Lingling An

Lingling An

Associate Professor, Agricultural-Biosystems Engineering
Associate Professor, Public Health
Associate Professor, Statistics-GIDP
Associate Professor, BIO5 Institute
Member of the General Faculty
Member of the Graduate Faculty
Primary Department
Department Affiliations
Contact
(520) 621-1248

Research Interest

Lingling An, PhD, conducts research in the interdisciplinary boundaries of many fields such as statistical sciences, biological and medical sciences, genomics and genetics. Her statistical group's major research interests include development and application of statistical and computational methods for analysis of high-dimensional genomic/genetic, metagenomic/ metatranscriptomic, and epigenomic data. The overlying vision is to develop rigorous, timely and useful statistical and computational methodologies to help biologists/geneticists to ask, answer, and disseminate biologically interesting information in the quest to understand the ultimate function of DNA and gene network.

Publications

Du, R., Sohn, M., & An, L. (2016). Normalization methods for sequence count data of microbial community and their impacts on differential abundance analysis. BMC Bioinformatics.
An, L. -., Pookhao, N., Jiang, H., & Xu, J. (2014). A Statistical approach for profiling functionality of a microbial community. PLoS ONE, 9(9): e106588.
McDowell, E., Kapteyn, J., Schmidt, A., Li, C., Kang, J., Descour, A., Shi, F., Larson, M., Schilmiller, A., An, L. -., Jones, A., Pichersky, E., Soderlund, C., & David, G. (2011). Comparative functional genomic analysis of Solanum glandular trichome types. Plant physiology, 155, 524-39.
Liu, S. S., Kim, H. T., Chen, J., & Lingling, A. n. (2010). Visualizing desirable patient healthcare experiences. Health Marketing Quarterly, 27(1), 116-130.

PMID: 20155554;Abstract:

High healthcare cost has drawn much attention and healthcare service providers (HSPs) are expected to deliver high-quality and consistent care. Therefore, an intimate understanding of the most desirable experience from a patient's and/or family's perspective as well as effective mapping and communication of such findings should facilitate HSPs' efforts in attaining sustainable competitive advantage in an increasingly discerning environment. This study describes (a) the critical quality attributes (CQAs) of the experience desired by patients and (b) the application of two visualization tools that are relatively new to the healthcare sector, namely the "spider-web diagram" and "promotion and detraction matrix." The visualization tools are tested with primary data collected from telephone surveys of 1,800 patients who had received care during calendar year 2005 at 6 of 61 hospitals within St. Louis, Missouri-based, Ascension Health. Five CQAs were found by factor analysis. The spider-web diagram illustrates that communication and empowerment and compassionate and respectful care are the most important CQAs, and accordingly, the promotion and detraction matrix shows those attributes that have the greatest effect for creating promoters, preventing detractors, and improving consumer's likelihood to recommend the healthcare provider. © Taylor & Francis Group, LLC.

An, L., & Doerge, R. (2012). Dynamic Clustering of Gene Expression. ISRN Bioinformaitcs.

Article ID 537217. Doi:10.5402/2012/53721