Marek Kimmel, Ph.D.
Ph.D., Control Technology, Silesian Technical University, Gliwice, Poland
Principal interests are stochastic modeling of genome dynamics, in particular in cancer progression, statistical and population genetics, biostatistics and bioinformatics. Examples of projects include:
- Interaction of genetic and environmental causes in genesis of lung cancer.
- Modeling metabolic pathways in airways inflammation.
- Analysis of Single Nucleotide Polymorphism (SNP) data at cancer-related loci.
- Kimmel M and Corey S. Stochastic Hypothesis of Transition from Inborn Neutropenia to AML: Interactions of Cell Population Dynamics and Population Genetics. Front Oncol, 3:89 (2013). PubMed
- Goldwasser DL and Kimmel M. Small median tumor diameter at cure threshold (<20 mm) among aggressive non-small cell lung cancers in male smokers predicts both chest X-ray and CT screening outcomes in a novel simulation framework. Int J Cancer, 132(1):189-97 (2012). PubMed
- Hicks S, Wheeler DA, Plon SE and Kimmel M. Prediction of missense mutation functionality depends on both the algorithm and sequence alignment employed. Hum Mutat, 32(6):661-8 (2011). PubMed
- Kimmel M and Mathaes M. Modeling neutral evolution of Alu elements using a branching process. BMC Genomics, 11: Suppl 1:S11 (2010). PubMed
- Goldwasser DL and Kimmel M. Modeling excess lung cancer risk among screened arm participants in the Mayo Lung Project. Cancer, 116(1):122-31, (2010). PubMed
- Wu X, Strome ED, Meng Q, Hastings PJ, Plon SE and Kimmel M. A robust estimator of mutation rates. Mutat Res, 661(1-2):101-9, (2009) PubMed
- Chen BY, Bryant DH, Cruess AE, Bylund JH, Fofanov VY, Kristensen DM, Kimmel M Lichtarge O, and Kavraki LE. Composite motifs integrating multiple protein structures increase sensitivity for function prediction. Comput Syst Bioinformatics Conf, 6:343-55 (2007). PubMed
For more publications, see listing on PubMed.
Address: Statistics MS138
2097 Duncan Hall
6100 S. Main St.
Houston, TX 77005-1892
Additional Links: Stochastic Models in Cell Biology, Genetics, and Evolution