The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve healthcare practices in the era of precision medicine. However, several challenges must be addressed to exploit the benefits of ML in this field fully. In particular, there is a need to establish "gold standard" protocols for conducting ML analysis experiments and improve interactions between microbiome researchers and ML experts. The Machine Learning Techniques in Human Microbiome Studies (ML4Microbiome) COST Action CA18131 is a European network established in 2019 to promote collaboration between discovery-oriented microbiome researchers and data-driven ML experts to optimize and standardize ML approaches for microbiome analysis. This perspective paper presents the key achievements of ML4Microbiome, which include identifying predictive and discriminatory 'omics' features, improving repeatability and comparability, developing automation procedures, and defining priority areas for the novel development of ML methods targeting the microbiome. The insights gained from ML4Microbiome will help to maximize the potential of ML in microbiome research and pave the way for new and improved healthcare practices.
- Publikační typ
- časopisecké články MeSH
The entire double-stranded DNA genome of the Streptomyces aureofaciens phage mu1/6 was sequenced and analyzed. Its size is 38.194 kbp with an overall molar G+C content of 71.2 %. Fifty-two potential open reading frames (orfs) were identified, divided into two oppositely transcribed regions. In the left arm of the mu1/6 genome, an identified putative integrase and possible regulation proteins were identified. The rightwards transcribed region contains genes organized into apparently four functional units responsible for: (i) replication, (ii) DNA packaging and head assembly, (iii) tail morphogenesis, and (iv) lysis. Putative functions were assigned to twelve orfs based on bioinformatic analysis or experimental substantiation. Comparative analysis with three complete genomes of streptomycete phages revealed resemblance with respect to the organization of their genes into functional modules. Closer relationship was observed only between mu1/6 and S. venezuelae phage VWB.
- MeSH
- bakteriofágy genetika imunologie MeSH
- finanční podpora výzkumu jako téma MeSH
- genomová knihovna MeSH
- komponenty genomu genetika MeSH
- lyzogenie genetika MeSH
- otevřené čtecí rámce genetika MeSH
- Siphoviridae genetika izolace a purifikace MeSH
- Streptomyces aureofaciens genetika izolace a purifikace MeSH
- tetracyklin farmakologie izolace a purifikace MeSH
