Y Lu, Z Pang, J Xia - Briefings in Bioinformatics, 2023 - academic.oup.com
Background: Global or untargeted metabolomics is widely used to comprehensively investigate metabolic profiles under various pathophysiological conditions such as …
Covering: up to the end of 2020 Recently introduced computational metabolome mining tools have started to positively impact the chemical and biological interpretation of …
C Wieder, C Frainay, N Poupin… - PLoS computational …, 2021 - journals.plos.org
Over-representation analysis (ORA) is one of the commonest pathway analysis approaches used for the functional interpretation of metabolomics datasets. Despite the widespread use …
Covering: up to 2021 Plants and their associated microbial communities are known to produce millions of metabolites, a majority of which are still not characterized and are …
Covering: up to 2022 With the emergence of large amounts of omics data, computational approaches for the identification of plant natural product biosynthetic pathways and their …
The computational metabolomics field brings together computer scientists, bioinformaticians, chemists, clinicians, and biologists to maximize the impact of metabolomics across a wide …
Background Single sample pathway analysis (ssPA) transforms molecular level omics data to the pathway level, enabling the discovery of patient-specific pathway signatures …
J Cortada-Garcia, R Daly, SA Arnold, K Burgess - Scientific Reports, 2023 - nature.com
Metabolomics is a powerful tool for the identification of genetic targets for bioprocess optimisation. However, in most cases, only the biosynthetic pathway directed to product …
V Pascal Andreu, HE Augustijn, K van den Berg… - Msystems, 2021 - Am Soc Microbiol
Microbial gene clusters encoding the biosynthesis of primary and secondary metabolites play key roles in shaping microbial ecosystems and driving microbiome-associated …