Article

A Hybrid Machine Learning And Network Analysis Approach Reveals Two Parkinson's Disease Subtypes From 115 RNA-Seq Post-mortem Brain Samples

2022-01-24

Abstract excerpt

Precision medicine emphasizes fine-grained diagnostics, taking individual variability into account to enhance treatment effectiveness. Parkinson's Disease (PD) heterogeneity among individuals is a proof that disease subtypes exist, and assigning individuals to subgroups is necessary for a better understanding of disease mechanisms and designing precise treatment approaches. The purpose of this study was to identif...

Topics

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

Identifiers and source

Literature Corpus work: d7cd0a47-2474-5d20-af28-01d8dd4acdb1
DOI: 10.20944/preprints202201.0348.v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

A Hybrid Machine Learning And Network Analysis Approach Reveals Two Parkinson's Disease Subtypes From 115 RNA-Seq Post-mortem Brain SamplesDOI 10.20944/preprints202201.0348.v1Read

Identification of Parkinson’s disease PACE subtypes and repurposing treatments through integrative analyses of multimodal dataSemantic proximity Read

Transcriptomics profiling of Parkinson’s disease progression subtypes reveals distinctive patterns of gene expressionSemantic proximity Read

Identification of Parkinson PACE subtypes and repurposing treatments through integrative analyses of multimodal clinical progression, neuroimaging, genetic, and transcriptomic dataSemantic proximity Read

Integrative Transcriptomic and Machine Learning Analysis Reveals a Robust Gene Signature in Parkinson’s DiseaseSemantic proximity Read

Integrated Analysis of Single-Cell RNA Sequencing and Transcriptome Data Identifies a Pyroptosis-Associated Diagnostic Model for Parkinson’s DiseaseSemantic proximity Read

Deciphering shared molecular dysregulation across Parkinson’s Disease variants using a multi-modal network-based data integration and analysisSemantic proximity Read

Deciphering shared molecular dysregulation across Parkinson’s disease variants using a multi-modal network-based data integration and analysisSemantic proximity Read

Constructing Parkinson's disease progression- endotype molecular networks for drug repurposing: multi-omics evidence aggregation and large-scale real-world data validationSemantic proximity Read

Identification of PLOD3 and LRRN3 as potential biomarkers for Parkinson’s disease based on integrative analysisSemantic proximity Read

A Machine Learning Approach to Parkinson’s Disease Blood TranscriptomicsSemantic proximity Read

Multi-Modality Machine Learning Predicting Parkinson’s DiseaseSemantic proximity Read