Tim HulsenPhilips | Philips · Professional Health Solutions & Services
Tim Hulsen
PhD
Working on LIMA (Liquid Biopsies and Imaging), ReIMAGINE and other projects in oncology, data management & data science.
About
59
Publications
9,692
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
1,824
Citations
Introduction
Tim Hulsen currently works on Translational Research IT at Philips Research. His expertise is in bioinformatics, genomics, prostate cancer, data science, data management and data curation. His current projects are: Movember GAP3, RE-IMAGINE and LIMA.
Additional affiliations
May 2014 - present
Philips Research
Position
- Project Manager
January 2010 - May 2014
Philips Research
Position
- Senior Researcher
March 2009 - December 2009
Philips Research
Position
- Senior Researcher
Education
September 1997 - May 2001
Publications
Publications (59)
Data science is an interdisciplinary field that applies numerous techniques, such as
machine learning (ML), neural networks (NN) and artificial intelligence (AI), to create
value, based on extracting knowledge and insights from available ‘big’ data. The recent advances in data science and AI have had a major impact on healthcare already, as can be...
Some embodiments are directed to a method for anonymizing a genomic data set. The method comprises receiving the genomic data set and obtaining a phenotypic probability for at least one phenotype informative single nucleotide polymorphism (SNP) of the genomic data set and a proportion of a population which exhibits a corresponding phenotypic trait....
Artificial intelligence (AI), as recently defined by the European Commission, refers to systems that display intelligent behavior by analyzing their environment and taking actions—with some degree of autonomy-to achieve specific goals. AI is already being used in many industries, including healthcare, to go from “big” data to information, knowledge...
Data science is an interdisciplinary field that applies numerous techniques, such as
machine learning (ML), neural networks (NN) and artificial intelligence (AI), to create
value, based on extracting knowledge and insights from available ‘big’ data. The recent advances in data science and AI have had a major impact on healthcare already, as can be...
Introduction
Prostate cancer (PCa) is the most frequent cancer diagnosis in men worldwide. Our ability to identify those men whose cancer will decrease their lifespan and/or quality of life remains poor. The ReIMAGINE Consortium has been established to improve PCa diagnosis.
Materials and methods
MRI will likely become the future cornerstone of...
Artificial intelligence (AI) refers to the simulation of human intelligence in machines, using machine learning (ML), deep learning (DL) and neural networks (NNs). AI enables machines to learn from experience and perform human-like tasks. The field of AI research has been developing fast over the past five to ten years, due to the rise of ‘big data...
Artificial Intelligence (AI) refers to the simulation of human intelligence in machines, using machine learning, deep learning and neural networks. AI enables machines to learn from experience and perform human-like tasks. The field of AI research has been developing fast over the past five to ten years, due to the rise of ‘big data’ and increasing...
Artificial Intelligence (AI) refers to the simulation of human intelligence in machines, using machine learning, deep learning and neural networks. AI enables machines to learn from experience and perform human-like tasks. The field of AI research has been developing fast over the past five to ten years, due to the rise of 'big data' and increasing...
One of the most popular methods to visualize the overlap and differences between data sets is the Venn diagram. Venn diagrams are especially useful when they are 'area-proportional' i.e. the sizes of the circles and the overlaps correspond to the sizes of the data sets. In 2007, the BioVenn web interface was launched, which is being used by many re...
The Clinical Data Lake (CDL) allows managing and sharing clinical data sets in a scalable way to accelerate collaborative data-driven research, while conforming to healthcare privacy and regulatory requirements. Capabilities include (but not limited to):
- a data ingestion pipeline for ingesting large volumes of data
- an extensible data curation w...
“Big data” is a term that has been used often in the past decade to describe datasets that are extremely large and complex so that traditional software is unable to store and analyze them in an accurate way. It can refer to “long data,” “wide data,” and both. Big data is of increasing importance in healthcare as well: new methods dedicated to impro...
In recent years, more and more health data are being generated. These data come not only from professional health systems, but also from wearable devices. All these 'big data' put together can be utilized to optimize treatments for each unique patient ('precision medicine'). For this to be possible, it is necessary that hospitals, academia and indu...
Translational research applies findings from basic science to enhance human health and well-being. In translational research projects, academia and industry work together to improve healthcare, often through public-private partnerships. This “translation” is often not easy, because it means that the so-called “valley of death” will need to be cross...
Developing a future-proof database for the European Randomized
Study of Screening for Prostate Cancer (ERSPC)
Prostate cancer (PCa) is the second most common cancer in men, and the second leading cause of death from cancer in men. Many studies on PCa have been carried out, each taking much time before the data is collected and ready to be analyzed. However, on the internet there is already a wide range of PCa datasets available, which could be used for dat...
For over a decade the term “Big data” has been used to describe the rapid increase in volume, variety and velocity of information available, not just in medical research but in almost every aspect of our lives. As scientists, we now have the capacity to rapidly generate, store and analyse data that, only a few years ago, would have taken many years...
Introduction & Objectives
The European Randomized Study of Screening for Prostate Cancer (ERSPC) is a combined and integrated study performed by 9 institutions in 8 European countries (the Netherlands, Sweden, Finland, Belgium, France (x2), Spain, Italy and Switzerland), existing since 1992. It is the world’s largest randomized prostate cancer scre...
Translational Research IT at Philips Research
An overview of publicly available patient-centered prostate cancer datasets
INTRODUCTION AND OBJECTIVES
Prostate cancer (PCa) is the second most common cancer in men, and the second leading cause of death from cancer in men. Many studies on PCa have been carried out, each taking much time before the data is collected and ready to be analyzed. However, on the internet there is already a wide range of PCa datasets available...
A method, a system and a computer program product for anonymization of genetic data from at least one individual wherein the genetic data are grouped into a subset of genetic data being directly related to a disease and one or more subsets of genetic data being distantly related to the disease based upon the genome pathways network, and wherein the...
In August 2014, the Movember Foundation launched the Global Action Plan Prostate Cancer Active Surveillance (GAP3) initiative. This global project aims to create the largest centralized prostate cancer active surveillance database to date, comprising the majority of the world’s organized active surveillance patient data. This database will be used...
Objectives:
The Movember Foundation launched the Global Action Plan Prostate Cancer Active Surveillance (GAP3) initiative to create a global consensus on the selection and monitoring of men with low-risk prostate cancer (PCa) on active surveillance (AS). The aim of this study is to present data on inclusion and follow-up for AS in this unique glob...
A system and method are provided for generating a mapping function for use in loading data from a source database, which is structured in accordance with a source data model, into a target database, which is structured in accordance with a target data model. The mapping function is automatically generated, e.g., on the basis of descriptions of both...
Active surveillance (AS) is broadly described as a management option for men with low-risk prostate cancer, but semantic heterogeneity exists in both the literature and in guidelines. To address this issue, a panel of leading prostate cancer specialists in the field of AS participated in a consensus-forming project using a modified Delphi method to...
Prostate cancer is a major cause of death of men in the Western world. It can be treated by radiotherapy or surgical removal of the prostate, but a substantial number of patients suffer relapse due to metastatic tumours for which only palliative therapy is available. The Prostate Cancer Molecular Medicine (PCMM) project has addressed two major clin...
Integrating large datasets for the Movember Global Action Plan
on Active Surveillance for low risk Prostate Cancer
INTRODUCTION & OBJECTIVES:
The Movember Global Action Plan (GAP) on active surveillance for low risk prostate cancer includes the integrated 30 months activity of 19 institutions in 14 countries in the 5 Movember regions (Australasia, Europe, UK, Canada, and USA). The initiative is also open to other eligible centres. Milestones of the project incl...
In Western countries, prostate cancer is the most frequent malignancy and one of the major causes of cancer-related death in men. The Prostate Cancer Molecular Medicine (PCMM) project addresses two major clinical needs in prostate cancer, namely the reduction of overdiagnosis and overtreatment of this disease due to screening and the improvement of...
Background
Glucocorticoids are potent anti-inflammatory agents used for the treatment of diseases such as rheumatoid arthritis, asthma, inflammatory bowel disease and psoriasis. Unfortunately, usage is limited because of metabolic side-effects, e.g. insulin resistance, glucose intolerance and diabetes. To gain more insight into the mechanisms behi...
Background
Glucocorticoids are potent anti-inflammatory agents used for the treatment of diseases such as rheumatoid arthritis, asthma, inflammatory bowel disease and psoriasis. Unfortunately, usage is limited because of metabolic side-effects, e.g. insulin resistance, glucose intolerance and diabetes. To gain more insight into the mechanisms behin...
384 genes that are linked with insulin resistance in Medline abstracts. Table S3. Gene disease profiles. Table S4A. Enriched drug terms. Table S4B. Enriched disease terms. Table S4A.2. Genes linked with enriched drug terms. Table S4B.2. Genes linked with enriched disease terms. Table S5. 131 genes that linked with osteoporosis.
Part of the disease matrix, which has been used for the clustering.
Hierarchical cluster of disease terms from the CoPub database with bootstrapping values. Red numbers at the nodes represent Approximately Unbiased (AU) bootstrap values (%). Green numbers at the nodes represent Bootstrap Probability (BP) value (%).
Enriched disease terms found per sub-cluster when searching with the DAVID annotation server.
Network of top scoring genes with osteoporosis. Genes in blue have a co-occurrence with dexamethasone in Medline abstracts (R-scaled score). The strength of the link with dexamethasone is given by the color shading, ranging from no link (white) to a strong link (dark blue). The strength of the link with inflammation (R-scaled score) is given by the...
Distribution of connectivity of IR related gene network. The node connectivity follows a significant power law distribution (p-value < 0.001).
The present invention relates to a tumor marker or group of tumor markers associated with the progression of a cancer disease from a less progressed stage to a more progressed stage, wherein the expression of the tumor markers is modified when comparing the expression in the less progressed stage and in the more progressed stage. The present invent...
The present invention relates to a tumor marker or group of tumor markers associated with the progression of a neoplastic disease from a less progressed stage to a more progressed stage, wherein the expression of the tumor markers is modified when comparing the expression in the less progressed stage and in the more progressed stage. The present in...
The present invention relates to a tumor marker or group of tumor markers associated with the progression of a cancer disease from a less progressed stage to a more progressed stage, wherein the expression of the tumor markers is modified when comparing the expression in the less progressed stage and in the more progressed stage. The present invent...
The present invention relates to a tumor marker or group of tumor markers associated with the progression of a neoplastic disease from a less progressed stage to a more progressed stage, wherein the expression of the tumor marker or group of tumor markers is modified when comparing the expression of the tumor marker or group of tumor markers in the...
The present invention relates to a tumor marker or group of tumor markers associated with the progression of a cancer disease from a less progressed stage to a more progressed stage, wherein the expression of the tumor markers is modified when comparing the expression in the less progressed stage and in the more progressed stage. The present invent...
The present invention relates to a tumor marker or group of tumor markers associated with the progression of a neoplastic disease from a less progressed stage to a more progressed stage, wherein the expression of the tumor markers is modified when comparing the expression in the less progressed stage and in the more progressed stage. The present in...
The present invention relates to a tumor marker or group of tumor markers associated with the progression of a cancer disease from a less progressed stage to a more progressed stage, wherein the expression of the tumor markers is modified when comparing the expression in the less progressed stage and in the more progressed stage. The present invent...
Gene-oriented sequence clusters (transcriptional units) have found many applications in genomics research including the construction of transcriptome maps and identification of splice variants. We developed a new method to construct transcriptional that uses the genomic sequence as a template. We present and discuss our method in detail together wi...
Phylogenetic patterns show the presence or absence of certain genes in a set of full genomes derived from different species.
They can also be used to determine sets of genes that occur only in certain evolutionary branches. Previously, we presented
a database named PhyloPat which allows the complete Ensembl gene database to be queried using phyloge...
In many genomics projects, numerous lists containing biological identifiers are produced. Often it is useful to see the overlap between different lists, enabling researchers to quickly observe similarities and differences between the data sets they are analyzing. One of the most popular methods to visualize the overlap and differences between data...
The orientation of closely linked genes in mammalian genomes is not random: there are more head-to-head (h2h) gene pairs than expected. To understand the origin of this enrichment in h2h gene pairs, we have analyzed the phylogenetic distribution of gene pairs separated by less than 600 bp of intergenic DNA (gene duos). We show here that a lack of h...
Our current knowledge of the general factor requirement in transcription by the three mammalian RNA polymerases is based on a small number of model promoters. Here, we present a comprehensive chromatin immunoprecipitation (ChIP)-on-chip analysis for 28 transcription factors on a large set of known and novel TATA-binding protein (TBP)-binding sites...
All of the protein pairs that are considered to be 'true orthologs' within our ortholog reference set, consisting of several protein families. The first column contains the name of the protein family, the second the human gene names and the third the mouse/worm gene names. The fourth column contains the corresponding human 'Protein World' entries,...
All end data used to create the figures.
In the past years the Smith-Waterman sequence comparison algorithm has gained popularity due to improved implementations and rapidly increasing computing power. However, the quality and sensitivity of a database search is not only determined by the algorithm but also by the statistical significance testing for an alignment. The e-value is the most...
Phylogenetic patterns show the presence or absence of certain genes or proteins in a set of species. They can also be used to determine sets of genes or proteins that occur only in certain evolutionary branches. Phylogenetic patterns analysis has routinely been applied to protein databases such as COG and OrthoMCL, but not upon gene databases. Here...
The transfer of functional annotations from model organism proteins to human proteins is one of the main applications of comparative genomics. Various methods are used to analyze cross-species orthologous relationships according to an operational definition of orthology. Often the definition of orthology is incorrectly interpreted as a prediction o...
Many G protein-coupled receptor (GPCR) models have been built over the years. The release of the structure of bovine rhodopsin in August 2000 enabled us to analyze models built before that period to learn more about the models we build today. We conclude that the GPCR modelling field is riddled with 'common knowledge' similar to Lord Kelvin's remar...
The immune system is of major importance since it protects metazoans from infection by pathogenic organisms. Throughout evolution, two major branches have originated: innate and adaptive immunity. The innate immune system exists in a wide range of metazoans, whereas the adaptive immune system is only present in jawed vertebrates. Both the innate an...
Projects
Projects (10)
PIONEER is part of the Innovative Medicine Initiative’s (IMI’s) “Big Data for Better Outcomes” (BD4BO) umbrella programme. The BD4BO mission is to improve health outcomes and healthcare systems in Europe by maximising the potential of Big Data
PIONEER aims to transform the field of prostate cancer care with particular focus on improving prostate-cancer related outcomes, health system efficiency and the quality of health and social care across Europe.
See https://prostate-pioneer.eu.
Prostate cancer (PCa) is the most common malignancy in Western men. When localised within the prostate, the tumour can be treated by radiotherapy or surgical removal of the prostate. However, a substantial number of patients suffer relapse due to metastatic tumours that can only be treated by palliative therapy.
The Prostate Cancer Molecular Medicine (PCMM) project will address two major clinical needs. Firstly, the need to reduce overdiagnosis and overtreatment of prostate cancer due to today’s less than ideal screening tests (PSA tests). Secondly, the need for better therapy monitoring techniques for advanced disease.
To improve overdiagnosis, the project will attempt to develop and validate novel biomarkers in blood, urine and tissue that can be used to differentially diagnose and evaluate prognosis for individual patients, and that can also be applied for tailored treatment. To improve therapy monitoring for metastatic tumours, it will develop and test innovative imaging tools that can be used to visualise and evaluate early response to treatment, allowing therapy management at the level of the individual patient.
The biomarker and imaging studies in PCMM will be facilitated by a unique Dutch prospective biobank composed of biological specimens and imaging data from patients with various stages of prostate cancer. An IT infrastructure will be designed that allows for the integration of clinical and research data in a central database.
