A comprehensive overview of microbiome data in the light of machine learning applications: categorization, accessibility, and future directions

Frontiers in Microbiology, Journal Year: 2024, Volume and Issue: 15

Published: Feb. 13, 2024

Metagenomics, Metabolomics, and Metaproteomics have significantly advanced our knowledge of microbial communities by providing culture-independent insights into their composition functional potential. However, a critical challenge in this field is the lack standard comprehensive metadata associated with raw data, hindering ability to perform robust data stratifications consider confounding factors. In review, we categorize publicly available microbiome five types: shotgun sequencing, amplicon metatranscriptomic, metabolomic, metaproteomic data. We explore importance for reuse address challenges collecting standardized metadata. also, assess limitations collection existing public repositories metagenomic This review emphasizes vital role interpreting comparing datasets highlights need protocols fully leverage data's Furthermore, future directions implementation Machine Learning (ML) retrieval, offering promising avenues deeper understanding ecological roles. Leveraging these tools will enhance capabilities dynamics diverse ecosystems. Finally, emphasize crucial ML models development.

Language: Английский

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The emerging role of the gut microbiota and its application in inflammatory bowel disease

Biomedicine & Pharmacotherapy, Journal Year: 2024, Volume and Issue: 179, P. 117302 - 117302

Published: Aug. 19, 2024

Inflammatory bowel disease (IBD), including Crohn's and ulcerative colitis, is a complex disorder with an unknown cause. However, the dysbiosis of gut microbiome has been found to play role in IBD etiology, exacerbated immune responses defective intestinal barrier integrity. The can also be potential biomarker for several diseases, IBD. Currently, conventional treatments targeting pro-inflammatory cytokines pathways IBD-associated do not yield effective results. Other therapies that directly target dysbiotic outcomes are emerging. We review health its as diagnostic, prognostic, therapeutic This explores emerging advancements microbiome-associated alterations IBD, such nanoparticle or encapsulation delivery, fecal microbiota transplantation, nutritional therapies, microbiome/probiotic engineering, phage therapy, mesenchymal stem cells (MSCs), proteins, herbal formulas.

Language: Английский

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A Machine-Learning Approach to Finding Gene Target Treatment Options for Long COVID

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 13, 2025

Abstract Long COVID, also known as post-acute sequelae of SARS-CoV-2 infection (PASC), encompasses a range symptoms persisting for weeks or months after the acute phase COVID-19. These symptoms, affecting multiple organ systems, significantly impact quality life. This study employs machine-learning approach to identify gene targets treating COVID. Using datasets GSE275334, GSE270045, and GSE157103, Recursive Ensemble Feature Selection (REFS) was applied key genes associated with The highlights therapeutic potential targeting such PPP2CB, SOCS3, ARG1, IL6R, ECHS1. Clinical trials pharmacological interventions, including dual antiplatelet therapy anticoagulants, are explored their efficacy in managing COVID-19-related complications. findings suggest that machine learning can effectively biomarkers targets, offering promising avenue personalized treatment strategies COVID patients.

Language: Английский

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Contributions of Artificial Intelligence to Analysis of Gut Microbiota in Autism Spectrum Disorder: A Systematic Review

Children, Journal Year: 2024, Volume and Issue: 11(8), P. 931 - 931

Published: July 31, 2024

Background: Autism spectrum disorder (ASD) is a highly heterogeneous neurodevelopmental whose etiology not known today, but everything indicates that it multifactorial. For example, genetic and epigenetic factors seem to be involved in the of ASD. In recent years, there has been an increase studies on implications gut microbiota (GM) behavior children with ASD given dysbiosis GM may trigger onset, development progression through microbiota–gut–brain axis. At same time, significant progress occurred artificial intelligence (AI). Methods: The aim present study was perform systematic review articles using AI analyze individuals line PRISMA model, 12 were selected. Results: Outcomes reveal majority relevant this topic have conducted China (33.3%) Italy (25%), followed by Netherlands (16.6%), Mexico (16.6%) South Korea (8.3%). Conclusions: bacteria Bifidobacterium most biomarker regard Although provides very promising approach data analysis, caution needed avoid over-interpretation preliminary findings. A first step must taken representative general population samples order obtain standard according age, sex country. Thus, more work required bridge gap between mental health research clinical care

Language: Английский

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Understanding Parkinson's: The microbiome and machine learning approach

Maturitas, Journal Year: 2024, Volume and Issue: 193, P. 108185 - 108185

Published: Dec. 23, 2024

Language: Английский

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Machine-Learning Analysis of mRNA: An Application to Inflammatory Bowel Disease

Published: July 8, 2024

Language: Английский

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