Heath, Lenwood S.Ramakrishnan, NarenSederoff, Ronald R.Whetten, Ross W.Chevone, Boris I.Struble, Craig A.Jouenne, Vincent Y.Chen, Daweivan Zyl, LeonelGrene, Ruth2017-09-182017-09-182002-01-01Lenwood S. Heath, Naren Ramakrishnan, Ronald R. Sederoff, et al., “Studying the Functional Genomics of Stress Responses in Loblolly Pine With the Expresso Microarray Experiment Management System,” Comparative and Functional Genomics, vol. 3, no. 3, pp. 226-243, 2002. doi:10.1002/cfg.169http://hdl.handle.net/10919/79101Conception, design, and implementation of cDNA microarray experiments present avariety of bioinformatics challenges for biologists and computational scientists. The multiplestages of data acquisition and analysis have motivated the design of Expresso, asystem for microarray experiment management. Salient aspects of Expresso includesupport for clone replication and randomized placement; automatic gridding, extraction ofexpression data from each spot, and quality monitoring; flexible methods of combiningdata from individual spots into information about clones and functional categories; and theuse of inductive logic programming for higher-level data analysis and mining. Thedevelopment of Expresso is occurring in parallel with several generations of microarrayexperiments aimed at elucidating genomic responses to drought stress in loblolly pineseedlings. The current experimental design incorporates 384 pine cDNAs replicated andrandomly placed in two specific microarray layouts. We describe the design of Expresso aswell as results of analysis with Expresso that suggest the importance of molecularchaperones and membrane transport proteins in mechanisms conferring successfuladaptation to long-term drought stress.application/pdfenCreative Commons Attribution 4.0 InternationalStudying the Functional Genomics of Stress Responses in Loblolly Pine With the Expresso Microarray Experiment Management SystemArticle - Refereed2017-09-18Copyright © 2002 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Comparative and Functional Genomicshttps://doi.org/10.1002/cfg.169