy framework. Journal of Proteome Research. 13: 5898-908. PMID 25301683 DOI: 10.1021/Pr500812T |
0.664 |
|
2014 |
Sheynkman GM, Johnson JE, Jagtap PD, Shortreed MR, Onsongo G, Frey BL, Griffin TJ, Smith LM. Using Galaxy-P to leverage RNA-Seq for the discovery of novel protein variations. Bmc Genomics. 15: 703. PMID 25149441 DOI: 10.1186/1471-2164-15-703 |
0.688 |
|
2014 |
Onsongo G, Erdmann J, Spears MD, Chilton J, Beckman KB, Hauge A, Yohe S, Schomaker M, Bower M, Silverstein KA, Thyagarajan B. Implementation of Cloud based next generation sequencing data analysis in a clinical laboratory. Bmc Research Notes. 7: 314. PMID 24885806 DOI: 10.1186/1756-0500-7-314 |
0.316 |
|
2012 |
Zhang Y, Erdmann J, Chilton J, Onsongo G, Bower M, Beckman K, Thyagarajan B, Silverstein K, Lamblin A. CLIA-certified next-generation sequencing analysis in the cloud Bmc Proceedings. 6: 54. DOI: 10.1186/1753-6561-6-S6-P54 |
0.341 |
|
2010 |
Stone MD, Odland RM, McGowan T, Onsongo G, Tang C, Rhodus NL, Jagtap P, Bandhakavi S, Griffin TJ. Novel In Situ Collection of Tumor Interstitial Fluid from a Head and Neck Squamous Carcinoma Reveals a Unique Proteome with Diagnostic Potential. Clinical Proteomics. 6: 75-82. PMID 20930922 DOI: 10.1007/S12014-010-9050-3 |
0.613 |
|
2010 |
Onsongo G, Stone MD, Van Riper SK, Chilton J, Wu B, Higgins L, Lund TC, Carlis JV, Griffin TJ. LTQ-iQuant: A freely available software pipeline for automated and accurate protein quantification of isobaric tagged peptide data from LTQ instruments. Proteomics. 10: 3533-8. PMID 20821806 DOI: 10.1002/Pmic.201000189 |
0.667 |
|
2010 |
de Jong EP, Xie H, Onsongo G, Stone MD, Chen XB, Kooren JA, Refsland EW, Griffin RJ, Ondrey FG, Wu B, Le CT, Rhodus NL, Carlis JV, Griffin TJ. Quantitative proteomics reveals myosin and actin as promising saliva biomarkers for distinguishing pre-malignant and malignant oral lesions. Plos One. 5: e11148. PMID 20567502 DOI: 10.1371/Journal.Pone.0011148 |
0.651 |
|
2010 |
Bandhakavi S, Kim YM, Ro SH, Xie H, Onsongo G, Jun CB, Kim DH, Griffin TJ. Quantitative nuclear proteomics identifies mTOR regulation of DNA damage response. Molecular & Cellular Proteomics : McP. 9: 403-14. PMID 19955088 DOI: 10.1074/Mcp.M900326-Mcp200 |
0.539 |
|
2010 |
Onsongo G, Xie H, Griffin TJ, Carlis JV. Relational operators for prioritizing candidate biomarkers in high-throughput differential expression data 2010 Acm International Conference On Bioinformatics and Computational Biology, Acm-Bcb 2010. 25-34. DOI: 10.1145/1854776.1854786 |
0.651 |
|
2009 |
Bandhakavi S, Stone MD, Onsongo G, Van Riper SK, Griffin TJ. A dynamic range compression and three-dimensional peptide fractionation analysis platform expands proteome coverage and the diagnostic potential of whole saliva. Journal of Proteome Research. 8: 5590-600. PMID 19813771 DOI: 10.1021/Pr900675W |
0.716 |
|
2008 |
Xie H, Onsongo G, Popko J, de Jong EP, Cao J, Carlis JV, Griffin RJ, Rhodus NL, Griffin TJ. Proteomics analysis of cells in whole saliva from oral cancer patients via value-added three-dimensional peptide fractionation and tandem mass spectrometry. Molecular & Cellular Proteomics : McP. 7: 486-98. PMID 18045803 DOI: 10.1074/Mcp.M700146-Mcp200 |
0.732 |
|
2008 |
Onsongo G, Xie H, Griffin TJ, Carlis J. Generating GO slim using relational database management systems to support proteomics analysis Proceedings - Ieee Symposium On Computer-Based Medical Systems. 215-217. DOI: 10.1109/CBMS.2008.77 |
0.645 |
|
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