Predicting bacterial functional traits from whole genome sequences using random forest

Wei Zhang; Scott J Emrich; Joshua Livermore; Dan Liu; Erliang Zeng; Stuart E Jones

doi:10.1109/ICCABS.2013.6629212

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Conference proceeding

Predicting bacterial functional traits from whole genome sequences using random forest

Wei Zhang, Scott J Emrich, Joshua Livermore, Dan Liu, Erliang Zeng and Stuart E Jones

2013 IEEE 3rd International Conference on Computational Advances in Bio and medical Sciences (ICCABS), pp.1-2

06/2013

DOI: 10.1109/ICCABS.2013.6629212

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Abstract

Microbes are the most abundant and diverse biota on earth. Despite their small size, they have a huge impact in many essential ecosystem services and overall global health. However, due to the complexity of microbial communities and the fact that most of the members cannot be cultured, the molecular and ecological details as well as influencing factors of these processes are still poorly understood [1]. An important question in ecological biology is how biodiversity influences ecosystem functioning [2]. In general, it is thought that biodiversity maximizes potential either through greater chances of containing highly successful individuals and/or poorly understood processes that benefit communities [3]-[5]. Underlying this is the relationship between the presence of individual organism and specific functional traits.

Bioinformatics

Genomics

Earth

Biological system modeling

Details

Title: Subtitle: Predicting bacterial functional traits from whole genome sequences using random forest
Creators: Wei Zhang - Dept. of Comput. Sci. & Eng., Univ. of Notre Dame, South Bend, IN, USA
Scott J Emrich - Dept. of Comput. Sci. & Eng., Univ. of Notre Dame, South Bend, IN, USA
Joshua Livermore - Dept. of Biol. Sci., Univ. of Notre Dame, South Bend, IN, USA
Dan Liu - Dept. of Biol. Sci., Univ. of Notre Dame, South Bend, IN, USA
Erliang Zeng - University of Iowa, Dental Research
Stuart E Jones - Dept. of Biol. Sci., Univ. of Notre Dame, South Bend, IN, USA
Resource Type: Conference proceeding
Publication Details: 2013 IEEE 3rd International Conference on Computational Advances in Bio and medical Sciences (ICCABS), pp.1-2
DOI: 10.1109/ICCABS.2013.6629212
Publisher: IEEE
Language: English
Date published: 06/2013
Academic Unit: Preventive and Community Dentistry; Roy J. Carver Department of Biomedical Engineering; Iowa Neuroscience Institute; Biostatistics; Dental Research
Record Identifier: 9984071900302771

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