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Open Access

Peer-reviewed

Research Article

PG-Metrics: A chemometric-based approach for classifying bacterial peptidoglycan data sets and uncovering their subjacent chemical variability

Keshav Kumar,

Roles Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing

Affiliation Laboratory for Molecular Infection Medicine Sweden, Department of Molecular Biology, Umeå Centre for Microbial Research, Umeå University, Umeå, Sweden
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Akbar Espaillat,

Roles Conceptualization, Formal analysis, Supervision, Writing – original draft, Writing – review & editing

Affiliation Laboratory for Molecular Infection Medicine Sweden, Department of Molecular Biology, Umeå Centre for Microbial Research, Umeå University, Umeå, Sweden
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Felipe Cava

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing

* E-mail: felipe.cava@molbiol.umu.se

Affiliation Laboratory for Molecular Infection Medicine Sweden, Department of Molecular Biology, Umeå Centre for Microbial Research, Umeå University, Umeå, Sweden
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PG-Metrics: A chemometric-based approach for classifying bacterial peptidoglycan data sets and uncovering their subjacent chemical variability

Keshav Kumar,
Akbar Espaillat,
Felipe Cava

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Published: October 17, 2017
https://doi.org/10.1371/journal.pone.0186197

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Principal component analysis
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Chromatographic techniques
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Cell walls
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Peptidoglycans
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Algorithms
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Computational pipelines
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Plant cell walls
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Simulation and modeling
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