An assessment of the complexity of 3' UTRs relative to that of protein-coding sequences: a comparison of the three models selected for each pairwise alignment of 3 UTRs
Viewed:
2003
The dataset comes from a study which assessed the complexity of 3′ UTRs (three prime untranslated regions) relative to that of protein-coding sequences, by comparing the extent to which segmental substructures can be detected within these two genomic fractions based on sequence composition and conservation.
The data provides results from a comparison of the three models for each pairwise alignment of 3′ UTRs. The data shows that MP: mixture proportions; T/T: Transition/Transversion ratio. Class 11 of Dme vs Dsi (MP: 0.7%, Conservation: 56%, GC content: 17% and T/T: 0.5) and the class 9 of Dme vs Dya (MP: 7.5%, Conservation: 85%, GC content: 45% and T/T: 1.1) alignments did not match with other models.
Geographical area of data collection
kmlPolyCoords
159.255525,-9.219822 112.921454,-9.219822 112.921454,-54.777218 159.255525,-54.777218 159.255525,-9.219822
Publications
Algama, Manjula, Oldmeadow, Christopher, Tasker, Edward, Mengersen, Kerrie, & Keith, Jonathan M. (2014) Drosophila 3′ UTRs are more complex than protein-coding sequences. PLoS ONE, 9(5), e97336.
http://dx.doi.org/10.1371/journal.pone.0097336
Research areas
Genome complexity
Markov models
Genome analysis
Probability theory
Molecular biology
Molecular biology techniques
Genomics
Bayes theorem
MATHEMATICAL
SCIENCES
Comparative genomics
Biostatistics
Genome evolution
Sequencing techniques
Computational biology
Sequence analysis
Biological
sciences
Cite this collection
Algama, Manjula; Oldmeadow, Christopher; Tasker, Edward; Mengersen, Kerrie; Keith, Jonathan M. (2014): Model comparisons. Table_3.xls. PLOS ONE.
Algama,Manjula; Oldmeadow,Christopher; Tasker,Edward; Mengersen,Kerrie; Keith,Jonathan. (2014): An assessment of the complexity of 3' UTRs relative to that of protein-coding sequences: a comparison of the three models selected for each pairwise alignment of 3 UTRs. [Queensland University of Technology]. https://doi.org/10.4225/09/58573f380cf7d
Related information
This work was supported by the Australian Research Council, the National Health and Medical Research Council and by a Vice Chancellor’s Research Fellowship funded by Queensland University of Technology.
http://goo.gl/C7eHbJ
Edward Tasker, Research collaborator
http://goo.gl/ftN7eC
Manjula Algama, Research collaborator
http://goo.gl/ftN7eC
Jonathan M. Keith, Research collaborator
http://goo.gl/ftN7eC
Christopher Oldmeadow, Research collaborator
http://goo.gl/ftN7eC
Access the data
Data file types
.xls
Licence
Copyright
© 2014 Algama et al.
Dates of data collection
From 2013-01-01 to 2013-12-31
Connections
Was collected by
Contacts
Name: Distinguished Professor Kerrie Mengersen
Email: k.mengersen@qut.edu.au
Phone: +61 7 3138 2063
Fax: +61 7 3138 2063
Other
Date record created:
2014-06-30T11:30:59
Date record modified:
2019-08-01T12:04:51
Record status:
Published - Open Access