This page is under development; more information will be added over time. For now, it presents an overview of my programming work, and the projects I did during my biology master at the Vrije Universiteit Amsterdam.

If you have any comments regarding this site, you can send an e-mail to jorn-www@xs4all.nl

Curriculum vitae

Curriculum vitae

Programming projects

"INCA: INsect Count Analyzer"
Free-lance project for the Urban Wildlands Group, Los Angeles, December 2001 – March 2002

Description: INCA is a user-friendly computer program that analyzes data from transect counts: the number of insects along a fixed route on a number of days. In its analysis, INCA uses the Zonneveld model, which contains four parameters: an index of population size, the time of peak emergence, spread in emergence times, and the death rate. INCA returns estimates for each of these parameters, complete with standard deviations. In addition, it displays a chart containing both your data and the model fit; this allows you to judge the model description.

INCA is freely available and can be downloaded from the Urban Wildlands Group site.

Free-lance project, suggested by the Department of Theoretical biology, Vrije Universiteit Amsterdam, August 2004 - present

Description: PlotReader is a plot digitizer. It is a Windows program that enables you to retrieve data point coordinates from an image (scanned, photographed or other) that contains a plot. You simply open or paste a plot image in PlotReader, set 2 calibration points per axis, and click all points you want coordinates for. PlotReader will then calculate the original plot coordinates, and allows you to export these to file or clipboard.

PlotReader is freely available and can be downloaded from my site.

Master projects

"Modeling Emiliania huxleyi: photosynthesis, calcification, and the global CO2 increase"
Internship, department of Theoretical biology, Vrije Universiteit Amsterdam, February 2000 – July 2001
Supervision: Dr. Cor Zonneveld, Prof. Dr. S.A.L.M. Kooijman

Summary: Coccolithophorids are a group of unicellular marine algae considered to be responsible for the major part of the earth’s calcite production. This process plays an important role in the global carbon cycle, and may to a certain extent affect future developments in atmospheric CO2. Our aim was to model the physiology of one of the most common coccolithophorids: Emiliania huxleyi. The model should allow for application in research related to the global climate and carbon cycle. Using the Dynamic Energy Budget modeling approach (Kooijman, 2000), a dynamic model was constructed that described all major carbon fluxes in a population of E. huxleyi, as a function of external light intensity, CO2 , HCO3- and NO3-. Steady state analysis of this initial model revealed some serious model shortcomings related to the interaction between calcification and photosynthesis. The model was modified to include a biochemically more realistic representation of these processes: an internal CO2 pool was added, which supplied CO2 to photosynthesis, and obtained CO2 from calcification. This corresponds more closely to the current hypotheses regarding calcification. Steady state analysis showed obvious improvements in the behavior of the model. Subsequently, the model was used to describe the behavior of Emiliania at various concentrations of ambient CO2, illustrating the model’s use in its targeted area of research. Although the model was able to describe the data, we must conclude that the datasets were too limited to constrain the parameter values. Clearly, the complexity of the model places severe requirements on the quality and quantity of the data used. If these requirements were satisfied, the model could be valuable not only in research related to the global climate, but also to that focusing on the biochemistry and physiology of calcification.

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"Mining MIM: Phenotype clustering as source of candidate genes"
Internship, department of Bioinformatics, Wageningen University, November 2002 - April 2003
Supervision: Prof. Dr. Jack Leunissen

Summary: Given a description of an anomalous phenotype, one may well be able find the gene(s) responsible for the anomaly in a list of genes associated with very similar phenotypes. Thus, a technique that identifies similar phenotypes could be exploited as a resource of candidate genes. In this project, we aim to develop such a technique.
As test case, we take the Online Mendelian Inheritance in Man (OMIM) database, which contains 14,000+ articles describing human inheritable traits and diseases. To determine the similarity between OMIM articles, we first characterize each article by the occurrence of a select set of (bio)medical terms. This set comprises the ‘anatomy’ and ‘disease’ categories of the Medical Subject Headings (MeSH) thesaurus. All MeSH entries are regarded as potential features of an OMIM article; per article, the value of any such feature is taken equal to the number of occurrences of the corresponding entry. In addition, we add for each matched entry its MeSH ancestors (i.e. the entries describing a superset of the entry) to the feature vector. This allows for closely related terms (sharing ancestors) to contribute to between-article similarity rather than diminishing it; in effect, the system has become term-relation-aware. Finally, feature vectors are corpus-size normalized, and feature values are weighed according to a scheme common in the field of information retrieval.
To determine similarity between phenotype feature vectors, we calculate their length-normalized correlation (i.e. the cosine of the angle between the vectors). With this similarity measure, we can list phenotypes similar to a given reference, ordered by proximity (i.e. ranking). In addition, we perform hierarchical clustering (UPGMA) on the full set of phenotypes.
To establish whether phenotype similarities indicate genotype similarities, we derive a genotype feature matrix for a set of ±1,000 OMIM articles, selecting as features the Gene Ontology (GO) terms indirectly associated with the articles. Subsequently, we calculate the correlation between phenotype- and genotype proximity matrices, both pre- and post-clustering.
Result evaluation is difficult, as the set of phenotypes is large, and calculation of the significance of phenotype-genotype correlation coefficients is not feasible. However, both random sampling of article neighbors and qualitative evaluation of correlation coefficients indicate our system could prove a valuable resource of candidate genes. This is specifically the case for human phenotypes (i.e. OMIM); current application for other species may be troublesome due to low-quality phenotype descriptions, and lack of a dictionary with phenotype-describing terms.

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"Religion: Spandrel of the Brain? The Evolutionary Psychology of Religion"
Literature study, department of Theoretical biology, Amsterdam, July - September 2003
Supervision: Dr. Cor Zonneveld

Summary: During the last decades, research into the biological origin of religion has gained considerable momentum. Religiousness has been shown to be heritable – though only to a moderate extent – which has prompted various scholars (e.g. D.S. Wilson, R.D. Alexander) to argue religion is an adaptation: a genetically inherited trait that increases fitness. However, as Stephen J Gould has forcefully argued, not all inheritable traits need be adaptations; in various ways traits can emerge and persist in evolution without increasing fitness per se. In this literature study, I explore the possibility that religion is not an adaptation, but exists for different reasons.
Non-adaptive traits can persist as by-products of adaptive traits. A number of scholars (P. Boyer, L. Kirkpatrick, S. Atran, S.J. Mithen, S. Guthrie) have argued religion qualifies as a by-product of cognitive hardware. In their view, religious thought and behavior is produced by various brain mechanisms that in themselves are adaptive. These were preserved in evolution because they solved particular (non-religious) problems faced by our ancestors. By-product theories of religion provide an interesting and plausible alternative to their adaptationist counterparts: they are capable of explaining the full spectrum of religious manifestations, without invoking any function for which they were selected.
Five million years ago, the evolutionary paths of man and chimpanzee separated: our last common ancestor eventually gave rise to a distinct human ancestor – Australopithecus – and an ‘ancestral’ chimpanzee. In the period to follow, the ape-like Australopithecus came to evolve into the modern Homo sapiens sapiens; selection pressures over the last five millions years gave rise to all traits commonly considered uniquely human (e.g. language, culture). What were these selection pressures like? Many have argued that our ancestor most prominently was under great pressure to organize: formation of ever-larger groups would have been indispensable for coordinated hunting- and gathering expeditions, and defense against predators (animals, but also other human groups).
To enable increases in group size, our brain has become strongly focused on other humans: it ascribes them beliefs, intentions and emotional states, feels their pain, shares their moral codes, and watches closely if others adhere to such codes. In fact, the human brain has become so strongly focused on humans that it quite easily perceives humans when there are none: any inexplicable phenomenon, any single or remarkable event is ascribed to human agents. In addition, the new cognitive hardware for active reasoning about other humans tends to over-activity: it fails to shutdown when observing familiar corpses (thus leaving the brain with the concept of a bodiless human agent), and prefers to represent the subconscious self as beliefs and intentions of others. As a result, the brain cannot help but observe an environment flooded with (signs of) powerful, invisible supernatural agents. Given the means through which it does so, it is not surprising that the brain holds quite elaborate assumptions on the nature of such agents: they are thought powerful, invisible or acting remotely, and involved in social exchange (and hence, to a certain extent manageable – one could achieve something by engaging in social interaction with the supernatural).
Summarizing, the brain inadvertently develops the notion of relevant supernatural agents: certainly an ideal starting point for religious thought and practices. Five million years 3 of specializing in social interaction rendered a well-adapted brain that fluidly – yet inadvertently – constructs its own religions.

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last update: November 12, 2010. Copyright Jorn Bruggeman.