Back to search

Article

A neural network-based framework to understand the Type 2 Diabetes (T2D)-related alteration of the human gut microbiome

2020-09-08

Abstract excerpt

<h4>ABSTRACT</h4> To identify the microbial markers from the complex human gut microbiome for delineating the disease-related microbial alteration is of great interest. Here, we develop a framework combining neural network (NN) and random forest (RF), resulting in 40 marker species and 90 marker genes identified from the metagenomic dataset D1 (185 healthy and 183 type 2 diabetes (T2D) samples), respectively. Usi...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
40d1f283-7ff0-5c6a-8727-d6d95ccdcdfc
DOI
10.1101/2020.09.06.284885
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
A neural network-based framework to understand the Type 2 Diabetes (T2D)-related alteration of the human gut microbiomeDOI 10.1101/2020.09.06.284885
Predicting the role of the human gut microbiome in type 1 diabetes using machine-learning methodsSemantic proximity
Gut Microbiome-Based Diagnostic Model to Predict Diabetes MellitusSemantic proximity
Discovering Potential Taxonomic Biomarkers of Type 2 Diabetes From Human Gut Microbiota via Different Feature Selection MethodsSemantic proximity
Insights of Host Physiological Parameters and Gut Microbiome of Indian Type 2 Diabetic Patients Visualized via Metagenomics and Machine Learning ApproachesSemantic proximity
A network perspective on the ecology of gut microbiota and progression of Type 2 Diabetes: linkages to keystone taxa in a Mexican cohortSemantic proximity
Machine learning reveals time-varying microbial predictors with complex effects on glucose regulationSemantic proximity
mNFE: Microbiome network flow entropy for detecting pre-disease states of type 1 diabetesSemantic proximity
Understanding Patterns of the Gut Microbiome May Contribute to an Early Detection and Prevention of Type 2 Diabetes MellitusSemantic proximity
A core microbiome signature as an indicator of healthSemantic proximity
Gut Bacterial Characteristics of Patients With Type 2 Diabetes Mellitus and the Application PotentialSemantic proximity
Type 2 Diabetes Biomarkers of Human Gut Microbiota Selected via Iterative Sure Independent Screening MethodSemantic proximity
Systems Biology of Human Microbiome for the Prediction of Personal Glycaemic ResponseSemantic proximity
Select a neighboring publication to make it the new centre.