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2. Contributors

4. Food, nutrition, and autism: from soil to fork

6. Multi-objective Evolutionary Discretization of Gene Expression Profiles: Application to COVID-19 Severity Prediction

9. Nutritional Interventions to Prevent the Development of Atopic Diseases: A Focus on Cow’s Milk Allergy

13. Modelling Asthma Patients’ Responsiveness to Treatment Using Feature Selection and Evolutionary Computation

16. Report of a Meeting: Food, Nutrition, and Autism: From Soil to Fork

18. Methodology for biomarker discovery with reproducibility in microbiome data using machine learning

19. A robust microbiome signature for autism spectrum disorder across different studies using machine learning

26. A robust mRNA signature obtained via recursive ensemble feature selection predicts the responsiveness of omalizumab in moderate‐to‐severe asthma

34. Oropharyngeal Microbiota Clusters in Children with Asthma/Wheeze Associate with Allergy, Blood Transcriptomic Immune Pathways and Exacerbations Risk

37. Increased exploration and hyperlocomotion in a cigarette smoke and LPS induced murine model of COPD

41. Medication use in uncontrolled pediatric asthma: Results from the SysPharmPediA study

45. Classifying asthma control using salivary and fecal bacterial microbiome in children with moderate-to-severe asthma

46. The interaction between intestinal bacterial metabolites and phosphatase and tensin homolog in autism spectrum disorder

47. The relationship between immune fitness and saliva biomarkers of systemic inflammation

48. A robust mRNA signature obtained via recursive ensemble feature selection predicts the responsiveness of omalizumab in moderate-to-severe asthma

49. An Innovative AI-based primer design tool for precise and accurate detection of SARS-CoV-2 variants of concern

50. A multiscale hybrid model for exploring the effect of Resolvin D1 on macrophage polarization during acute inflammation

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