Author

Miranda T. Schram

Maastricht University Medical CentreORCID 0000-0001-8113-7604Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Neuroscience· 2 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:human· 3 Approach:statistical model· 3 Research Focus:benchmarking· 2 Research Focus:differential expression· 2 Approach:Bayesian inference· 1 Research Focus:gene regulatory network inference· 1 Assay:GWAS summary statistics· 1 Assay:imaging· 1

Frequent Co-Authors

David E.J. LindeniD· 3 shared Coen D.A. StehouweriD· 2 shared Jacobus F.A. JanseniD· 2 shared Jennifer Monereo SáncheziD· 2 shared Joost J.A. de JongiD· 2 shared Walter H. BackesiD· 2 shared Alexey A. ShadriniD· 1 shared Dennis van der MeeriD· 1 shared

Activity by Year

2019-2021 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 31 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

3 shared papersNeuroscience

David E.J. LindenORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Genetic & Genomic MedicineFrontiers in NeurosciencePeer-reviewedJul 5, 2021

Genetic overlap between Alzheimer's disease and depression mapped onto the brain

Jennifer Monereo Sánchez, Miranda T. Schram, Oleksandr Frei…·Dennis van der Meer

This study identifies genetic overlap between Alzheimer's disease and depression using GWAS data and biostatistical tools, finding shared variants and brain morphology associations.

29 citations

humanGWAS summary statistics

𝕏 PostBluesky

NeuroscienceNeuroImagePeer-reviewedMay 15, 2021

Quality control strategies for brain MRI segmentation and parcellation: practical approaches and recommendations - insights from The Maastricht Study

Jennifer Monereo Sánchez, Joost J.A. de Jong, Gerhard S. Drenthen…·Jacobus F.A. Jansen

This study compares manual and automated quality control strategies for brain MRI segmentation, finding that Euler numbers and MRIQC provide reliable and efficient methods to reduce measurement error.

95 citationstop 3%

humanimaging

𝕏 PostBluesky

NeurosciencebioRxivPreprintOct 16, 2019

The Effect of MR Image Quality on Structural and Functional Brain Connectivity: The Maastricht Study

Joost J.A. de Jong, Jacobus F.A. Jansen, Laura W. M. Vergoossen…·Walter H. Backes

The paper examines how MRI image quality affects brain connectivity measures and finds that low quality metrics like SNR and motion reduce connectivity, impacting associations with age, sex, and BMI.

3 citations

humanmultiome

𝕏 PostBluesky