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Increasing power by sharing information from genetic background and treatment in clustering of gene expression time series
Joint Authors
Heath, Paul R.
Rahman, Muhammad Arifur
al-Araji, Nabil H.
Lawrence, Neil D.
al-Rashid, Sura Zaki Naji
Source
Journal of Babylon University : Journal of Applied and Pure Sciences
Issue
Vol. 26, Issue 4 (30 Apr. 2018), pp.253-267, 15 p.
Publisher
Publication Date
2018-04-30
Country of Publication
Iraq
No. of Pages
15
Main Subjects
Abstract EN
Clustering of gene expression time series gives insight into which genes may be co-regulated, allowing us to discern the activity of pathways in a given microarray experiment.
Of particular interest is how a given group of genes varies with different conditions or genetic background.
This paper develops a new clustering method that allows each cluster to be parameterised according to whether the behaviour of the genes across conditions is correlated or anti-correlated.
By specifying correlation between such genes,more information is gain within the cluster about how the genes interrelate.
Amyotrophic lateral sclerosis (ALS) is an irreversible neurodegenerative disorder that kills the motor neurons and results in death within 2 to 3 years from the symptom onset.
Speed of progression for different patients are heterogeneous with significant variability.
The SOD1G93A transgenic mice from different backgrounds (129Sv and C57) showed consistent phenotypic differences for disease progression.
A hierarchy of Gaussian isused processes to model condition-specific and gene-specific temporal co-variances.
This study demonstrated about finding some significant gene expression profiles and clusters of associated or co-regulated gene expressions together from four groups of data (SOD1G93A and Ntg from 129Sv and C57 backgrounds).
Our study shows the effectiveness of sharing information between replicates and different model conditions when modelling gene expression time series.
Further gene enrichment score analysis and ontology pathway analysis of some specified clusters for a particular group may lead toward identifying features underlying the differential speed of disease progression.
American Psychological Association (APA)
al-Rashid, Sura Zaki Naji& Rahman, Muhammad Arifur& al-Araji, Nabil H.& Lawrence, Neil D.& Heath, Paul R.. 2018. Increasing power by sharing information from genetic background and treatment in clustering of gene expression time series. Journal of Babylon University : Journal of Applied and Pure Sciences،Vol. 26, no. 4, pp.253-267.
https://search.emarefa.net/detail/BIM-1233522
Modern Language Association (MLA)
al-Rashid, Sura Zaki Naji…[et al.]. Increasing power by sharing information from genetic background and treatment in clustering of gene expression time series. Journal of Babylon University : Journal of Applied and Pure Sciences Vol. 26, no. 4 (2018), pp.253-267.
https://search.emarefa.net/detail/BIM-1233522
American Medical Association (AMA)
al-Rashid, Sura Zaki Naji& Rahman, Muhammad Arifur& al-Araji, Nabil H.& Lawrence, Neil D.& Heath, Paul R.. Increasing power by sharing information from genetic background and treatment in clustering of gene expression time series. Journal of Babylon University : Journal of Applied and Pure Sciences. 2018. Vol. 26, no. 4, pp.253-267.
https://search.emarefa.net/detail/BIM-1233522
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 265-267
Record ID
BIM-1233522