Data

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
Algama, Manjula ; Oldmeadow, Christopher ; Tasker, Edward ; Mengersen, Kerrie ; Keith, Jonathan
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.4225/09/58573f380cf7d&rft.title=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&rft.identifier=10.4225/09/58573f380cf7d&rft.publisher=Queensland University of Technology&rft.description=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. &rft.creator=Algama, Manjula &rft.creator=Oldmeadow, Christopher &rft.creator=Tasker, Edward &rft.creator=Mengersen, Kerrie &rft.creator=Keith, Jonathan &rft.date=2014&rft.edition=1&rft.coverage=159.255525,-9.219822 112.921454,-9.219822 112.921454,-54.777218 159.255525,-54.777218 159.255525,-9.219822&rft_rights=© 2014 Algama et al.&rft_rights=Creative Commons Attribution 3.0 http://creativecommons.org/licenses/by/3.0/au/&rft_subject=MATHEMATICAL SCIENCES&rft_subject=Molecular biology &rft_subject=Sequencing techniques &rft_subject=Genome analysis &rft_subject=Molecular biology techniques &rft_subject=Genomics&rft_subject=Genome complexity &rft_subject=Computational biology &rft_subject=Bayes theorem &rft_subject=BIOLOGICAL SCIENCES&rft_subject=Comparative genomics &rft_subject=Sequence analysis &rft_subject=Genome evolution &rft_subject=Probability theory &rft_subject=Biostatistics &rft_subject=Markov models &rft.type=dataset&rft.language=English Access the data
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Creative Commons Attribution 3.0
http://creativecommons.org/licenses/by/3.0/au/

© 2014 Algama et al.

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Contact Information

Postal Address:
Professor Kerrie Mengersen

k.mengersen@qut.edu.au

Full description

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.

Data time period: 2013 to 31 12 2013

This dataset is part of a larger collection

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  • Associated with Drosophila 3′ UTRs Are More Complex than Protein-Coding Sequences
    10.1371/JOURNAL.PONE.0097336
  • Associated with Edward Tasker, Research collaborator
    goo.gl/ftN7eC
  • Associated with 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.
    goo.gl/C7eHbJ

159.25553,-9.21982 112.92145,-9.21982 112.92145,-54.77722 159.25553,-54.77722 159.25553,-9.21982

136.0884895,-31.99852

Subjects
Biological Sciences | Bayes theorem | Biostatistics | Comparative genomics | Computational biology | Genome analysis | Genome complexity | Genome evolution | Genomics | Mathematical Sciences | Markov models | Molecular biology | Molecular biology techniques | Probability theory | Sequence analysis | Sequencing techniques |

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