Bioinformatics Core Staff

Eric Rouchka, D.Sc., Director

University of Louisville Bioinformatics Core

Director, KBRIN Bioinformatics Core

Algorithm for Sequence Analysis

Eric Rouchka, D.Sc., Computer Engineering and Computer Science


Email Eric Rouchka
Phone: 502-852-3060

Publications on google scholarResearchgate publicationsPublications on ScopusPublications on LinkedInPublications on orcidPublications on ResearcherID

Dr. Rouchka's laboratory is primarily interested in algorithmic development and design for use with high throughput genomic and transcriptomic data. The laboratory has ongoing research in the areas of understanding gene regulation from both a transcriptional and translational point of view as well as in the area of systems biology for understanding cross-tissue signalling through an ongoing collaboration with the Petruska lab. Dr. Rouchka's team also uses publicly available next-generation sequence data for studying genomic variation.

Flight RM, Harrison BJ, Mohammad F, Bunge MB, Moon LD, Petruska JC, Rouchka EC.categoryCompare, an analytical tool based on feature annotations.
Front Genet. 2014 Apr 29;5:98. doi: 10.3389/fgene.2014.00098. eCollection 2014.

Harrison BJ, Flight RM, Gomes C, Venkat G, Ellis SR, Sankar U, Twiss JL, Rouchka EC, Petruska JC., IB4-binding sensory neurons in the adult rat express a novel 3' UTR-extended isoform of CaMK4 that is associated with its localization to axons. J Comp Neurol. 2014 Feb 1;522(2):308-36. doi: 10.1002/cne.23398.

Hougland MT, Harrison BJ, Magnuson DS, Rouchka EC, Petruska JC. The Transcriptional Response of Neurotrophins and Their Tyrosine Kinase Receptors in Lumbar Sensorimotor Circuits to Spinal Cord Contusion is Affected by Injury Severity and Survival Time.Front Physiol. 2013 Jan 9;3:478. doi: 10.3389/fphys.2012.00478. eCollection 2012.

Rouchka EC, Flight RM. Proceedings of the 12th Annual UT-ORNL-KBRIN Bioinformatics Summit 2013.BMC Bioinformatics. 2013 Mar 22;14 Suppl 17:A1. No abstract available.

Mohammad F, Flight RM, Harrison BJ, Petruska JC, Rouchka EC. AbsIDconvert: an absolute approach for converting genetic identifiers at different granularities.BMC Bioinformatics. 2012 Sep 12;13:229. doi: 10.1186/1471-2105-13-229.

Nigel Cooper

University of Louisville Bioinformatics Core

Regulome and Pathway Analysis

Nigel Cooper, Ph.D., Anatomical Sciences and Neurobiology


Email Nigel Cooper
Phone: 502-852-1474

Researchgate publicationsPublications on MendeleyPublications on ScopusPublications on LinkedIn

The research interests of Dr. Cooper's laboratory are related to signal transduction and gene networks in neurons. His group is currently funded to investigate cell death and cell survival pathways in animal models of retinal ischemia, and they propose to establish signature events related to this blinding disorder. Discoveries in this field may lead to better therapeutic interventions. The relationship between the expressions of miRs and mRNAs is one area under investigation.

The laboratory's interests in bioinformatics include the potential for biomarker discovery as well as for the development of tools, resources, and other infrastructures for life sciences research. The promise of bioinformatics is that it will allow an investigator to reach beyond his/her own computational capacity to access and integrate multiple and disparate sources of information and to manage the complexities of scale inherent in genomic, molecular, cellular, and organismal systems.

Andreeva K and Cooper NG (2014)
MicroRNAs in the Neural Retina.
Int J Genomics.
Review Article ID 165897
PMID:24745005; PMC3972879

Rebolledo-Mendez JD, Vaishnav RA, Cooper NG, and Friedland RP (2013)
Cross-Kingdom Sequence Similarities Between Human micro-RNAs and Plant Viruses.
Commun Integr Biol. Sep 1;6(5):e24951.
PMID: 24228136        PMCID: PMC3821693

Schuck JB, Sun H, Penberthy WT, Cooper NG, Li X, and Smith ME ( 2011)
Transcriptomic Analysis of the Zebrafish Inner Ear Points to Growth Hormone Mediated Regeneration Following Acoustic Trauma.
BMC Neurosci.
PMID: 21888654

Wang XP and Cooper NG. (2010)
Comparative in silico analyses of cpeb1-4 with functional predictions.
Bioinform Biol Insights. 4:61-83.

Wang XP and Cooper NG. (2009)
Characterization of the transcripts and protein isoforms for cytoplasmic polyadenylation element binding protein-3 (CPEB3) in the mouse retina.
BMC Mol Biol. 10:109.

Shesh Rai, PhD

University of Louisville Bioinformatics Core

Clinical Trials Informatics

Shesh Rai, Ph.D., Department of Bioinformatics and Biostatistics


Email Shesh Rai
Phone: 502-852-4030

Researchgate publicationsPublications on ScopusPublications on LinkedInPublications on orcid

Dr. Rai is thoroughly experienced in designing (sample size) and analyzing retrospective/prospective studies in cancer and other clinical and basic science researches and behavioral interventions. He pursues developing statistical methods with real applications in heterogeneity in clinical studies, threshold dose-response models, survival analysis with incomplete and correlated data, efficient estimation in mixed effects (repeated measure) models, robust estimation in high-dimension data (bioinformatics), effects of samplng weights in log-linear models, and characterization and estimation of population risk.

Henry Roberts, Shesh N Rai, Katherine V Shannon, Susan Galandiu. Hospital Discharges for Crohn's Disease in States with High Smoking Prevalence.Journal of clinical gastroenterology (Impact Factor: 2.21). 05/2014; DOI:10.1097/MCG.0000000000000146

Shyam S Bansal, Hina Kausar, Manicka V Vadhanam, Srivani Ravoori, Jianmin Pan, Shesh N Rai, Ramesh C Gupta. Curcumin Implants, not Curcumin Diet Inhibits Estrogen-Induced Mammary Carcinogenesis in ACI rats.Cancer Prevention Research (Impact Factor: 4.89). 02/2014; DOI:10.1158/1940-6207.CAPR-13-0248

Kiwhoon Lee, Goetz Kloecker, Jianmin Pan, Shesh Rai, Neal E Dunlap. The Integration of Multimodality Care for the Treatment of Small Cell Lung Cancer in a Rural Population and Its Impact on Survival.American journal of clinical oncology (Impact Factor: 2.21). 09/2013; DOI:10.1097/COC.0b013e3182a5346d


Juw Won Park, PhD

University of Louisville Bioinformatics Core

RNA Sequencing Analysis

Juw Won Park, Ph.D., Computer Engineering & Computer Science


Email Juw Won Park
Phone: 502-852-1047

Publications on google scholarResearchgate publications

Dr. Park's research interest is in bioinformatics and computational genomics. Bioinformatics is, by nature, interdisciplinary. It combines computational and biological research together to answer important biological questions, including how diseases like cancer develop. His research focuses on the analysis of alternative mRNA splicing and its regulation in eukaryotic cells using high-throughput RNA sequencing (RNA-seq) and related genomic technologies, including their applications in biology. He also develops novel computational and statistical methods for analysis of massive genome and transcriptome data.

Bebee TW.*, Park JW.*, Sheridan KI., Warzecha CC., Cieply BW., Rohacek AM., Xing Y., Carstens RP. (2015) The splicing regulators Esrp1 and Esrp2 direct an epithelial splicing program essential for mammalian development, eLife, In Press. (* joint first authors)

Lu ZX.*, Huang Q.*,Park JW.*, Shen S., Lin L., Tokheim C., Henry MD., Xing Y. (2015) Transcriptome-wide Landscape of Pre-mRNA Alternative Splicing Associated with Metastatic Colonization, Molecular Cancer Research, 13(2):305-18. [highlight by MCR] (* joint first authors)

Shen S.*, Park JW.*, Lu ZX., Lin L., Henry MD., Wu YN., Zhou Q., Xing Y. (2014) rMATS: Robust and Flexible Detection of Differential Alternative Splicing from Replicate RNA-Seq Data, Proc. Natl. Acad. Sci. U.S.A., 111(51):E5593-601. (* joint first authors).

Guo R., Zheng L., Park JW., Lv R., Chen H., Jiao F., Xu W., Mu S., Wen H., Qiu J., Wang Z., Yang P., Wu F., Hui J., Fu X., Shi X., Shi Y., Xing Y., Lan F., Shi Y. (2014) BS69/ZMYND11 Reads and Connects Histone H3.3 Lysine 36 Trimethylation Decorated Chromatin to Regulated Pre-mRNA Processing. Molecular Cell, 56(2):298-310.

Park JW., Tokheim C., Shen S., Xing Y. (2013) Identifying differential alternative splicing events from RNA sequencing data using RNASeq-MATS. Methods in Molecular Biology: Deep Sequencing Data Analysis, Invited Book Chapter, 1038:171-179.


Julia Chariker, PhD

University of Louisville Bioinformatics Core

Networks and Data Visualization

Julia Chariker, Ph.D., Psychological and Brain Sciences


Email Julia Chariker
Phone: 502-852-1503

Publications on ScopusPublications on LinkedIn

Julia Chariker's research is focused on the effective use of visualization for scientific discovery. Visualization is a powerful tool for uncovering meaningful patterns in data. Patterns that are difficult or impossible to find in numerical representations of data, may be immediately apparent using an appropriate visualization technique. However, choosing an effective method of visualization can be challenging for scientists dealing with large scale, multidimensional data sets, such as those produced by next-generation sequencing technologies. Many traditional approaches to visualization become ineffective with large scale data, and newer methods of visualization, designed for visualizing large data sets, have not been well-evaluated in terms of their effectiveness. Dr. Chariker is interested in understanding how these new methods of visualization can be used effectively in scientific analysis.

Naaz, F., Chariker, J. H., & Pani, J. R. (2014). Computer-Based Learning: Graphical Integration of Whole and Sectional Neuroanatomy Improves Long-Term Retention. Cognition and Instruction, 32, 44-64.
Pani, J. R., Chariker, J. H., & Naaz, F., Mattingly, W., Roberts, J., & Sephton, S. E. (2014). Learning with interactive computer graphics in the undergraduate neuroscience classroom. Advances in Health Sciences Education: Theory and Practice, DOI 10.1007/s10459-013-9483-3.

Pani, J. R., Chariker, J. C., & Naaz, F. (2013). Computer based instruction of neuroanatomy: Interleaving whole and sectional representation. Anatomical Sciences Education, 6, 11-18.

Chariker, J. H., Naaz, F., & Pani, J. (2012).Item difficulty in the evaluation of computer-based instruction: An example from Neuroanatomy. Anatomical Sciences Education, 5, 63-75.

Chariker, J. H., Naaz, F., & Pani, J. (2011). Computer-based learning of neuroanatomy: A longitudinal study of learning, transfer, and retention. Journal of Educational Psychology, 103(01), 19-31.

Olfa Nasraoui

University of Louisville Bioinformatics Core

Machine Learning and Data Mining

Olfa Nasraoui, Ph.D., Computer Engineering and Computer Science

Olfa Nasraoui'S research activities and interests include Machine Learning and Data Mining, Web mining, Information Retrieval, and Data Science, and their applications to solve challenging real world interdisciplinary Big Data and Explainable AI problems. Her research has been funded mainly by the US NSF and by NASA.


Book Chapters

  • O. Nasraoui and M. Soliman, "Market-Based Profile Infrastructure: Giving Back to the User", in "Next Generation of Data Mining”, H. Kargupta, J. Han, P.S. Yu, R. Motwani, V. Kumar (Ed.), CRC Press 2009.
  • Khribi, Mohamed Koutheaïr, Mohamed Jemni, and Olfa Nasraoui. “Automatic Personalization in E-Learning Based on Recommendation Systems: An Overview.” Intelligent and Adaptive Learning Systems: Technology Enhanced Support for Learners and Teachers. IGI Global, 2012. 19-33. Web. 29 Aug. 2011
  • Bamshad Mobasher and Olfa Nasraoui, “CHAPTER 12: Web Usage Mining”, invited book chapter in “Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (Data-Centric Systems and Applications)“, Second Edition, July 2011, by Bing Liu
  • Michael Losavio, Olfa Nasraoui, Vincent Thacker, Jeff Marean, Nick Miles, Roman Yampolsky and Ibrahim Imam, “Assessing the Legal Risks in Network Forensic Probing”, In Advances in Digital Forensics V, IFIP Advances in Information and Communication Technology, Gilbert Peterson, Sujeet Shenoi, Eds, Springer 2009, Vol 306, 255-266.
  • O. Nasraoui and M. Soliman, “Market-Based Profile Infrastructure: Giving Back to the User”, in “Next Generation of Data Mining”, H. Kargupta, J. Han, P.S. Yu, R. Motwani, V. Kumar (Ed.), CRC Press 2009.
  • L. Zhuhadar, O. Nasraoui , R. Wyatt, “Knowledge Mining for Adaptive Multimedia Web-based Educational Platform“, in “Technology Enhanced Learning: Best Practices”, April, 2008, Idea Group, 2008.


  • M. Soliman, O. Nasraoui, N. Cooper. "Analysis and visualization of a literature-mined glaucoma gene interaction network". Conference: 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), August 2016.
  • Carlos Rojas, Olfa Nasraoui, Nurcan Durak, Leyla Zhuhadar, Sofiane Sellah, Zhiyong Zhang, Basheer Hawwash, Esin Saka, Elizabeth Leon, Jonatan Gomez, Fabio Gonzalez, Maha Soliman, “Knowledge Discovery in Data with Selected Java Open Source Software” CIML: Machine Learning Virtual Organizations, Computational Intelligence and Machine Learning, October 24, 2008.
  • O. Nasraoui, M. Soliman, and A. Badia. “Mining and Tracking Evolving User Profiles and More - A Real-Life Case Study”. In Proceedings of the Data Mining meets Marketing workshop, New York, NY,Nov. 2005.
David Tieri

University of Louisville Bioinformatics Core

David Tieri, PhD, Anatomical Sciences and Neurobiology


Email David Tieri
Phone: 502-852-1531

Publications on google scholarResearchgate publications

My research involves the development of hidden Markov Models which identify DNA and RNA sequences that have the potential to form g4 quadruplex structures. These structures play a key role in gene regulation of wide range of biological processes, including the regulation of telomerase. Telomerase is responsible for the lengthening of telomeres which allows for cell immortality, and is significantly upregulated in the majority of human cancers. This, along with the fact that g4 quadruplex structures show a rich structural diversity, allowing for a high degree of selectivity, suggests that they are promising therapeutic targets in oncology.

Xiaohong Li

University of Louisville Bioinformatics Core

RNA and DNA Sequencing Analysis Specialist

Xiaohong Li, Ph.D., Bioinformatics and Biostatistics


Email Xiaohong Li
Phone: 502-852-1809

Researchgate publicationsPublications on ScopusPublications on LinkedIn

Dr. Li’s primary interest is the application of statistical methods in genomic research. As part of her Ph.D. dissertation, she developed new normalization methods for high throughput RNA-seq data analysis and sample size calculation methods for designing RNA-seq experiment. She is experienced in the analysis of cDNA microarray, RNA-seq, DNA-seq,16S-seq and related pathway, and is an IPA certified analyst.

Book Chapter:
Xiaohong Li, Carolyn M. Klinge, and Susmita Datta. Novel and Alternative Bioinformatics Approaches to Understand microRNA-mRNA Interactome in Cancer Research. In Systems Biology in Cancer Research and Drug Discovery. 2012, Part 3, 267-288, DOI: 10.1007/978-94-007-4819-4_11.

Journal Articles

  • Li X, Cooper GF, Shyr Y, Wu D, Rouchka EC, et al. Inference and sample size calculations based on statistical tests in a negative binomial distribution for differential gene expression in RNA-seq data (2017). J Biom Biostat, 8.
  •  Li X, Brock GN, Rouchka EC, Cooper NG, Wu D, O’Toole TE, Gill RS, Eteleeb AM, O’Brien L, Rai SN. A comparison of per sample global scaling and per gene normalization methods for differential expression analysis of RNA-seq data (2017). PLoS One.12(5):e0176185.
  • Song M, Li X, Zhang X, Shi H, Vos, M, Wei X, Wang Y, Gao H, Rouchka EC, Yin x, Zhou Z, Prough R, Cave M, McClain CJ. Dietary copper-fructose interactions alter gut microbial activity in male rats (2017). Am Journal of Physiology Gastrointest and Liver Physiol. PMID:29025734
  • Xiaohong Li, Ryan Gill, Nigel G. F. Cooper, Jae Keun Yoo and Susmita Datta. Modeling microRNA-mRNA interactions using PLS regression in human colon cancer (2011). BMC Med Genomics 4:44 (highly accessed).
Mark Farman

University of Kentucky

Director, UK Advanced Genetic Technologies Center

Bioinformatics Education and Training

Mark Farman, Ph.D., Plant Pathology


Email Mark Farman
Phone: 859-218-0728

Researchgate publicationsPublications on ScopusPublications on LinkedInPubFacts for Mark Farman

Mark Farman's research interest lie in the study of Phytopathogenic fungi; fungal genetics; the fungal genome: structure and evolution; molecular evolution of host specificity; molecular genetics of oomycetes.

UK Advanced Genetic Technologies Center

Peter T Nelson, Steven Estus, Erin L Abner, Ishita Parikh, Manasi Malik, Janna H Neltner, Eseosa Ighodaro, Wang-Xia Wang, Bernard R Wilfred, Li-San Wang, Walter A Kukull, Kannabiran Nandakumar, Mark L Farman, Wayne W Poon,Maria M Corrada, Claudia H Kawas, David H Cribbs, David A Bennett, Julie A Schneider, Eric B Larson, Paul K Crane,Otto Valladares, Frederick A Schmitt, Richard J Kryscio, Gregory A Jicha, Charles D Smith, Stephen W Scheff, Joshua A Sonnen, Jonathan L Haines, Margaret A Pericak-Vance, Richard Mayeux, Lindsay A Farrer, Linda J Van Eldik, Craig Horbinski, Robert C Green, Marla Gearing, Leonard W Poon, Patricia L Kramer, Randall L Woltjer, Thomas J Montine,Amanda B Partch, Alexander J Rajic, KatieRose Richmire, Sarah E Monsell, , Gerard D Schellenberg, David W Fardo. ABCC9 gene polymorphism is associated with hippocampal sclerosis of aging pathology. Acta Neuropathol. 2014 Jun 27;127(6):825-43. Epub 2014 Apr 27.

Christopher L Schardl, Carolyn A Young, Juan Pan, Simona Florea, Johanna E Takach, Daniel G Panaccione, Mark L Farman, Jennifer S Webb, Jolanta Jaromczyk, Nikki D Charlton, Padmaja Nagabhyru, Li Chen, Chong Shi, Adrian Leuchtmann. Currencies of mutualisms: sources of alkaloid genes in vertically transmitted epichloae.Toxins (Basel) 2013 Jun 6;5(6):1064-88. Epub 2013 Jun 6.

Christopher L Schardl, Carolyn A Young, Uljana Hesse, Stefan G Amyotte, Kalina Andreeva, Patrick J Calie, Damien J Fleetwood, David C Haws, Neil Moore, Birgitt Oeser, Daniel G Panaccione, Kathryn K Schweri, Christine R Voisey, Mark L Farman, Jerzy W Jaromczyk, Bruce A Roe, Donal M O'Sullivan, Barry Scott, Paul Tudzynski, Zhiqiang An, Elissaveta G Arnaoudova, Charles T Bullock, Nikki D Charlton, Li Chen, Murray Cox, Randy D Dinkins, Simona Florea, Anthony E Glenn, Anna Gordon, Ulrich Güldener, Daniel R Harris, Walter Hollin, Jolanta Jaromczyk, Richard D Johnson, Anar K Khan, Eckhard Leistner, Adrian Leuchtmann, Chunjie Li, JinGe Liu, Jinze Liu, Miao Liu, Wade Mace, Caroline Machado, Padmaja Nagabhyru, Juan Pan, Jan Schmid, Koya Sugawara, Ulrike Steiner, Johanna E Takach, Eiji Tanaka, Jennifer S Webb, Ella V Wilson, Jennifer L Wiseman, Ruriko Yoshida, Zheng Zeng. Plant-symbiotic fungi as chemical engineers: multi-genome analysis of the clavicipitaceae reveals dynamics of alkaloid loci. PLoS Genet 2013 28;9(2):e1003323. Epub 2013 Feb 28.

John H Starnes, David W Thornbury, Olga S Novikova, Cathryn J Rehmeyer, Mark L Farman. Telomere-targeted retrotransposons in the rice blast fungus Magnaporthe oryzae: agents of telomere instability. Genetics 2012 Jun 23;191(2):389-406. Epub 2012 Mar 23.

Mark L Farman . Targeted cloning of fungal telomeres. Methods Mol Biol 2011 ;722:11-31.

Claire Rinehart, PhD

Western Kentucky University

Director, KBRIN Small Genome Discovery Program

Co-Director of BISC (Bioinformatics and Information Science Center)

Claire Rinehart, Ph.D. Biology


Email Claire Rinehart
Phone: 270-745-5997

Publications on orcidPublications on LinkedInPublications on Scopus

Dr. Rinehart's research interests include:

  • Bioinformatics
  • Application of genome analysis to discover genes that are differentially expressed and the metabolic and regulatory pathways to which they belong.
  • Genome sequencing and annotation.
  • Comparison of bacteriophage families to discover the functional design of their genomes.
  • In silico prediction of protein structure as an aid in discovering the protein's function.

Pope WH1, Anders KR, Baird M, Bowman CA, Boyle MM, Broussard GW, Chow T, Clase KL, Cooper S, Cornely KA, DeJong RJ, Delesalle VA, Deng L, Dunbar D, Edgington NP, Ferreira CM, Weston Hafer K, Hartzog GA, Hatherill JR, Hughes LE, Ipapo K, Krukonis GP, Meier CG, Monti DL, Olm MR, Page ST, Peebles CL, Rinehart CA, Rubin MR, Russell DA, Sanders ER, Schoer M, Shaffer CD, Wherley J, Vazquez E, Yuan H, Zhang D, Cresawn SG, Jacobs-Sera D, Hendrix RW, Hatfull GF. Cluster M mycobacteriophages Bongo, PegLeg, and Rey with unusually large repertoires of tRNA isotypes.J Virol. 2014 Mar;88(5):2461-80. doi: 10.1128/JVI.03363-13. Epub 2013 Dec 11.

Forbes-Stovall J1, Howton J1, Young M1, Davis G1, Chandler T1, Kessler B2, Rinehart CA1, Jacobshagen S3. Chlamydomonas reinhardtii strain CC-124 is highly sensitive to blue light in addition to green and red light in resetting its circadian clock, with the blue-light photoreceptor plant cryptochrome likely acting as negative modulator. Plant Physiol Biochem. 2014 Feb;75:14-23. doi: 10.1016/j.plaphy.2013.12.002. Epub 2013 Dec 12.

Van Rechem C1, Black JC, Abbas T, Allen A, Rinehart CA, Yuan GC, Dutta A, Whetstine JR. The SKP1-Cul1-F-box and leucine-rich repeat protein 4 (SCF-FbxL4) ubiquitin ligase regulates lysine demethylase 4A (KDM4A)/Jumonji domain-containing 2A (JMJD2A) protein. J Biol Chem. 2011 Sep 2;286(35):30462-70. doi: 10.1074/jbc.M111.273508. Epub 2011 Jul 8.

Black JC1, Allen A, Van Rechem C, Forbes E, Longworth M, Tschöp K, Rinehart C, Quiton J, Walsh R, Smallwood A, Dyson NJ, Whetstine JR. Conserved antagonism between JMJD2A/KDM4A and HP1γ during cell cycle progression. Mol Cell. 2010 Dec 10;40(5):736-48. doi: 10.1016/j.molcel.2010.11.008.

Gaskill C1, Forbes-Stovall J, Kessler B, Young M, Rinehart CA, Jacobshagen S. Improved automated monitoring and new analysis algorithm for circadian phototaxis rhythms in Chlamydomonas. Plant Physiol Biochem. 2010 Apr;48(4):239-46. doi: 10.1016/j.plaphy.2010.01.006. Epub 2010 Jan 21.

Pat Callie

Eastern Kentucky University

Coordinator - Master's Degree Program in Bioinformatics

Pat Calie, Ph.D. Biological Sciences


Email Pat Calie
Phone: 859-622-1543

Publications on google scholarPublications on ScopusResearchgate publicationsPub Med publications

Dr. Calie's current research efforts are in two areas: flowering plant and fungal phylogenetics, using either sets of individual genes or entire genomes, and fungal genomics. In the first venue he is focusing on the evolutionary history of the genera Rhyncospora (Cyperaceae) and Arisaema (Araceae), and the members of the family Sarraceniaceae, the pitcher plant family. For this effort r. Calie's collaborators and I are using both coding and non-coding regions of the nuclear, plastid, and mitochondrial genomes for informative data sets to facilitate the construction of testable hypothesis regarding current relationships and likely evolutionary histories. In the genomics efforts, he is collaborating with colleagues (Drs. Chris Schardl, Rudy Yoshida, and Jerzy Jaromcyk) at the University of Kentucky in determining the information (gene) content of select members of the fungal ascomycete family Clavicipitaceae. The efforts are now focused on the origin and evolution of genes that allow for the production of novel alkaloid compounds, on determining the origins of several hybrid fungal taxa, and on the development of appropriate statistical and computational tools to allow for the use of entire genome sequences as data sets for phylogenetic reconstruction.

Ellison, A.M., C.C. Davis, P.J. Calie, and R.F. C. Naczi. 2014. Pitcher plants (Sarracenia) provide a 21st-century perspective on interspecific and infraspecific ranks: a modest proposal for appropriate recognition and use. Systematic Botany in press.

Schardl, C.L., S. Florea, J. Pan, P. Nagabhyru, S. Bec, P.J. Calie. 2013. The epichloae: alkaloid diversity and roles in symbiosis with grasses. Current Opinions in Plant Biology 16: 480-488.

Christopher L. Schardl, Carolyn A. Young, Uljana Hesse, Stefan G. Amyotte, Kalina Andreeva , Patrick J. Calie , Damien J. Fleetwood , David C. Haws , Neil Moore, Birgitt Oeser , Daniel G. Panaccione , Kathryn K. Schweri, Christine R. Voisey, Mark L. Farman, Jerzy W. Jaromczyk, Bruce A. Roe, Donal M. O’Sullivan, Barry Scott, Paul Tudzynski, Zhiqiang An, Elissaveta G. Arnaoudova, Charles T. Bullock, Nikki D. Charlton, Li Chen, Murray Cox, Randy D. Dinkins, Simona Florea, Anthony E. Glenn, Anna Gordon, Ulrich Güldener, Daniel R. Harris, Walter Hollin, Jolanta Jaromczyk, Richard D. Johnson, Anar K. Khan, Eckhard Leistner, Adrian Leuchtmann, Chunjie Li, JinGe Liu, Jinze Liu, Miao Liu, Wade Mace, Caroline Machado, Padmaja Nagabhyru, Juan Pan, Jan Schmid, Koya Sugawara, Ulrike Steiner, Johanna E. Takach, Eiji Tanaka, Jennifer S. Webb, Ella V. Wilson, Jennifer Wiseman, Ruriko Yoshida, Zheng Zeng. 2013. Plant-symbiotic fungi as chemical engineers: Multi-genome analysis of the Clavicipitaceae reveals dynamics of alkaloid loci. PLoS Genetics 9: e1003323.

Ellison, A.M., Butler, E.B., Hicks, E.J., Naczi, R.F.C., Calie, P.J., Bell. C.D., and Davis, C.C. 2012. Phylogeny of the carnivorous plant family Sarraceniaceae.PLoS One 7: e39291.

Chumley, T.W., Palmer, J.D., Mower, J.P., Fourcade, H.M., Calie, P.J., Boore, J.L., and Jansen, R.K. 2006. The complete chloroplast genome sequence of Pelargonium x hortorum: Organization and evolution of the largest and most highly rearranged chloroplast genome of land plants. Molecular Biology and Evolution 23: 2175-2190.