Antony A. Cooper

Transcriptome-Wide Alternative Splicing Analysis Implicates Complex Events in Bipolar Disorder

This study performs a transcriptome-wide alternative splicing analysis in bipolar disorder, identifying complex splicing events and candidate genes associated with the disorder.

FAMILY-BASED RNA SEQUENCING IN BIPOLAR DISORDER FOR CANDIDATE GENE AND PATHWAY IDENTIFICATION

This study uses RNA sequencing in multiplex bipolar disorder families to identify differentially expressed genes and pathways, finding significant lncRNAs and ion homeostasis dysregulation.

Deep sequencing of proteotoxicity modifier genes uncovers a Presenilin-2/beta-amyloid-actin genetic risk module shared among alpha-synucleinopathies

The paper identifies a shared genetic risk module involving PSEN2 and actin regulation across alpha-synucleinopathies, linking them to Alzheimer's disease mechanisms.

Single molecule fingerprinting reveals different amplification properties of α-synuclein oligomers and preformed fibrils in seeding assay.

The paper uses single molecule spectroscopy to compare the seeding properties of α-synuclein oligomers and preformed fibrils in amplification assays, finding that fibrils dominate the response despite lower quantities.

Establishing gene regulatory networks from Parkinson's disease risk loci

This study identifies gene regulatory networks influenced by Parkinson's disease risk SNPs using eQTL and chromosomal conformation data across multiple tissues.

Machine learning identifies six genetic variants and alterations in the Heart Atrial Appendage as key contributors to PD risk predictivity.

The paper uses machine learning to identify six genetic variants and tissue-specific eQTL effects linked to Parkinson's disease risk.

A transcription regulatory network within the ACE2 locus may promote a pro-viral environment for SARS-CoV-2 by modulating expression of host factors.

The paper identifies regulatory elements within the ACE2 locus that control host gene expression, suggesting they may contribute to a pro-viral environment for SARS-CoV-2.

blkbox: Integration Of Multiple Machine Learning Approaches To Identify Disease Biomarkers

blkbox integrates nine machine learning algorithms to identify disease biomarkers by selecting the best classifier for a dataset, offering feature selection and visualization without parameter optimization.