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PointCloudExplore 2: Visual exploration of 3D gene expression

Title: PointCloudExplore 2: Visual exploration of 3D gene expression
Authors: International Research Training Group Visualization of Large; Unstructured Data Sets; University of Kaiserslautern; Germany; Institute for Data Analysis; Visualization; University of California; Davis; CA; Computational Research Division; Lawrence Berkeley National Laboratory (LBNL); Berkeley; Genomics Division, LBNL; Computer Science Department; Irvine; Computer Science Division,University of California; Life Sciences Division, LBNL; Department of Molecular; Cellular Biology; the Center for Integrative Genomics; Ruebel, Oliver; Rubel, Oliver; Weber, Gunther H.; Huang, Min-Yu; Bethel, E. Wes; Keranen, Soile V.E.; Fowlkes, Charless C.; Hendriks, Cris L. Luengo; DePace, Angela H.; Simirenko, L.; Eisen, Michael B.; Biggin, Mark D.; Hagen, Hand; Malik, Jitendra; Knowles, David W.; Hamann, Bernd
Contributors: Lawrence Berkeley National Laboratory. Computational Research Division.; Lawrence Berkeley National Laboratory. Genomics Division.; Lawrence Berkeley National Laboratory. Life Sciences Division.
Publisher Information: Lawrence Berkeley National Laboratory
Publication Year: 2008
Collection: University of North Texas: UNT Digital Library
Subject Terms: Management; Drosophila; Genes; Transcription; Exploration; Architecture; Resolution
Time: 60; 99
Description: To better understand how developmental regulatory networks are defined inthe genome sequence, the Berkeley Drosophila Transcription Network Project (BDNTP)has developed a suite of methods to describe 3D gene expression data, i.e.,the output of the network at cellular resolution for multiple time points. To allow researchersto explore these novel data sets we have developed PointCloudXplore (PCX).In PCX we have linked physical and information visualization views via the concept ofbrushing (cell selection). For each view dedicated operations for performing selectionof cells are available. In PCX, all cell selections are stored in a central managementsystem. Cells selected in one view can in this way be highlighted in any view allowingfurther cell subset properties to be determined. Complex cell queries can be definedby combining different cell selections using logical operations such as AND, OR, andNOT. Here we are going to provide an overview of PointCloudXplore 2 (PCX2), thelatest publicly available version of PCX. PCX2 has shown to be an effective tool forvisual exploration of 3D gene expression data. We discuss (i) all views available inPCX2, (ii) different strategies to perform cell selection, (iii) the basic architecture ofPCX2., and (iv) illustrate the usefulness of PCX2 using selected examples.
Document Type: report
File Description: Text
Language: English
Relation: osti: 928314; https://digital.library.unt.edu/ark:/67531/metadc898032/; ark: ark:/67531/metadc898032
DOI: 10.2172/928314
Availability: https://doi.org/10.2172/928314; https://digital.library.unt.edu/ark:/67531/metadc898032/
Accession Number: edsbas.D14264C
Database: BASE