Author

Zuné Jansen van Rensburg

UCL Queen Square Institute of NeurologyORCID 0000-0002-4219-5139Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Genetics· 1

Signature Assays, Organisms & Methods

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Assay:proteomics· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Organism:C. elegans· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1 Organism:Drosophila· 1 Approach:experimental assay· 1

Frequent Co-Authors

Carla LouwiD· 2 shared Nina TruteriD· 2 shared Radouane Oudrhiri· 2 shared Raminderpal Singh· 2 shared Alastair John NoyceiD· 1 shared Alejandro Martínez-CarrascoiD· 1 shared Alina Jama· 1 shared Amica Corda Müller-NedebockiD· 1 shared

Activity by Year

2022-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersBioinformatics

Carla LouwORCID

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3 papers

Recent·Most cited

Geneticsnpj Parkinson s DiseasePeer-reviewedMar 4, 2023

The IPDGC/GP2 Hackathon - an open science event for training in data science, genomics, and collaboration using Parkinson's disease data

Hampton L. Leonard, Ruqaya Murtadha, Alejandro Martínez-Carrasco…·Alastair John Noyce

The paper describes a virtual hackathon event that brought together early career scientists to develop tools for Parkinson's disease research using open science principles.

7 citations

experimental assaysoftware / tool

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BioinformaticsbioRxivPreprintOct 31, 2022

ALaSCA: a computational platform for quantifying the effect of proteins using Pearlian causal inference, with an example application in Alzheimer's disease

Nina Truter, Zuné Jansen van Rensburg, Radouane Oudrhiri…·Carla Louw

This paper introduces ALaSCA, a platform using Pearlian causal inference to identify molecular drivers of neuronal aging, with an application in Alzheimer's disease.

DOI 10.1101/2022.10.31.514546

Drosophilaproteomics

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BioinformaticsbioRxivPreprintJun 24, 2022

Supervised machine learning with feature selection for prioritization of targets related to time-based cellular dysfunction in aging

Nina Truter, Zuné Jansen van Rensburg, Radouane Oudrhiri…·Carla Louw

The paper uses supervised machine learning with feature selection to prioritize aging-related genes in C. elegans, identifying known and novel genes associated with cellular dysfunction markers.

3 citations

C. elegansproteomics

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