Broadly, my research interests involve biomedical informatics and its related disciplines, namely computer science, systems engineering, molecular and cellular biology, mathematics, statistics and probability. Specifically, my interests include innovative ways to model biological interaction networks, application of probabilistic, statistical and biological methods to the analysis of biomedical data, incorporating existing biological knowledge and resources into solving biomedical problems, development of new algorithms for extracting useful information from biomedical data, as well as a little bit of graph theory in its application to biomedical informatics.
My lab group’s webpage at ASU is here: http://biocomputing.asu.edu.
My CV is available on the “About” page.
If you are interested in manuscripts, slides, posters, supplementary files, etc. not listed here, please email me directly — I’d be happy to provide them.
Publications
Verdicchio, M. P. and Kim, S. (2011) “Identifying Targets for Intervention by Analyzing Basins of Attraction.” Pacific Symposium on Biocomputing, 16, Jan 3-7 2011, Hawaii. (Manuscript, Supplements)
Bryce, D., Verdicchio M.P., Kim, S. (to appear). “Planning Interventions in Biological Networks.” ACM Transactions on Intelligent Systems and Technology
Verdicchio, M. P. and Kim, S. (2010). Reduction of Boolean Network Basins of Attraction Reveals Intervention Targets. Technical report, Arizona State University, Tempe, Arizona.
Sen, I., Verdicchio M. P., Jung, S., Trevino, R., Bittner, M., Kim, S. (2009). “Context-Specific Gene Regulations in Gene Expression Cancer Data.” Pacific Symposium on Biocomputing, 14:75-86, Jan 5-9 2009, Hawaii. (Sen and Verdicchio contributed equally as first authors)
Verdicchio, M. P. (2006). “Jump-Starting Your Bioinformatics Career as an Undergraduate: One Student’s Approach.” ACM Crossroads, Fall 2006 – 13.1.
Presentations
Verdicchio, M. P., Kim, S. (2011). “Identifying Targets for Intervention by Analyzing Basins of Attraction.” Pacific Symposium on Biocomputing, 16, Jan 7 2011, Hawaii. Invited oral and poster presentation of accepted paper.
Alterovitz, G., Verdicchio, M.P., Cavalcanti, S., Wang, M., Ramoni, M. (2011). “Reverse Engineering and Synthesis of Biomolecular Systems.” Pacific Symposium on Biocomputing, 16, Jan 3 2011, Hawaii. Session tutorial presentation with G. Alterovitz.
Verdicchio, M., Kim, S. (2009). “Boolean Network Models of Human Aging.” Invited oral and poster presentations at the Rocky ‘09 Bioinformatics Conference, December 10-12, Aspen, Colorado.
Bidaye, D., Dzifcak, J., Stracuzzi, D., Chimera, R., Verdicchio, M. P., Kim, S., Langley, P. “An Interactive Environment for Visualizing, Interpreting, and Revising Biological Process Models.” Poster presentation at RECOMB 2009 Conference, May 17-21, Tucson, Arizona.
Verdicchio, M., Zhang, X., Baral, C., Kim, S. (2008). “Learning Causal Relationships Between Genes from Steady State Data: Algorithms, Simulation and Application.” Invited oral and poster presentations at the Rocky ‘08 Bioinformatics Conference, December 4-7, Aspen, Colorado.
Zhang, X., Verdicchio, M., Baral, C., Kim, S. (2008). “Learning Causal Relationships Between Genes from Steady State Data: Algorithms, Simulation and Application.” Poster presentation at the 2008 Translational Genomics Research Institute (TGen) Scientific Retreat, Phoenix, Arizona.
Verdicchio, M., Kim, S. (2006). “Graphical Representation of Gene Regulatory Networks.” Poster presentation at the Fulton Undergraduate Research Initiative Undergraduate Research Symposium, Tempe, Arizona. (Earlier versions presented at similar symposia, November, April, 2005)
Works in Progress
Verdicchio, M. P. and Kim, S. “Effective use of replicates in microarray data.”
Verdicchio, M. P. and Kim, S. “Approximation approaches to Basins of Attraction.”
Jung, S., Verdicchio, M. P., Bittner, M., Kim, S. “Review Paper: Context-Specific Gene Regulatory Networks.”
Jung, S., Kim, S., Verdicchio, M. P. (in progress, participants not in any particular order). “Analysis of Context-Specific Bayesian Networks from Cancer Gene Expression Data.”
