ANDREWS, Simon and MCLEOD, K. (2018). A visual analytics technique for exploring gene expression in the developing mouse embryo. In: 23rd International Conference on Conceptual Structures, proceedings. Lecture Notes in Artificial Intelligence . Springer, 137-151.
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Abstract
This paper describes a novel visual analytics technique for exploring gene co-expression is the developing mouse embryo. The majority of existing techniques either visualise a single gene profile or a single tissue profile, whereas the technique presented here combines both - visualising gene co-expression in a group of tissues, for example, in the components of the developing heart. The technique is presented using data provided by the Edinburgh Mouse Atlas Project of gene expression assays conducted on tissues of the developing mouse embryo and a corresponding hierarchical graph of tissues defining the mouse anatomy. By specifying a particular tissue, such as the heart, and a particular stage of development, a Formal Concept Lattice is constructed making use of the hierarchical mouse anatomy to visualise the components of the specified tissue and the genes expressed in each component. Examples of lattices are given to illustrate the technique and show how it can provide useful information to genetic researchers of embryo development and tissue differentiation, particularly when comparing gene expression across several stages of development.
Item Type: | Book Section |
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Additional Information: | Lecture Notes in Artificial Intelligence (ISSN: 0302-9743) is a subseries of Lecture Notes in Computer Science (ISSN: 0302-9743). Paper presented at 23rd International Conference on Conceptual Structures, June 20th-22nd 2018, Edinburgh, Scotland. |
Research Institute, Centre or Group - Does NOT include content added after October 2018: | Cultural Communication and Computing Research Institute > Communication and Computing Research Centre |
Page Range: | 137-151 |
Depositing User: | Jill Hazard |
Date Deposited: | 10 May 2018 10:30 |
Last Modified: | 18 Mar 2021 01:30 |
URI: | https://shura.shu.ac.uk/id/eprint/21103 |
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