James A. Foster

Affiliations: 
University of Idaho, Moscow, ID, United States 
Area:
Computer Science
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"James Foster"
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Publications

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Banzhaf W, Baumgaertner B, Beslon G, et al. (2016) Defining and simulating open-ended novelty: requirements, guidelines, and challenges. Theory in Biosciences = Theorie in Den Biowissenschaften
Foster JA, Gerton GL. (2016) The Acrosomal Matrix. Advances in Anatomy, Embryology, and Cell Biology. 220: 15-33
Beck D, Foster JA. (2015) Machine learning classifiers provide insight into the relationship between microbial communities and bacterial vaginosis. Biodata Mining. 8: 23
Sam Ma Z, Guan Q, Ye C, et al. (2015) Network analysis suggests a potentially 'evil' alliance of opportunistic pathogens inhibited by a cooperative network in human milk bacterial communities. Scientific Reports. 5: 8275
Zhbannikov IY, Foster JA. (2015) MetAmp: combining amplicon data from multiple markers for OTU analysis. Bioinformatics (Oxford, England). 31: 1830-2
Beck D, Dennis C, Foster JA. (2015) Seed: a user-friendly tool for exploring and visualizing microbial community data. Bioinformatics (Oxford, England). 31: 602-3
Beck D, Foster JA. (2015) Machine learning classifiers provide insight into the relationship between microbial communities and bacterial vaginosis Biodata Mining. 8: 1-9
Baker YS, Agrawal R, Foster JA, et al. (2014) Detecting Bacterial Vaginosis Using Machine Learning. Proceedings of the 2014 Acm Southeast Regional Conference / Association For Computing Machinery-Digital Library. 2014
Baker YS, Agrawal R, Foster JA, et al. (2014) APPLYING MACHINE LEARNING TECHNIQUES IN DETECTING BACTERIAL VAGINOSIS. Proceedings / International Conference On Machine Learning and Cybernetics. International Conference On Machine Learning and Cybernetics. 2014: 241-246
Beck D, Foster JA. (2014) Machine learning techniques accurately classify microbial communities by bacterial vaginosis characteristics. Plos One. 9: e87830
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