Dr. Dawn E. Wilkins

Professor and Chair

203 Weir Hall
(662) 915-7309
dwilkins@cs.olemiss.edu

Dr. Wilkins is Professor and Chair in the Department of Computer and Information Science at the University of Mississippi in Oxford, Mississippi. In Spring of 1995, she completed her Ph.D. in the Department of Computer Science (now Electrical Engineering and Computer Science) at Vanderbilt University in Nashville, Tennessee. Her dissertation, Learning Restricted-Read Branching Programs with Queries, was concerned with the computational aspects of learning branching programs (decision dags). Her dissertation advisor was Dr. Vijay Raghavan.

Professional Research

Dr. Wilkins’ current research is generally in Machine Learning, Computational Biology, Bioinformatics and Database Systems.

As part of the Mississippi EPSCoR (Experimental Program to Stimulate Competitive Research), she is building a data provenance system called PARS (Provenance Archive and Retrieval System). PARS can be used by researchers in the state to archive, share and store provenance information about their research data and processes. She is also collaborating with Dr. Robert Doerksen, UM Medicinal Chemistry, and researchers at University of Southern Mississippi and Jackson State University on a project that uses machine learning techniques to help to better understand certain protein-protein and protein-ligand interactions.

Previously, she has collaborated with researchers at the University of Mississippi Medical Center and at St. Jude Children’s Research Hospital. The work at SJCRH was to apply machine learning and data mining techniques to DNA microarray data, mostly Affymetrix. The work was in association with the Hartwell Center for Bioinformatics and Biotechnology at St. Jude’s.

Selected Publications

• V Raghavan, D Wilkins. Learning μ-branching programs with queries, Proceedings of the Sixth Annual Conference on Computational Learning Theory, 1993.
• L Hellerstein, K Pillaipakkamnatt, V Raghavan, D Wilkins. How many queries are needed to learn? Journal of the ACM (JACM) 43 (5), 840-862, 1996.
• D Wilkins, K Pillaipakkamnatt. The effectiveness of machine learning techniques for predicting time to case disposition, Proceedings of the 6th International Conference on Artificial intelligence, 1997.
• KF Gates, PB Lawhead, DE Wilkins. Toward an adaptive WWW: a case study in customized hypermedia, New review of hypermedia and multimedia 4 (1), 89-113, 1998.
• DE Wilkins, PB Lawhead. Evaluating individuals in team projects, ACM SIGCSE Bulletin 32 (1), 172-175, 2000.
• EJ Yeoh, ME Ross, SA Shurtleff, WK Williams, D Patel, R Mahfouz, … Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling, Cancer Cell 1 (2), 133-143, 2002
• Y Ding, D Wilkins. The Effect of Normalization on Microarray Data Analysis, DNA and Cell Biology 23 (10), 635-642, 2004.
• Y Ding, D Wilkins. Improving the Performance of SVM-RFE to Select Genes in Microarray Data, BMC Bioinformatics 7 (2), S12, 2006.
• Y Ding, X Dang, H Peng, D Wilkins. Robust Clustering in High Dimensional Data Using Statistical Depths, BMC Bioinformatics 8 (7), S8, 2007.
• C Gao, X Dang, Y Chen, D Wilkins. Graph Ranking for Exploratory Gene Data Analysis, BMC Bioinformatics 10 (11), S19, 2009.
• C Vicknair, M Macias, Z Zhao, X Nan, Y Chen, D Wilkins. A Comparison of a Graph Database and a Relational Database: A Data Provenance Perspective, ACM Proceedings of the 48th Annual Southeast Regional Conference, 42, 2010.
• S Liu, RY Patel, PR Daga, H Liu, G Fu, R Doerksen, Y Chen, D Wilkins. Multi-class Joint Rule Extraction and Feature Selection for Biological Data, Bioinformatics and Biomedicine (BIBM), IEEE International Conference on Bioinformatics and Biomedicine, 2011.
• S Liu, RY Patel, PR Daga, H Liu, G Fu, RJ Doerksen, Y Chen, DE Wilkins. Combined Rule Extraction and Feature Elimination in Supervised Classification, IEEE Rransactions on Nanobioscience 11 (3), 228-236, 2012.
• S Liu, S Dissanayake, S Patel, X Dang, T Mlsna, Y Chen, D Wilkins. Learning Accurate and Interpretable Models Based on Regularized Random Forests Regression, BMC systems biology 8 (3), S5, 2014.
• T Gui, C Ma, F Wang, DE Wilkins. Survey on Swarm Intelligence Based Routing Protocols for Wireless Sensor Networks: An Extensive Study, Industrial Technology (ICIT), IEEE International Conference on, 1944-1949, 2016.
• S Zhang, Y Chen, D Wilkins. A Probabilistic Approach to Multiple-Instance Learning, International Symposium on Bioinformatics Research and Applications, 331-336, 2017.
• S Zhang, J Wang, T Ghoshal, D Wilkins, YY Mo, Y Chen, Y Zhou. lncRNA Gene Signatures for Prediction of Breast Cancer Intrinsic Subtypes and Prognosis, Genes 9 (2), 65, 2018.