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Martijn Peter van Iersel


martijn.vaniersel@bigcat.unimaas.nl

Journal articles

2010
Martijn P van Iersel, Alexander R Pico, Thomas Kelder, Jianjiong Gao, Isaac Ho, Kristina Hanspers, Bruce R Conklin, Chris T Evelo (2010)  The BridgeDb framework: standardized access to gene, protein and metabolite identifier mapping services.   BMC Bioinformatics 11: 1. Jan  
Abstract: ABSTRACT: BACKGROUND: Many complementary solutions are available for the identifier mapping problem. This creates an opportunity for bioinformatics tool developers. Tools can be made to flexibly support multiple mapping services or mapping services could be combined to get broader coverage. This approach requires an interface layer between tools and mapping services. RESULTS: Here we present BridgeDb, a software framework for gene, protein and metabolite identifier mapping. This framework provides a standardized interface layer through which bioinformatics tools can be connected to different identifier mapping services. This approach makes it easier for tool developers to support identifier mapping. Mapping services can be combined or merged to support multi-omics experiments or to integrate custom microarray annotations. BridgeDb provides its own ready-to-go mapping services, both in webservice and local database forms. However, the framework is intended for customization and adaptation to any identifier mapping service. BridgeDb has already been integrated into several bioinformatics applications. CONCLUSION: By uncoupling bioinformatics tools from mapping services, BridgeDb improves capability and flexibility of those tools. All described software is open source and available at http://www.bridgedb.org.
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Emek Demir, Michael P Cary, Suzanne Paley, Ken Fukuda, Christian Lemer, Imre Vastrik, Guanming Wu, Peter D'Eustachio, Carl Schaefer, Joanne Luciano, Frank Schacherer, Irma Martinez-Flores, Zhenjun Hu, Veronica Jimenez-Jacinto, Geeta Joshi-Tope, Kumaran Kandasamy, Alejandra C Lopez-Fuentes, Huaiyu Mi, Elgar Pichler, Igor Rodchenkov, Andrea Splendiani, Sasha Tkachev, Jeremy Zucker, Gopal Gopinath, Harsha Rajasimha, Ranjani Ramakrishnan, Imran Shah, Mustafa Syed, Nadia Anwar, Ozgün Babur, Michael Blinov, Erik Brauner, Dan Corwin, Sylva Donaldson, Frank Gibbons, Robert Goldberg, Peter Hornbeck, Augustin Luna, Peter Murray-Rust, Eric Neumann, Oliver Reubenacker, Matthias Samwald, Martijn van Iersel, Sarala Wimalaratne, Keith Allen, Burk Braun, Michelle Whirl-Carrillo, Kei-Hoi Cheung, Kam Dahlquist, Andrew Finney, Marc Gillespie, Elizabeth Glass, Li Gong, Robin Haw, Michael Honig, Olivier Hubaut, David Kane, Shiva Krupa, Martina Kutmon, Julie Leonard, Debbie Marks, David Merberg, Victoria Petri, Alex Pico, Dean Ravenscroft, Liya Ren, Nigam Shah, Margot Sunshine, Rebecca Tang, Ryan Whaley, Stan Letovksy, Kenneth H Buetow, Andrey Rzhetsky, Vincent Schachter, Bruno S Sobral, Ugur Dogrusoz, Shannon McWeeney, Mirit Aladjem, Ewan Birney, Julio Collado-Vides, Susumu Goto, Michael Hucka, Nicolas Le Novère, Natalia Maltsev, Akhilesh Pandey, Paul Thomas, Edgar Wingender, Peter D Karp, Chris Sander, Gary D Bader (2010)  The BioPAX community standard for pathway data sharing.   Nat Biotechnol 28: 9. 935-942 Sep  
Abstract: Biological Pathway Exchange (BioPAX) is a standard language to represent biological pathways at the molecular and cellular level and to facilitate the exchange of pathway data. The rapid growth of the volume of pathway data has spurred the development of databases and computational tools to aid interpretation; however, use of these data is hampered by the current fragmentation of pathway information across many databases with incompatible formats. BioPAX, which was created through a community process, solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. Using BioPAX, millions of interactions, organized into thousands of pathways, from many organisms are available from a growing number of databases. This large amount of pathway data in a computable form will support visualization, analysis and biological discovery.
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2009
Thomas Kelder, Alexander R Pico, Kristina Hanspers, Martijn P van Iersel, Chris Evelo, Bruce R Conklin (2009)  Mining biological pathways using WikiPathways web services.   PLoS One 4: 7. 07  
Abstract: WikiPathways is a platform for creating, updating, and sharing biological pathways [1]. Pathways can be edited and downloaded using the wiki-style website. Here we present a SOAP web service that provides programmatic access to WikiPathways that is complementary to the website. We describe the functionality that this web service offers and discuss several use cases in detail. Exposing WikiPathways through a web service opens up new ways of utilizing pathway information and assisting the community curation process.
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2008
Martijn P van Iersel, Thomas Kelder, Alexander R Pico, Kristina Hanspers, Susan Coort, Bruce R Conklin, Chris Evelo (2008)  Presenting and exploring biological pathways with PathVisio.   BMC Bioinformatics 9: 09  
Abstract: BACKGROUND: Biological pathways are a useful abstraction of biological concepts, and software tools to deal with pathway diagrams can help biological research. PathVisio is a new visualization tool for biological pathways that mimics the popular GenMAPP tool with a completely new Java implementation that allows better integration with other open source projects. The GenMAPP MAPP file format is replaced by GPML, a new XML file format that provides seamless exchange of graphical pathway information among multiple programs. RESULTS: PathVisio can be combined with other bioinformatics tools to open up three possible uses: visual compilation of biological knowledge, interpretation of high-throughput expression datasets, and computational augmentation of pathways with interaction information. PathVisio is open source software and available at http://www.pathvisio.org. CONCLUSION: PathVisio is a graphical editor for biological pathways, with flexibility and ease of use as primary goals.
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Susan L M Coort, Martijn P van Iersel, Marjan van Erk, Teake Kooistra, Robert Kleemann, Chris T A Evelo (2008)  Bioinformatics for the NuGO proof of principle study: analysis of gene expression in muscle of ApoE3*Leiden mice on a high-fat diet using PathVisio.   Genes Nutr 3: 3-4. 185-191 Dec  
Abstract: Insulin resistance is a characteristic of type-2 diabetes and its development is associated with an increased fat consumption. Muscle is one of the tissues that becomes insulin resistant after high fat (HF) feeding. The aim of the present study is to identify processes involved in the development of HF-induced insulin resistance in muscle of ApOE3*Leiden mice by using microarrays. These mice are known to become insulin resistant on a HF diet. Differential gene expression was measured in muscle using the Affymetrix mouse plus 2.0 array. To get more insight in the processes, affected pathway analysis was performed with a new tool, PathVisio. PathVisio is a pathway editor customized with plug-ins (1) to visualize microarray data on pathways and (2) to perform statistical analysis to select pathways of interest. The present study demonstrated that with pathway analysis, using PathVisio, a large variety of processes can be investigated. The significantly regulated genes in muscle of ApOE3*Leiden mice after 12 weeks of HF feeding were involved in several biological pathways including fatty acid beta oxidation, fatty acid biosynthesis, insulin signaling, oxidative stress and inflammation.
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2007
W B Derry, R Bierings, M van Iersel, T Satkunendran, V Reinke, J H Rothman (2007)  Regulation of developmental rate and germ cell proliferation in Caenorhabditis elegans by the p53 gene network.   Cell Death Differ 14: 4. 662-670 Apr  
Abstract: Caenorhabditis elegans CEP-1 activates germline apoptosis in response to genotoxic stress, similar to its mammalian counterpart, tumor suppressor p53. In mammals, there are three p53 family members (p53, p63, and p73) that activate and repress many distinct and overlapping sets of genes, revealing a complex transcriptional regulatory network. Because CEP-1 is the sole p53 family member in C. elegans, analysis of this network is greatly simplified in this organism. We found that CEP-1 functions during normal development in the absence of stress to repress many (331) genes and activate only a few (28) genes. In response to genotoxic stress, 1394 genes are activated and 942 are repressed, many of which contain p53-binding sites. Comparison of the CEP-1 transcriptional network with transcriptional targets of the human p53 family reveals considerable overlap between CEP-1-regulated genes and homologues regulated by human p63 and p53, suggesting a composite p53/p63 action for CEP-1. We found that phg-1, the C. elegans Gas1 (growth arrest-specific 1) homologue, is activated by CEP-1 and is a negative regulator of cell proliferation in the germline in response to genotoxic stress. Further, we find that CEP-1 and PHG-1 mediate the decreased developmental rate and embryonic viability of mutations in the clk-2/TEL2 gene, which regulates lifespan and checkpoint responses.
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2006
Markus Storvik, Pekka Tiikkainen, Martijn van Iersel, Garry Wong (2006)  Distinct gene expression profiles in adult rat brains after acute MK-801 and cocaine treatments.   Eur Neuropsychopharmacol 16: 3. 211-219 Apr  
Abstract: Uncompetitive N-methyl-D-aspartate (NMDA) receptor antagonists have been suggested to attenuate the self-administration and rewarding effects of psychostimulants. Microarrays containing 14,500 rat cDNAs were hybridized to identify alterations in gene expression levels in rat brain regions elicited by the uncompetitive NMDA receptor antagonist MK-801 (dizocilpine, 1 mg/kg), the dopamine agonist cocaine (20 mg/kg), or combined treatment (MK-801 15 min prior to cocaine) 4 h after injections. Total genes up regulated (Z-ratio >2) in parietal cortex and nucleus accumbens were 111 and 158, respectively. Total genes down regulated (Z-ratio <2) in the same tissues were 360 and 166, respectively. These genes fell into multiple molecular function gene ontology (GO) categories, but were highly represented in catalytic activities (44% of all genes), signal transduction (14%), protein (20%), nucleotide (18%), and nucleic acid (15%) binding. In nucleus accumbens, genes up regulated by MK-801 (87 genes) did not overlap those up regulated by cocaine (46 genes). Genes down regulated by MK-801 (33 genes) consisted of 2 overlapping genes with those down regulated by cocaine (89 genes). In parietal cortex, low numbers of overlapping regulated genes were also observed. Combined treatments also indicated low numbers (0-10) of genes commonly regulated when compared with single treatments alone. In situ hybridisation studies indicated significant increases in b-ZIP transcription factors (CREM, ICER, CBP, and c-fos) elicited by MK-801 and decreases in c-fos elicited by cocaine. The results indicate independent gene expression signatures following acute MK-801 and cocaine administration that appears to be largely non-overlapping and context dependent.
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