Cloud Computing: An Analysis on Round Robin Technique

Saxena, Shubhra; Saxena, Khushboo; Goyal, Jayanti; Saxena, Akash

doi:10.2139/ssrn.3166544

Cited by 2 publications

(1 citation statement)

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“…The commensal skin microbiome influences the physical characteristics of the epidermis layer and regulates the development of immune system, and a dysbiosis of this community is associated with several skin diseases such as acne, atopic dermatitis, and psoriatic lesions (Byrd et al, 2018;Grice et al, 2009;Naik et al, 2012;Picardo and Ottaviani, 2014;SanMiguel and Grice, 2015;Zeeuwen et al, 2013;Saxena, 2018). In addition to being crucial for the host health, the skin microbiome also possesses a large and diverse reservoir of metabolic enzymes that play a key role in metabolizing numerous biomolecules naturally produced by either host skin cells or other commensal microorganisms.…”

Section: Introductionmentioning

confidence: 99%

SkinBug: an artificial intelligence approach to predict human skin microbiome-mediated metabolism of biotics and xenobiotics

et al. 2021

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Summary In addition to being pivotal for the host health, the skin microbiome possesses a large reservoir of metabolic enzymes, which can metabolize molecules (cosmetics, medicines, pollutants, etc.) that form a major part of the skin exposome. Therefore, to predict the complete metabolism of any molecule by skin microbiome, a curated database of metabolic enzymes (1,094,153), reactions, and substrates from ∼900 bacterial species from 19 different skin sites were used to develop “SkinBug.” It integrates machine learning, neural networks, and chemoinformatics methods, and displays a multiclass multilabel accuracy of up to 82.4% and binary accuracy of up to 90.0%. SkinBug predicts all possible metabolic reactions and associated enzymes, reaction centers, skin microbiome species harboring the enzyme, and the respective skin sites. Thus, SkinBug will be an indispensable tool to predict xenobiotic/biotic metabolism by skin microbiome and will find applications in exposome and microbiome studies, dermatology, and skin cancer research.

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