Conference proceeding
Mapping genomic features to functional traits through microbial whole genome sequences
International Journal of Bioinformatics Research and Applications, Vol.10(4-5), pp.461-478
2nd IEEE International Conference on Computational Advances in Bio and Medical Sciences (ICCABS)
01/01/2014
DOI: 10.1504/IJBRA.2014.062995
PMID: 24989863
Abstract
Recently, the utility of trait-based approaches for microbial communities has been identified. Increasing availability of whole genome sequences provide the opportunity to explore the genetic foundations of a variety of functional traits. We proposed a machine learning framework to quantitatively link the genomic features with functional traits. Genes from bacteria genomes belonging to different functional traits were grouped to Cluster of Orthologs (COGs), and were used as features. Then, TF-IDF technique from the text mining domain was applied to transform the data to accommodate the abundance and importance of each COG. After TF-IDF processing, COGs were ranked using feature selection methods to identify their relevance to the functional trait of interest. Extensive experimental results demonstrated that functional trait related genes can be detected using our method. Further, the method has the potential to provide novel biological insights.
Details
- Title: Subtitle
- Mapping genomic features to functional traits through microbial whole genome sequences
- Creators
- Wei Zhang - Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USAErliang Zeng - Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46556, USADan Liu - Department of Biological Science, University of Notre Dame, Notre Dame, IN 46556, USAStuart E Jones - Department of Biological Science, University of Notre Dame, Notre Dame, IN 46556, USAScott Emrich - Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46556, USA
- Resource Type
- Conference proceeding
- Publication Details
- International Journal of Bioinformatics Research and Applications, Vol.10(4-5), pp.461-478
- Conference
- 2nd IEEE International Conference on Computational Advances in Bio and Medical Sciences (ICCABS)
- DOI
- 10.1504/IJBRA.2014.062995
- PMID
- 24989863
- NLM abbreviation
- Int J Bioinform Res Appl
- ISSN
- 1744-5485
- eISSN
- 1744-5493
- Publisher
- Inderscience Publishers Ltd
- Language
- English
- Date published
- 01/01/2014
- Academic Unit
- Preventive and Community Dentistry; Roy J. Carver Department of Biomedical Engineering; Iowa Neuroscience Institute; Biostatistics; Dental Research
- Record Identifier
- 9984065370302771
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