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MetabolomicsMachine Learning-Based Retention Time Prediction of Trimethylsilyl Derivatives of Metabolites
In gas chromatography-mass spectrometry-based untargeted metabolomics, metabolites are identified by comparing mass spectra and chromatographic retention time with reference databases or standard materials. In that sense, machine learning has been used to predict the retention time of metabolites la...
2022-05-26 | MTBLS2841 | MetaboLights
MetabolomicsPrediction of complex phenotypes using the Drosophila melanogaster metabolome
Understanding the genotype-phenotype map and how variation at different levels of biological organization is associated are central topics in modern biology. Fast developments in sequencing technologies and other molecular omic tools enable researchers to obtain detailed information on variation at ...
2021-08-05 | MTBLS2060 | MetaboLights
MetabolomicsMetabolome-based prediction of yield heterosis contributes to the breeding of elite rice
The improvement of breeding efficiencies for heterotic and climate-resilient crops can mitigate the food shortage crisis from overpopulation and climate change. Thus far, diverse molecular markers have been utilized for guiding field phenotypic selections, while the accurate predictions of complex h...
2019-12-10 | MTBLS742 | MetaboLights
MetabolomicsStructure of gut microbiota and characteristics of fecal metabolites in people living with HIV

Objective: The gut microbiome plays a pivotal role in human immunodeficiency virus (HIV) infection. However, the associated alterations in the gut microbiome-host interaction remain unclear. This study aims to investigate the gut microbiota and fecal metabolites in people living with HIV (PLWH).<...

2024-09-16 | MTBLS9264 | MetaboLights
ProteomicsBlind testing cross-linking/mass spectrometry under the auspices of the 11th critical assessment of methods of protein structure prediction (CASP11)
We report the first blind test on the readiness of combining high-density cross-linking/mass spectrometry data in conjunction with ab initio structure prediction, through the help of Critical Assessment of protein Structure Prediction (CASP). This blind test was coordinated by the CASP organizers ...
ORGANISM(S): Homo sapiens (Human) Ruminococcus gnavus Bacteroides caccae Staphylococcus aureus 
2016-12-02 | PXD003643 | Pride
Casp Protein structure prediction Cross-linking/mass spectrometry 
ProteomicsAlphaLink: bringing protein structure prediction in situ with in-cell photo-crosslinking mass spectrometry, crosslinking mass spectrometry, XL-MS,
The protein structure prediction problem has been revolutionised by AlphaFold2, an algorithm that uses neural networks and evolutionary information to predict accurate models from the primary sequence. However, some proteins remain difficult to predict. Moreover, proteins are dynamic entities that e...
ORGANISM(S): Escherichia Coli 
2023-02-22 | PXD036833 | JPOST Repository
MetabolomicsIntegration of magnetic resonance imaging and protein and metabolite CSF measurements to enable early diagnosis of secondary progressive multiple sclerosis

Molecular networks in neurological diseases are complex. Despite this fact, contemporary biomarkers are in most cases interpreted in isolation, leading to a significant loss of information and power. We present an analytical approach to scrutinize and combine information from biomarkers originati...

2018-08-13 | MTBLS558 | MetaboLights
UnknownSmall angle X-ray scattering-assisted protein structure prediction in CASP13 and emergence of solution structure differences.
Not available
S-EPMC6851496 | biostudies-literature
MetabolomicsA machine learning model for the prediction and verification of the protective intestinal microbiota-derived L-valine in sepsis

The intestinal microflora and metabolites produced by these microbes serve as important regulators of the development of sepsis. Accordingly, this study was designed to systematically explore the relationships between the regulation of septicemia and both the intestinal flora and fecal metabolite...

2023-07-28 | MTBLS7866 | MetaboLights
UnknownProtein structure validation by generalized linear model root-mean-square deviation prediction.
Not available
S-EPMC3324767 | biostudies-literature
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