Computational Approaches to Deciphering the Molecular and Cellular Heterogeneity of Alzheimer's Disease

G.A. Bouland

doi:10.4233/uuid:871ba6f5-63bc-4423-a44b-53a03af7ddec

Computational Approaches to Deciphering the Molecular and Cellular Heterogeneity of Alzheimer's Disease

G.A. Bouland

Pattern Recognition and Bioinformatics

Research output: Thesis › Dissertation (TU Delft)

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Abstract

In summary, the contributions within this thesis advance Alzheimer's research by introducing new computational tools and methods to better understand the genetics of the disease and cellular mechanisms. Additionally, showing that single-cell gene expression can be effectively analyzed in a binary format (expressed or not) simplifies genomic data analysis, making it more accessible, efficient, and applicable to a range of diseases and conditions.

Original language	English
Awarding Institution	Delft University of Technology
Supervisors/Advisors	Reinders, M.J.T., Promotor Mahfouz, A.M.E.T.A., Copromotor
Award date	10 Mar 2025
Print ISBNs	978-94-93431-10-2
DOIs	https://doi.org/10.4233/uuid:871ba6f5-63bc-4423-a44b-53a03af7ddec
Publication status	Published - 2025

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Digital version PhD thesis Gerard BoulandFinal published version, 13.3 MB

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AB - In summary, the contributions within this thesis advance Alzheimer's research by introducing new computational tools and methods to better understand the genetics of the disease and cellular mechanisms. Additionally, showing that single-cell gene expression can be effectively analyzed in a binary format (expressed or not) simplifies genomic data analysis, making it more accessible, efficient, and applicable to a range of diseases and conditions.

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Computational Approaches to Deciphering the Molecular and Cellular Heterogeneity of Alzheimer's Disease

Abstract

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