Bioinformatics

1. Yan Ma, Zhenyu Ding, Yong Qian, Ying-wooi Wan, Kursad Tosun, Xianglin Shi,Vincent Castranova, E. James Harner, and Nancy L Guo*. An
Integrative Genomic and Proteomic Approach to Chemosensitivity Prediction. Submitted. Appendix Supplementary

2. Guo L*, Abraham J, Flynn D.C, Castranova V, Shi X and Qian Y.Individualized Survival and Treatment Response Predictions in Breast Cancer Patients: Involvements of Phospho-EGFR and Phospho-Her2/Neu Proteins. The Open Clinical Cancer Journal, 2008, Volume 2,pp.18-31 Manuscript

3. Ma Y, Qian Y, Wei L, Abraham J, Shi X, Castranova V, Harner J, Flynn D.C. and Guo L*. Population-Based Molecular Prognosis of Breast Cancer by Transcriptional Profiling. Clinical Cancer Research, 13(7):2014-22, 2007. [Cover sidebar] Manuscript Supplementary

4. Guo L*, Abraham J, Flynn D.C, Castranova V, Shi X,Qian Y. Individualized survival and treatment response predictions for breast cancers using phospho-EGFR,phospho-ER, phospho-HER2/neu, phospho-IGF-IR/In, phospho-MAPK, and phospho-p70S6K proteins.The International Journal of Biological Markers, Vol. 22 no. 1, 2007, pp. 1-11 Manuscript

5. Ou Y, Guo L, Zhang CQ, A New Clustering Method and Its Application to Proteomic Profiling for Colon Cancer, Proc. of IASTED on Computational and Systems Biology, pp 68-71 ACTA Press, 2006.Manuscript

6. Ma Y, Ding Z, Qian Y, Shi X, Castranova V, Harner, EJ, Guo L*. Predicting Cancer Drug Response by Proteomic Profiling. Clinical Cancer Research 12(15):4583-9, 2006
Manuscript Supplementary Result table(excel)

7. Guo L*, Ma Y, Ward R, Castranova V, Shi X, Qian Y. Constructing Molecular Classifiers for Accurate Prognosis of Lung Adenocarcinoma. Clinical Cancer Research, 12(11): 3344-3354, 2006
Manuscript Supplementary

(* - Senior Author)

Software Engineering

1. Ma Y, Guo L, Cukic B. A Statistical Framework for the Prediction of Fault-Proneness. Advances in Machine Leaning Application in Software Engineering, Idea Group Inc., 2006 Manuscript

2. Guo L, Ma Y, Cukic B, Singh H. Robust Prediction of Fault-Proneness by Random Forests. Proc. 15th IEEE International Symposium on Software Reliability Engineering (ISSRE 2004), pp.417-428, IEEE Press, 2004 (Extended paper invited by Kluwer's Empirical Software Engineering) (Acceptance rate: 25%) Manuscript

3. Guo L, Mukhopadhyay S, Cukic B. Does Your Result Checker Really Check? Proc. the International Conference on Dependable Systems and Networks (DSN 2004), pp.399-405, IEEE Press, 2004 (Acceptance rate: 15%) Manuscript

4. Boddu R, Guo L, Mukhopadhyay S, Cukic B. RETNA: From Requirements to Testing in a Natural Way. Proc. 12th IEEE International Requirements Engineering Conference (RE 2004), pp.262-271, IEEE Press, 2004 (Acceptance rate: 20%) Manuscript

5. Guo L, Cukic B, Singh H. Predicting Fault Prone Modules by the Dempster-Shafer Belief Networks. Proc. 18th IEEE International Conference on Automated Software Engineering (ASE 2003), pp.249-252, IEEE Press, 2003 (Acceptance rate: 15%) Manuscript

6. Cukic B, Gunel E, Singh H, Guo L. The Theory of Software Reliability Corroboration. IEICE Transactions on Information & Systems, Vol. E86-D, No. 10, October, 2003 Manuscript

Ph.D. Dissertation

Lan Guo,Software Quality and Reliability Prediction Using Dempster-Shafer Theory,Ph.D. Dissertation,West Virginia University, 2004 .Ph.D.Dissertation

Advisor Dr.Bojan Cukic