Department of Bioinformatics – BiGCaT

PhD Projects


Current PhD projects

Integrative systems biology analysis of immune cell mRNA and miRNA expression by vitamin D

(Joint PhD-project between Maastricht University and Birmingham University)
PhD student: Amadeo Muñoz García, MSc
Supervising team: Prof. Dr. Chris Evelo (UM), Prof. Dr. Martin Hewison (BU) and Dr. Susan Steinbusch-Coort (UM)
Start date: October 2016
Description: Defining immune cell-specific mRNA and miRNA responses to vitamin D. To date studies of the immunomodulatory effects of vitamin D have focused primarily on responses to 1,25D in vitro using cultures of cell lines or purified homogeneous immune cells. However, whilst 1,25D is the active form of vitamin D there is no clear indication that this metabolite correlates with other vitamin D metabolites. In particular, 1,25D cannot be assumed to be a surrogate marker of 25D, the form of  vitamin D that is most commonly measured in human subjects. Almost all association studies and vitamin D supplementation trials are focused on variations in serum 25D concentrations. Thus, the first objective of studies will be using varying concentrations of 25D to represent vitamin D-deficiency (50 nM), -sufficiency (50-75 nM) and supra-sufficiency (>75 nM) – the latter representing levels of 25D targeted in some vitamin D supplementation studies. The second objective will be to use a mixed population of peripheral blood mononuclear cells (PBMC) as an in vitro model.  Finally, to determine the importance of immune stimulus in promoting vitamin D metabolism and responsiveness PBMC cultures will be treated with 25D/1,25D in the presence or absence of an immunogen. 


Visualization and integration of genetic variants data in pathway-based analysis

PhD student: Elisa Cirillo, MSc
Supervising team: Prof. Dr. Chris Evelo and Dr. Susan Steinbusch-Coort
Start date:
Description: My doctoral thesis research is based on the analysis of genetic variations and integration of biological knowledge of differing types, such as transcriptomic data and biological pathways, in order to discern more clearly the functional aspects of genetic association data. I am writing articles that will report on pathway and network methodologies that support secondary analysis of data from Genome Wide Association Studies (GWAS) of Type 2 Diabetes and BMI. I also take care of the data visualization aspect, that can facilitate the analysis. I compare the usability of tools that can display genetic variations in the context of biological pathways.


Direction information from pathway diagrams

PhD student: Ryan Miller, MSc
Supervising team: Prof. Dr. Chris Evelo and Dr. Egon Willighagen
Start date: January 2015
Description: Ryan is a PhD student at the Department of Bioinformatics (BiGCaT). He works as a developer for both Open PHACTS and WikiPathways. His main research is using semantic information about pathway diagrams to capture interaction information and directions. Information about pathway directions allows the ability to move about within the diagram.


Personalized risk profiles for cardiovascular disease: sub-typing obesity

PhD student: Mirella Kalafati, MSc
Supervising team: Prof. Dr. Chris Evelo and Prof. Dr. Ilja C.W. Arts and Dr. Michiel Adriaens
Start date: September 2015
Description: Mirella is a PhD student at the Department of Bioinformatics (BiGCaT) and the Maastricht Centre for Systems Biology (MaCSBio), working on the project of “Personalized risk profiles for cardiovascular disease: sub-typing obesity”. As part of the MUMC+ 2020 portfolio program “Healthy Living”, the Department of Bioinformatics, Epidemiology, Human Biology, Internal Medicine, and Systems Biology are collaborating to better understand the biological heterogeneity of obesity, to improve and personalize cardiometabolic risk classification of obese individuals and provide novel targets for prevention, early diagnosis and treatment of cardiometabolic diseases in those obese who are ‘at risk’.


Gaining a deeper insight into human metabolism: Applying chemical knowledge to systems biology for human health

PhD student: Denise Slenter, MSc
Supervising team: Prof. Dr. Chris Evelo and Dr. Egon Willighagen
Start date: 15 February 2017
Description: This PhD project will focus on improved data analysis in ongoing research projects, by taking advantage of as much experimental data as possible. With novel approaches we hope to extract much more data from metabolomics experiments to integrate them with other available omics data. To further accommodate integrative analyses, the project will develop novel methods to calculate pathway enrichment, based on multiple types of omics data. Furthermore, network approaches may further help analyze the network of metabolites, pathways, genes, regulatory and epigenetic aspects involved in certain diseases.


Adding an extra lane to the bridge: Working towards omics approaches in regulatory risk assessment

PhD student: Marvin Martens, MSc
Supervising team: Prof. Dr. Chris Evelo and Dr. Egon Willighagen
Start date: 01 March 2017
Description: Marvin Martens is a PhD student at the department of Bioinformatics (BiGCaT) at Maastricht University and is involved in two EU-funded projects that aim towards improving risk assessment approaches: EU-ToxRisk (CORDIS Project ID: 681002) and OpenRiskNet (CORDIS Project ID: 731075). His main topic is the concept of the Adverse Outcome Pathways (AOPs). This is the ‘bridge’ between toxicological research and regulatory risk assessment, serving as a guidance for conducted risk assessment. Marvin is involved in the creation of these AOPs and the elaboration of this tool by annotations, linking databases and working towards the implementation of omics approaches in regulatory risk assessment by use of WikiPathways, pathway enrichment and network analysis.

 


Preclinical trial on Rett-mouse model (Joint PhD-project between Maastricht University and University of Sydney)

PhD student: Nasim Bahram Sangani, MSc
Supervising team: Prof. Dr. Leopold Curfs and Dr. Friederike Ehrhart
Start date: 07 April 2015 (US), April 2017 (UM)
Description: The implication of Histone Deacetylase 6 (HDAC6) in Rett Syndrome (RTT) has been revealed through several studies.HDAC6 is a transcriptional regulator and its upregulation in RTT neurons is associated with abnormal trafficking of brain derived neurotrophic factor (BDNF).However, the underlying mechanisms behind its disregulation remains unclear. Now, pathway analysis has deciphered the potential effect of MeCP2 deficiency on HDAC6 regulation. To elucidate the role of MeCP2 in HDAC6 upregulation,the protein interactors of MeCP2 and HDAC6 were extracted from BioGRID and GeneMANIA databases.Using Cystoscape 3.5.1, the regulatory interactions from ENCODE database were integrated to the network and the biological networks were constructed.The final interaction network was visualized by PathVisio 3.2.4 and uploaded to WikiPathways (http://www.wikipathways.org/instance/WP3987). We,for the first time,visualized the major players in HDAC6 interaction network that might potentially be altered as a result of MeCP2 mutations. Of interest,was the co-regulation of BDNF expression by HDAC6 and MeCP2 via two different pathways. We also visualized an mRNA processing pathway in which a target of MeCP2 has a functional interaction with HDAC6 to regulate neurite outgrowth. Among the roles of HDAC6 which fall further behind its regulatory activity, its dysregulation in RTT encouraged us to map a comprehensive HDAC6 interaction network. Moreover, the interest in therapeutic inhibition of HDAC6 has been raised remarkably over the last decade and this interaction map can address how to target a specific function of HDAC6 while its other functions are maintained unchanged.

 


Finished PhD projects:


Towards the complete picture: Combining modelling and experimental data in a systems biology approach

PhD student: Dr. Anwesha Bohler
Supervising team: Prof. Dr. Chris Evelo and Dr. Martina Summer-Kutmon
Thesis defence: 16 February 2017
Thesis: Link
Description: This content described in this thesis is a step towards the complete picture of a biological process and enables integration and visualization of metabolic fluxes from mathematical modelling on interactions alongside experimental measurements of genes, proteins, and metabolites on nodes of pathway diagrams or pathway representations of the models themselves.


Managing Biological Data in Pathways and Network

PhD student: Dr. Martina Summer-Kutmon
Supervising team: Prof. Dr. Chris Evelo and Dr. Susan Coort
Thesis defense: 22 January 2015
Thesis: Download
Description: The aim of the work described in this thesis is to show the power of biological pathways and networks to store, integrate, analyze, visualize and interpret biological data. In this thesis, we moves from the applicability of focused, smaller biological pathway models to the advantages and challenges of larger, more complex biological networks. The thesis discusses the importance of data curation of pathway and interaction data, the challenges of data integration and the role of open data, open access and open source in biomedical research.


Understanding regulation of gene transcription through epigenomics and cistromics: unfolding ones and zeros into (un)folding chromatin

PhD student: Dr. Michiel Adriaens
Supervising team: Prof. Dr. Frederik-Jan van Schooten and Dr. Chris Evelo
Thesis defense: 21 June 2012
Thesis: Download
Description: Of all the steps involved in the analysis of epigenomics and cistromics data, the biological interpretation will remain the step that requires curation by human experts. The role of a bioinformatician should always be to make that step as smooth as possible for the biologist by creating standardized, biology driven approaches. The work presented in this thesis contributes to the standardization of analysis approaches in the field of epigenomics and cistromics by providing standardized approaches for data pre-processing of ChIP-on-chip and MeDIP-on-chip microarray data, for data pre-processing of blanketing histone modification ChIP-seq data, for human expert curation of existing biological knowledge to enable a comprehensive biological interpretation, and lastly for the biological interpretation of epigenomics and cistromics data. Applying the developed approaches in biological research has yielded new insights in the mechanisms behind estrogen-dependent breast cancer and epigenetic reprogramming in hypoxic tumors. Future developments should be directed towards automating the methods and making them available as services to the scientific community. The work presented in this thesis is only a small part of the field of systems biology. All efforts in this field together have revolutionized biological research. And in this age of biology, it is only a matter of time before they claim their justly place in the clinic and everyday life as well.


Exploratory pathway analysis

PhD student: Dr. Thomas Kelder
Supervising team: Prof. Dr. Frederik-Jan van Schooten and Dr. Chris Evelo
Thesis defense: 8 July 2011
Thesis: Download
Description: This thesis covered merely a fraction of the current developments towards better exploratory data analysis methods in the context of biological pathways. Pathway based approaches for data analysis and visualization continue to mature and become more established and standardized. This work contributed to this process by providing a platform for maintaining pathway information, an infrastructure to use it computationally and by demonstrating how these flexible tools and resources can be used to push the boundaries of pathway analysis. Our ability to measure biological phenomena in more detail and higher quantities keeps improving and the computational power to process and integrate this data continues to grow. However, interpretation largely remains a human task. By providing an interface between computer and human, the role of biological pathways in the process of exploring and understanding this data becomes increasingly important.


Data integration with biological pathways

PhD student: Dr. Martijn van Iersel
Supervising team: Prof. Dr. Edwin Mariman and Dr. Chris Evelo
Thesis defense: 05 November 2010
Thesis: Download
Description: The title of this thesis is “Data Integration with Biological Pathways”. Integration of data is currently one of the main problems in bioinformatics. In this thesis, integration of information occurs at several levels. Pathway diagrams can be used at one level, to integrate various bits of information, such as protein interactions, cellular locations, gene identifiers and literature references. At another level, identifier mapping services are used to integrate datasets from various sources. And finally, experimental data can be integrated with pathway diagrams to create visualizations that make the data easier to interpret.