Author

Carla Louw

ORCID 0000-0002-9293-9933Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:proteomics· 3 Research Focus:gene regulatory network inference· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Organism:C. elegans· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1 Organism:Drosophila· 1

Frequent Co-Authors

Nina TruteriD· 3 shared Radouane Oudrhiri· 3 shared Raminderpal Singh· 3 shared Ben LoosiD· 2 shared Zuné Jansen van RensburgiD· 2 shared David D. van NiekerkiD· 1 shared Dawie van Niekerk· 1 shared Martine van den Heever· 1 shared

Activity by Year

2022-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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3 shared papersBioinformatics

Nina TruterORCID

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3 papers

Recent·Most cited

ALaSCA: A novel in silico simulation platform to untangle biological pathway mechanisms, with a case study in Type 1 Diabetes progression

Carla Louw, Nina Truter, Wikus Bergh, Martine van den Heever, Shade Horn, Radouane Oudrhiri, Dawie van Niekerk, Ben Loos, Raminderpal Singh

This paper introduces ALaSCA, a causal analysis platform, and applies it to study antioxidant protein effects on Type 1 Diabetes progression using proteomic data.

bioRxiv · Mar 16, 2023 · PreprintBioinformatics

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, David D. van Niekerk, Ben Loos, Raminderpal Singh, 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.

bioRxiv · Oct 31, 2022 · PreprintBioinformatics

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, Raminderpal Singh, 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.

bioRxiv · Jun 24, 2022 · PreprintBioinformatics