Realizing the New Reality: Machine Learning Curbing Antimicrobial Resistance in Cutibacterium acnes
| Autor: | Romasha Gupta, Gagan Dhawan, Bipul Kumar, Hemant K. Gautam |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Research Journal of Biotechnology. 17:165-170 |
| ISSN: | 2278-4535 0973-6263 |
| DOI: | 10.25303/1712rjbt1650170 |
| Popis: | Increase in antibiotic resistance is the current cause of global concern facing the human healthcare sector. Dermatologists, particularly face a major challenge, especially when treating acne due to the overprescription of antibiotics. In an era of tremendous technological advancement, the need for the development of bioinformatics tools and the availability of public databases is the new holy grail to combat antibiotic resistance. With the emergence of machine learning approaches, screening of drugresistant microbes and identification of known and novel resistant genes have been facilitated for the rapid development of drugs or techniques to combat the problem of resistance. The whole-genome sequences of Cutibacterium acnes are stored digitally in the PATRIC database for research purposes. With the amalgamation of machine learning algorithms along with the availability of genomic sequences, the prediction of antimicrobial resistance is becoming a reality. The swift and accurate prediction of antibiotic resistance using machine learning tools and algorithms would lower the increasing rate of antibiotic resistance encountered in Cutibacterium acnes and will help dermatologists to combat the problem of Acne vulgaris more efficiently. |
| Databáze: | OpenAIRE |
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