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Using Growing Self-Organising Maps to Improve the Binning Process in Environmental Whole-Genome Shotgun Sequencing
Joint Authors
Chan, Chon-Kit Kenneth
Hsu, Arthur L.
Tang, Sen-Lin
Halgamuge, Saman K.
Source
Issue
Vol. 2008, Issue 2008 (31 Dec. 2008), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2007-11-21
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Metagenomic projects using whole-genome shotgun (WGS) sequencing produces many unassembled DNA sequences and small contigs.
The step of clustering these sequences, based on biological and molecular features, is called binning.
A reported strategy for binning that combines oligonucleotide frequency and self-organising maps (SOM) shows high potential.
We improve this strategy by identifying suitable training features, implementing a better clustering algorithm, and defining quantitative measures for assessing results.
We investigated the suitability of each of di-, tri-, tetra-, and pentanucleotide frequencies.
The results show that dinucleotide frequency is not a sufficiently strong signature for binning 10 kb long DNA sequences, compared to the other three.
Furthermore, we observed that increased order of oligonucleotide frequency may deteriorate the assignment result in some cases, which indicates the possible existence of optimal species-specific oligonucleotide frequency.
We replaced SOM with growing self-organising map (GSOM) where comparable results are obtained while gaining 7%–15% speed improvement.
American Psychological Association (APA)
Chan, Chon-Kit Kenneth& Hsu, Arthur L.& Tang, Sen-Lin& Halgamuge, Saman K.. 2007. Using Growing Self-Organising Maps to Improve the Binning Process in Environmental Whole-Genome Shotgun Sequencing. BioMed Research International،Vol. 2008, no. 2008, pp.1-10.
https://search.emarefa.net/detail/BIM-987773
Modern Language Association (MLA)
Chan, Chon-Kit Kenneth…[et al.]. Using Growing Self-Organising Maps to Improve the Binning Process in Environmental Whole-Genome Shotgun Sequencing. BioMed Research International No. 2008 (2008), pp.1-10.
https://search.emarefa.net/detail/BIM-987773
American Medical Association (AMA)
Chan, Chon-Kit Kenneth& Hsu, Arthur L.& Tang, Sen-Lin& Halgamuge, Saman K.. Using Growing Self-Organising Maps to Improve the Binning Process in Environmental Whole-Genome Shotgun Sequencing. BioMed Research International. 2007. Vol. 2008, no. 2008, pp.1-10.
https://search.emarefa.net/detail/BIM-987773
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-987773