Algorithms and tools for data-driven omics integration to achieve multilayer biological insights: a narrative review DOI Creative Commons
Aurelia Morabito, Giulia De Simone, Roberta Pastorelli

et al.

Journal of Translational Medicine, Journal Year: 2025, Volume and Issue: 23(1)

Published: April 10, 2025

Systems biology is a holistic approach to biological sciences that combines experimental and computational strategies, aimed at integrating information from different scales of processes unravel pathophysiological mechanisms behaviours. In this scenario, high-throughput technologies have been playing major role in providing huge amounts omics data, whose integration would offer unprecedented possibilities gaining insights on diseases identifying potential biomarkers. the present review, we focus strategies applied literature integrate genomics, transcriptomics, proteomics, metabolomics year range 2018-2024. Integration approaches were divided into three main categories: statistical-based approaches, multivariate methods, machine learning/artificial intelligence techniques. Among them, statistical (mainly based correlation) ones with slightly higher prevalence, followed by learning Integrating multiple layers has shown great uncovering molecular mechanisms, putative biomarkers, aid classification, most time resulting better performances when compared single analyses. However, significant challenges remain. The nature platforms introduces issues such as variable data quality, missing values, collinearity, dimensionality. These further increase combining datasets, complexity heterogeneity integration. We report found cope these challenges, but some open still remain should be addressed disclose full

Language: Английский

Beating Cardiac Cell Cultures From Different Developmental Stages of Rainbow Trout as a Novel Approach for Replication of Cardiac Fish Viruses DOI Creative Commons

Torben Krebs,

Julia Bauer,

Sarah Graff

et al.

Journal of Fish Diseases, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 17, 2025

ABSTRACT Piscine orthoreovirus‐1 and 3 (PRV‐1, PRV‐3) cause highly prevalent infection in cultured salmonids can induce heart skeletal muscle inflammation (HSMI) resulting economic losses aquaculture. However, to date, PRV‐1 PRV‐3 have withstood replication continuous cell lines. In this study, we used beating cultures obtained from different developmental stages of rainbow trout ( Oncorhynchus mykiss ) (RTC‐L RTC‐A) tested their ability sustain PRV‐3. Furthermore, compared the pattern viruses with those newly developed fibroblast line (RTH‐F) traditional established gonad (RTG‐2). Neither RTCs nor RTH‐F lines supported Comparative experiments showed varying susceptibility novel viral haemorrhagic septicaemia virus (VHSV), chum salmon reovirus (CSV), infectious pancreatic necrosis (IPNV), piscine myocarditis (PMCV), salmonid alphavirus (SAV‐3) tilapia lake (TiLV), indicating usability for work multiple fish viruses. While confirming difficulty replicating PRV‐3, results demonstrate potential heart‐derived as vitro tools studying

Language: Английский

Citations

0
Algorithms and tools for data-driven omics integration to achieve multilayer biological insights: a narrative review DOI Creative Commons
Aurelia Morabito, Giulia De Simone, Roberta Pastorelli

et al.

Journal of Translational Medicine, Journal Year: 2025, Volume and Issue: 23(1)

Published: April 10, 2025

Systems biology is a holistic approach to biological sciences that combines experimental and computational strategies, aimed at integrating information from different scales of processes unravel pathophysiological mechanisms behaviours. In this scenario, high-throughput technologies have been playing major role in providing huge amounts omics data, whose integration would offer unprecedented possibilities gaining insights on diseases identifying potential biomarkers. the present review, we focus strategies applied literature integrate genomics, transcriptomics, proteomics, metabolomics year range 2018-2024. Integration approaches were divided into three main categories: statistical-based approaches, multivariate methods, machine learning/artificial intelligence techniques. Among them, statistical (mainly based correlation) ones with slightly higher prevalence, followed by learning Integrating multiple layers has shown great uncovering molecular mechanisms, putative biomarkers, aid classification, most time resulting better performances when compared single analyses. However, significant challenges remain. The nature platforms introduces issues such as variable data quality, missing values, collinearity, dimensionality. These further increase combining datasets, complexity heterogeneity integration. We report found cope these challenges, but some open still remain should be addressed disclose full

Language: Английский

Citations

0