TurbOmics, a free web platform from CNIC and EMBL, integrates metabolomics with proteomics and transcriptomics data, no coding needed.
The simulation of diet-host-microbiome-disease relationships is made possible by genome-scale modeling of microbiome metabolism. However, the extent of available genome-scale reconstruction resources is constrained by computational difficulties. To create a database of 247,092 microbial genome-scale metabolic reconstructions encompassing 19 phyla and including more than 60% of uncharacterized strains, the analysis methodology known as APOLLO was…
A groundbreaking study conducted by researchers at the UK Biobank has unveiled a novel approach to understanding aging through metabolomics and machine learning. This study is among fascinating projects that involve the application of biology and technology to improve health. It presents a scenario where the application of metabolomics allows for the accurate prediction of…
Integrating metabolomics with other omics and providing insights into the biology of disease requires bioinformatics competence. Integration is difficult with present approaches, though, as they frequently call for programming knowledge. Unidentified metabolites are difficult for current methods to handle, and they leave out a sizable amount of data from untargeted metabolomics studies. Here, researchers from…
Burn injuries often incite substantial morbidity and lethality aftermath. Severe burn injuries due to hot liquids or solids and fire induce pathophysiological and inflammatory responses, metabolic alterations, and distributive shock in distant deeper organs that can extensively persist up to several years after the initial burn insult and are extremely unmanageable, leading towards multi-organ damage….
Scientists from Prague have developed MZmine3, a scalable platform for the analysis of mass spectrometry (MS) data from different instrumental setups. The platform supports hybrid datasets from various setups such as liquid and gas chromatography (LC and GC)-MS, ion mobility spectrometry (IMS)-MS, and MS imaging. Spatial metabolomics analyses with increased annotation confidence is now feasible…
Scientists from Aalto University and the University of Luxembourg have developed a machine learning model that can accurately identify small molecules. The model has the potential to be used in various fields, including medicine, drug discovery, and environmental chemistry. The model was trained using data from numerous laboratories and is now considered one of the…
Contrasting sharply with the little knowledge of the microbial world’s underlying structure is the rising awareness of its significance and variety. Despite recent developments in DNA sequencing, the establishment of general conclusions regarding microbial life on Earth is hampered by the absence of standardized techniques and shared analytical frameworks. Researchers at the University of California San…
A toolshed for synthetic biology, metabolic engineering, and industrial biotechnology is available through the Galaxy-SynBioCAD portal. Using the tools and workflows available on the portal, one can create libraries of strains that produce the desired chemical targets, spanning a comprehensive metabolic pathway design and engineering process from selecting strains and targets, designing DNA parts to…
How much of our body chemistry is related to what we eat can be determined through untargeted metabolomics by comparing blood or stool samples to a reference database of foods. A team of international scientists, led by investigators at the University of California San Diego, introduced untargeted metabolomics – a new method to determine the…
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