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MetabolomicsLandscape of gut microbiota and metabolites and their interaction in comorbid heart failure and depressive symptoms: a random forest analysis study

Depression is an individual risk factor for poor prognosis in patients with heart failure (HF). Recent studies show that gut microbiota and metabolites have critical role in comorbid HF and depressive symptoms. We recruited 95 subjects including 35 HF patients with depressive symptoms (HF-DS), 36...

2023-10-23 | MTBLS8183 | MetaboLights
ProteomicsPredicting the Protein Corona on Nanoparticles Using Random Forest Models with Nanoparticle, Protein, and Experimental Features
We describe the predicted composition and abundance of the protein corona as a function of protein, nanoparticle, and experimental features that serve as the input dataset in which our Random Forest Regression (RFR) and Random Forest Classifier (RFC) models were trained on. Predictions were made usi...
ORGANISM(S): Bos taurus (Bovine) 
2025-08-04 | PXD053700 | Pride
Random forest classifier Random forest regression Fetal bovine serum Nanoparticles Machine learning Protein corona Lc-ms/ms 
ModelsHuiyiLi2024 - Prediction of death risk in patients with acute diquat poisoning using Random Forest Model
The objective of this study was to develop and validate predictive models to assess the risk of death in patients with acute diquat (DQ) poisoning using innovative machine learning techniques. The study analyzed data from 201 consecutive patients admitted for deliberate oral intake of DQ between Feb...
2024-07-18 | MODEL2407180001 | BioModels
ProteomicsLinking soil microbial community traits to the soil storage potential of dissolved organic carbon from surface plant litter
Using Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) on microcosm samples from early phase plant litter degradation, we found that proteins and condensed hydrocarbons are the compounds with the strongest correlation to dissolved organic carbon (DOC) concentration. Proteins co...
ORGANISM(S): Environmental Samples <bacteria> (ncbitaxon:48479) 
MSV000088109 | MassIVE
TranscriptomicsTranscription profiling of acute lymphoblastic leukaemia patient samples that represent six different subgroups defined by cytogenetic features and immunophenotype
We examined published microarray data from 104 acute lymphoblastic leukaemia patient specimens, that represent six different subgroups defined by cytogenetic features and immunophenotypes. Using the decision-tree based supervised learning algorithm Random Forest (RF), we determined a small set of ge...
ORGANISM(S): Homo sapiens 
2007-05-11 | E-TABM-125 | biostudies-arrayexpress
TranscriptomicsTranscription profiling of human whole blood from rheumatoid arthritis patients
The whole blood was collected pre-treatment from rheumatoid arthritis patients starting the anti_TNF therapy. All patients were naïve to anti_TNFs. The disease activity was measured using the DAS28 score at the pre-treatment visit1 (DAS28_v1) and 14 weeks after treatment visit3 (DAS28_v3). The resp...
ORGANISM(S): Homo sapiens 
2009-09-18 | E-GEOD-15258 | biostudies-arrayexpress
ProteomicsMulti-omics analysis reveals the sensitivity of immunotherapy for unresectable non-small cell lung cancer
Peripheral blood plasma was collected from unresectable stage III and IV non-small cell lung cancer patients who were negative for driver mutations before receiving immunotherapy. Then we classified samples according to the follow-up results after two courses of immunotherapy and non-targeted metabo...
ORGANISM(S): Homo Sapiens 
2024-12-18 | PXD058967 |
GenomicsA Random-Forest Based Algorithm for Prediction of Enhancers From Histone Modifications
Transcriptional enhancers play critical roles in regulation of gene expression, but their identification has remained a challenge. Recently, it was shown that enhancers in the mammalian genome are associated with characteristic histone modification patterns, which have been increasingly exploited f...
ORGANISM(S): Homo sapiens 
2012-05-09 | E-GEOD-37858 | biostudies-arrayexpress
MetabolomicsPrediction and evaluation of the effect of pre-centrifugation sample management on the measurable untargeted LC-MS plasma metabolome

Optimal handling is the most important means to ensure adequate sample quality. We aimed to investigate whether pre-centrifugation delay time and temperature could be accurately predicted and to what extent variability induced by pre-centrifugation management can be adjusted for. We used untarget...

2021-10-13 | MTBLS2259 | MetaboLights
GenomicsBase-resolution methylation patterns accurately predict transcription factor bindings in vivo
Detecting in vivo transcription factor (TF) binding is important for understanding gene regulatory circuitries. ChIP-seq is a powerful technique to empirically define TF binding in vivo. However, the multitude of distinct TFs makes genome-wide profiling for them all labor-intensive and costly. Algor...
ORGANISM(S): Mus musculus 
2015-03-02 | E-GEOD-65093 | biostudies-arrayexpress
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