Promotor: Roeland M.H. Merks

Epithelial-mesenchymal plasticity (EMP) and tumor cell migration play an important role in cancer progression, and an improved understanding of the mechanisms underlying these concepts is essential for developing new targeted approaches.

There is a need for alternative methods to replace, reduce and refine (3R) animal experimentation. Combining experimental data from high-throughput in vitro studies with in silico modeling is a promising approach to unravel the effect of chemicals on living cells and to gain a better understanding of…

Promotor: Prof.dr. J.N. Kok

Drug-target binding kinetics determine the time course of the central event in pharmacotherapy: Drug-target interaction.

In this thesis it is posed that the central object of preference discovery is a co-creative process in which the Other can be represented by a machine. It explores efficient methods to enhance introverted intuition using extraverted intuition's communication lines.

Immunotherapies for cancer are an emerging class of therapeutic strategies which aim to treat cancer via augmentation of the immune system.

This dissertation focused on computational methods based on first principles calculations using the Density Functional Theory (DFT) framework. Emphasis was laid on affordable methods that can provide a tradeoff between computational expense and accuracy.

This thesis focuses on two processes involved in fighting infections: metabolism and immune cell motility and navigation.

This thesis investigates the contribution of quantum computers to machine learning, a field called Quantum Machine Learning. Quantum Machine Learning promises innovative perspectives and methods for solving complex problems in machine learning, leveraging the unique capabilities of quantum computers…

The zebrafish is a promising vertebrate model organism in early drug discovery and development.

Carbohydrates, or sugars, are the most diverse and most abundant biomolecules known. However, the isolation of carbohydrate samples in sufficient amounts and purity is often impractical or even impossible, so the chemical synthesis of glycosides becomes relevant. The glycosylation reaction, in which…

A complex community of microbes develops in the infant gut shortly after birth. We call this community the infant gut microbiota. The microbiota influences the health of the infant, which makes the composition and function of the infant gut microbiota an important topic to study.

This thesis describes the importance of being able to control the selectivity of potential drug candidates.

In the current global context, there is a pressing need to address sustainable energy supplies to safeguard our Planet and its ecosystems. The choices made by human society have a significant impact on genetic evolution and climate.

This thesis focuses on data found in the field of computational drug discovery. New insight can be obtained by applying machine learning in various ways and in a variety of domains. Two studies delved into the application of proteochemometrics (PCM), a machine learning technique that can be used to…

Assessing the risks of engineered nanomaterials (ENMs) solely on the basis of experimental assays is time-consuming, resource intensive, and constrained by ethical considerations (such as the principles of the 3Rs of animal testing). The adoption of computational toxicology in this field is a high p…

Optical projection tomography (OPT) is a tomographic 3D imaging technique used for specimens in the millimetre scale.

Cancer is considered the silent pandemic of the 21st century and the second leading cause of death worldwide.

Despite being the object of intense study, embryonic development has been difficult to model due to a number of reasons. First, complex tissues can be comprised of many cell types, of which we probably only know a subset.

LUMC Technology Focus Area (TFA) Data Analytics is een samenwerkingsverband van verschillende onderzoeksgroepen in het LUMC die nieuwe kwantitatieve en computationele methodologie ontwikkelen voor biomedisch en klinisch onderzoek.

Lezing

Sonja Boas ontwikkelde nieuwe technieken om het groeiproces van bloedvaten op computationele wijze te bestuderen. De resultaten van haar onderzoek geven een beter begrip van mechanismen in bloedvatgroei en dat is relevant voor de ontwikkeling van medische therapieën. Promotie op dinsdag 22 december…

We strive to address the challenge of constructing a modeling language to write software which can take advantage of recent hardware developments (multicore, cloud) without compromising in its abstraction levels.

Most of current public-key cryptography is considered insecure against attacks from sufficiently powerful quantum computers. Post-quantum cryptography studies methods to secure information resistant against such attacks. One proposal is isogeny-based cryptography, which bases its security on computational…

The long-held desire - to link structure directly to function and to explain molecular mechanisms based on basic chemical or physical principles - is finally coming closer, satisfying not only our scientific curiosity but also offering new solutions to the many challenges in the field of health, energy…

Lezing

Promotor: Prof.dr. R.M.H. Merks

To improve cancer treatments, personalized medicine approaches have aimed to identify exactly which mutations are driving tumor development in a given patient and specifically target these mutations using precision therapies.

In this thesis, we consider various (electro)chemical phenomena at surfaces and nanoparticles and their underlying atomistic processes, which we studied using first-principles methods such as density functional theory.

Real-life processes are characterized by dynamics involving time. Examples are walking, sleeping, disease progress in medical treatment, and events in a workflow.

Promotor: Prof.dr. J.N. Kok, Co-promotor: F.J. Verbeek

In 2016 hebben Universitaire Medische Centra (UMC's) van Nederland de zelfevaluatie-tool ontwikkeld gebaseerd op het PhD Competence Model. Onze partners van de Universiteit Utrecht stellen een digitale versie van de tool kosteloos beschikbaar voor onze promovendi binnen de Universiteit Leiden, ook voor…

Promotor: Prof.dr. E. Deprettere

Promotores: Prof.dr. P.C.W. Hogendoorn & Prof.dr. H.P. Spaink Co-promotor: Dr. B.E. Snaar-Jagalska

The aim of this thesis was to develop novel treatment strategies for different types of eye melanoma utilizing zebrafish models. We first establish orthotopic and ectopic xenograft models for uveal and conjunctival melanoma by engraftment of the immortalized cells derived from these tumors into zebrafish…

Promotie

In this work we describe three methods to improve the performance of Quantum Field Theory calculations.

Kunst en vrije tijd, Kunst en vrije tijd

Endothelial dysfunction and microvascular diseases are key drivers of cardiovascular disease, the world's leading cause of death.

Industrial manufacturing processes, such as the production of steel or the stamping of car body parts, are complex semi-batch processes with many process steps, machine parameters and quality indicators.

Clinical development of drugs for central nervous system (CNS) disorders has been particularly challenging and still suffers from high attrition rates.

Promotoren: Prof.dr. G.R. de Snoo en Dr. R. Heijungs

This dissertation studies the Asymptotics of Bayesian nonparametric inference for Gaussian linear models.

Death in all types of melanomas is generally caused by metastasis. Uveal melanoma (UM) is the most common intraocular melanoma, there are currently no (patient-derived) animal models that faithfully recapitulate metastatic dissemination of UM.

The molecular mechanisms that instigate a healthy cell to become malignant are fueled by (epi)genetic alterations in so-called driver genes.

In this thesis, we study systems of electrons in which strong correlations give rise to emergent exotic physics.

Promotor: Prof.dr. B. van de Water, Co-promotores: L.T.M. van der Ven, A.S. Kienhuis

This dissertation focuses on developing new mathematical and statistical methods to properly represent time-varying covariates and model them within the context of time-to-event analysis.