Jildau Bouwman

Bio: Jildau Bouwman is an academic researcher from Netherlands Organisation for Applied Scientific Research. The author has contributed to research in topics: Systems biology & Regulation of gene expression. The author has an hindex of 28, co-authored 61 publications receiving 7407 citations. Previous affiliations of Jildau Bouwman include Utrecht University & VU University Amsterdam.

The FAIR Guiding Principles for scientific data management and stewardship

Abstract: There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.

Synapse formation between central neurons requires postsynaptic expression of the MEN1 tumor suppressor gene.

Abstract: Synapse formation is a crucial step in the development of neuronal circuits and requires precise coordination of presynaptic and postsynaptic activities However, molecular mechanisms that control the formation of functionally mature synaptic contacts, in particular between central neurons, remain poorly understood To identify genes that are involved in the formation of central synapses, we made use of molluscan neurons that in culture form synaptic contacts between their somata (soma‐ soma synapses) in the absence of neurite outgrowth Using single-cell mRNA differential display, we have identified a molluscan homolog of the multiple endocrine neoplasia type 1 (MEN1) tumor suppressor gene encoding the transcription factor menin as a gene that is upregulated during synapse formation In vitro antisense knock-down of MEN1 mRNA blocks the formation of mature synapses between different types of identified central neurons Moreover, immunocytochemistry and cell-specific knock-down of MEN1 mRNA show that postsynaptic but not presynaptic expression is required for synapses to form Together, our data demonstrate that menin is a synaptogenic factor that is critically involved in a general postsynaptic mechanism of synapse formation between central neurons

Effect of personalized nutrition on health-related behaviour change: evidence from the Food4me European randomized controlled trial

Abstract: This is a pre-copyedited, author-produced version of an article accepted for publication in International Journal of Epidemiology following peer review. The version of record [Carlos Celis-Morales, et al, 'Effect of personalized nutrition on health-related behaviour change: evidence from the Food4Me European randomized controlled trail', International Journal of Epidemiology, Vol. 46 (2): 578-588, August 2016] is available online at: https://academic.oup.com/ije/article-lookup/doi/10.1093/ije/dyw186.

Addendum: The FAIR Guiding Principles for scientific data management and stewardship

Abstract: There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders-representing academia, industry, funding agencies, and scholarly publishers-have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.

Measuring enzyme activities under standardized in vivo-like conditions for Systems Biology

Abstract: Realistic quantitative models require data from many laboratories. Therefore, standardization of experimental systems and assay conditions is crucial. Moreover, standards should be representative of the in vivo conditions. However, most often, enzyme-kinetic parameters are measured under assay conditions that yield the maximum activity of each enzyme. In practice, this means that the kinetic parameters of different enzymes are measured in different buffers, at different pH values, with different ionic strengths, etc. In a joint effort of the Dutch Vertical Genomics Consortium, the European Yeast Systems Biology Network and the Standards for Reporting Enzymology Data Commission, we have developed a single assay medium for determining enzyme-kinetic parameters in yeast. The medium is as close as possible to the in vivo situation for the yeast Saccharomyces cerevisiae, and at the same time is experimentally feasible. The in vivo conditions were estimated for S. cerevisiae strain CEN.PK113-7D grown in aerobic glucose-limited chemostat cultures at an extracellular pH of 5.0 and a specific growth rate of 0.1 h(-1). The cytosolic pH and concentrations of calcium, sodium, potassium, phosphorus, sulfur and magnesium were determined. On the basis of these data and literature data, we propose a defined in vivo-like medium containing 300 mM potassium, 50 mM phosphate, 245 mM glutamate, 20 mM sodium, 2 mM free magnesium and 0.5 mM calcium, at a pH of 6.8. The V(max) values of the glycolytic and fermentative enzymes of S. cerevisiae were measured in the new medium. For some enzymes, the results deviated conspicuously from those of assays done under enzyme-specific, optimal conditions.

The Pfam protein families database in 2019.

Abstract: The last few years have witnessed significant changes in Pfam (https://pfam.xfam.org). The number of families has grown substantially to a total of 17,929 in release 32.0. New additions have been coupled with efforts to improve existing families, including refinement of domain boundaries, their classification into Pfam clans, as well as their functional annotation. We recently began to collaborate with the RepeatsDB resource to improve the definition of tandem repeat families within Pfam. We carried out a significant comparison to the structural classification database, namely the Evolutionary Classification of Protein Domains (ECOD) that led to the creation of 825 new families based on their set of uncharacterized families (EUFs). Furthermore, we also connected Pfam entries to the Sequence Ontology (SO) through mapping of the Pfam type definitions to SO terms. Since Pfam has many community contributors, we recently enabled the linking between authorship of all Pfam entries with the corresponding authors' ORCID identifiers. This effectively permits authors to claim credit for their Pfam curation and link them to their ORCID record.

The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019.

Abstract: The GWAS Catalog delivers a high-quality curated collection of all published genome-wide association studies enabling investigations to identify causal variants, understand disease mechanisms, and establish targets for novel therapies. The scope of the Catalog has also expanded to targeted and exome arrays with 1000 new associations added for these technologies. As of September 2018, the Catalog contains 5687 GWAS comprising 71673 variant-trait associations from 3567 publications. New content includes 284 full P-value summary statistics datasets for genome-wide and new targeted array studies, representing 6 × 109 individual variant-trait statistics. In the last 12 months, the Catalog's user interface was accessed by ∼90000 unique users who viewed >1 million pages. We have improved data access with the release of a new RESTful API to support high-throughput programmatic access, an improved web interface and a new summary statistics database. Summary statistics provision is supported by a new format proposed as a community standard for summary statistics data representation. This format was derived from our experience in standardizing heterogeneous submissions, mapping formats and in harmonizing content. Availability: https://www.ebi.ac.uk/gwas/.

PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews.

Abstract: The methods and results of systematic reviews should be reported in sufficient detail to allow users to assess the trustworthiness and applicability of the review findings. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement was developed to facilitate transparent and complete reporting of systematic reviews and has been updated (to PRISMA 2020) to reflect recent advances in systematic review methodology and terminology. Here, we present the explanation and elaboration paper for PRISMA 2020, where we explain why reporting of each item is recommended, present bullet points that detail the reporting recommendations, and present examples from published reviews. We hope that changes to the content and structure of PRISMA 2020 will facilitate uptake of the guideline and lead to more transparent, complete, and accurate reporting of systematic reviews.

The Dishonesty of Honest People: A Theory of Self-Concept Maintenance

Abstract: Dishonesty plays a large role in the economy. Causes for (dis)honest behavior seem to be based partially on external rewards, and partially on internal rewards. Here, we investigate how such external and internal rewards work in concert to produce (dis)honesty. We propose and test a theory of self-concept maintenance that allows people to engage to some level in dishonest behavior, thereby benefiting from external benefits of dishonesty, while maintaining their positive view about themselves in terms of being honest individuals. The results show that (1) given the opportunity to engage in beneficial dishonesty, people will engage in such behaviors; (2) the amount of dishonesty is largely insensitive to either the expected external benefits or the costs associated with the deceptive acts; (3) people know about their actions but do not update their self-concepts; (4) causing people to become more aware of their internal standards for honesty decreases their tendency for deception; and (5) increasing the "degrees of freedom" that people have to interpret their actions increases their tendency for deception. We suggest that dishonesty governed by self-concept maintenance is likely to be prevalent in the economy, and understanding it has important implications for designing effective methods to curb dishonesty.Former working paper titles:“(Dis)Honesty: A Combination of Internal and External Rewards” and "Almost Honest: Internal and External Motives for Honesty")

The Gene Ontology resource: enriching a GOld mine

Abstract: The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations.