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Department of Biology
338 Gardner Hall
Ph.D., Genetics, University of Wisconsin -- Madison
M.A., Entomology, University of Kansas
B.S., Biology, University of Wisconsin -- Stevens Point
B.A., English and Philosophy, University of Wisconsin -- Milwaukee
Biology 1020 BioQuest
Biology 1650 The Unity of Life, Lab and lecture
Biology 1750 The Diversity of Life, Lab
Biology 2420 Fundamentals of Biological Investigation
Biology 3330 Genetics
SPRING 2015 schedule
I believe it is important to provide students in the natural sciences with opportunity to perform meaningful research. This experience enriches their understanding of course content and prepares them for employment and postgraduate education. Currently I am engaged in several research areas. In most cases, I prefer that students have taken Biology 3330 (Genetics) before working with me because the work of our group requires a basic understanding of genetical concepts. However, I encourage all students interested in biological research in one of the RESEARCH TOPICS we're pursuing to contact me.
software and datasets
This software simulates the spread of Japanese hops in the riparian zones of the Driftless area. The user controls ecological and life history parameter values. Each year positional and genetic information of living plants are output. An R script is also provided to visualize results and perform population genetic analyses. The compressed files also provide a pdf with documentation.
To download source code, go to the GitHub repository and select "Download ZIP". Basic instructions are in the README file, while more detailed instructions are found in the invasion.pdf documentation file.
This software simulates 1Mb chromosomal segments with a selected SNP or microsatellite at it center (500kb). New mutation, recombination, and reproduction are all accounted for. We wrote this software to produce the simulated datasets detailed in Haasl, Johnson, and Payseur (2014). It requires the use of Hudson's ms program, which is bundled with our source code. Please e-mail for source code.
Datasets for Haasl, Johnson, and Payseur (2014)
Full autosomal scan of 85 individuals of Northwestern European ancestry (population CEU) using the ksk2(20) and ksk2(1) statistics detailed in Haasl, Johnson, and Payseur (2014).
The following links will load the custom tracks into the UCSC human genome browser and open to all of chromosome 19 (takes a bit to load). However, any part of an autosome can be viewed by entering the desired region in the search box of the genome browser.
† denotes UWP undergraduate student
02. Haasl RJ and Payseur BA (2014) Remarkable selective constraints on exonic dinucleotide repeats. Evolution, 68: 2737-2744. ABSTRACT
03. Gray MM, Wegmann D, Haasl RJ, White MA, Gabreil S, Searle JB, Cuthbert RJ, Ryan PG, Payseur BA (2014) Demographic history of a recent invasion of house mice on the isolated island of Gough. Molecular Ecology, 23: 1923-1939. PDF
05. Haasl RJ, McCarty CA, and Payseur BA (2013) Genetic ancestry inference using support vector machines, and the active emergence of a unique American population. European Journal of Human Genetics, 21: 554-562. PDF
08. Haasl RJ and Payseur BA (2010) The number of alleles at a microsatellite defines the allele frequency spectrum and facilitates fast accurate estimation of θ. Molecular Biology and Evolution, 27: 2702-2715. PDF
09. Simon DP, Meethal SV, Wilson AC, Gallego MJ, Weinecke SL, Bruce E, Lyons PF, Haasl RJ, Bowen RL, Atwood CS (2009) Activin receptor signaling regulates prostatic epithelial cell adhesion and viability. Neoplasia, 11: 365.
10. Chan HW, Liu T, Verdile G, Bishop G, Haasl RJ, Smith MA, Perry G, Martins RN, Atwood CS (2008) Copper induces apoptosis of neuroblastoma cells via post-translational regulation of the expression of Bcl-2-family proteins and the TxJ mouse is a better model of hepatic than brain Cu toxicity. Intl J. Clinical and Experimental Medicine, 1: 76.
11. Chen X, Han B, Fang J, Haasl RJ (2008) Large-scale Protein-Protein Interaction prediction using novel kernel methods. Intl J. of Data Mining and Bioinformatics, 2: 145-156.
12. Haasl RJ, Ahmadi MR, Meethal SV, Gleason CE, Johnson SC, Asthana S, Bowen RL, Atwood CS (2008) A luteinizing hormone receptor intronic variant is significantly associated with decreased risk of Alzheimer's disease in males carrying an apolipoprotein E ε4 allele. BMC Medical Genetics, 9: 37.
13. Wilson AC, Salamat MS, Haasl RJ, Roche KM, Karande A, Meethal SV, Terasawa E, Bowen RL, Atwood CS (2006) Human neurons express type I GnRH receptor and respond to GnRH I by increasing luteinizing hormone expression. Journal of Endocrinology, 191: 651-663.
14. Haasl RJ, Fang J (2006) Mining protein-protein interaction data. Current Bioinformatics, 1: 197-205.
15. Meethal SV, Gallego MJ, Haasl RJ, Petras SJ, Sgro JY, Atwood CS (2006) Identification of a gonadotropin-releasing hormone receptor orthologue in Caenorhabditis elegans. BMC Evolutionary Biology, 6: 103.
16. Fang J, Haasl RJ, Dong Y, Lushington GH (2005) Discover protein signatures from protein-protein interaction data. BMC Bioinformatics, 6: 277.
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