How Well Do Facts Travel?: Packaging Small Facts for Re-Use: Databases in Model Organism Biology

Model organism such as fruit-flies, mice and zebrafish are the undisputed protagonists of 21 century biology. Their prominent position as experimental systems has been further enhanced by the recent sequencing of their genomes, which opened up new opportunities for cross-species comparisons and inferences (the so-called ‘post-genomic era’). Such comparative research requires that facts about model organisms be able to travel across a multitude of research contexts. Indeed, the very idea of focusing on a limited set of organisms stems from the desire to bring together as many facts about these organisms as possible, in the hope to increase the scientific understanding of their biology and thus use them as representatives for the study of other species. Moreover, the high costs associated to the production of facts make their use beyond their context of production into an economic, as well as a scientific, priority.

[1]  Sabina Leonelli,et al.  On the Locality of Data and Claims about Phenomena , 2009, Philosophy of Science.

[2]  Ann Zimmerman,et al.  Not by metadata alone: the use of diverse forms of knowledge to locate data for reuse , 2007, International Journal on Digital Libraries.

[3]  K. Raj Relocating Modern Science: Circulation and the Construction of Knowledge in South Asia and Europe, 1650-1900 , 2007 .

[4]  M. Norton Wise,et al.  Science without laws : model systems, cases, exemplary narratives , 2007 .

[5]  Alberto Cambrosio,et al.  Making a New Technology Work: The Standardization and Regulation of Microarrays , 2007, The Yale journal of biology and medicine.

[6]  Barry Barnes,et al.  Genomes and What to Make of Them , 2008 .

[7]  I. Verma The Common Thread: A Story of Science, Politics, Ethics and the Human Genome , 2002, Nature Medicine.

[8]  Frank J. Bruggeman,et al.  Systems Biology: Philosophical Foundations , 2007 .

[9]  L. Blanchoin,et al.  Arabidopsis VILLIN1 Generates Actin Filament Cables That Are Resistant to Depolymerization , 2005, The Plant Cell Online.

[10]  Sabina Leonelli Arabidopsis, the botanical Drosophila: from mouse cress to model organism. , 2007, Endeavour.

[11]  H. Longino The Fate of Knowledge , 2001 .

[12]  J. Becker,et al.  The Aim and Structure of Physical Theory , 1955 .

[13]  Rachel A. Ankeny,et al.  Wormy Logic: Model Organisms as Case-Based Reasoning , 2006, Science without Laws.

[14]  M. Ashburner,et al.  The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration , 2007, Nature Biotechnology.

[15]  Nadine Schuurman,et al.  Ontologies for Bioinformatics , 2008, Bioinformatics and biology insights.

[16]  Winston A Hide,et al.  Big data: The future of biocuration , 2008, Nature.

[17]  Eugenie V. Mielczarek,et al.  Rosalind Franklin: The Dark Lady of DNA , 2002 .

[18]  S. Hilgartner Biomolecular Databases , 1995 .

[19]  Jeff Augen Bioinformatics in the Post-Genomic Era: Genome, Transcriptome, Proteome, and Information-Based Medicine , 2004 .

[20]  D. Kell,et al.  Here is the evidence, now what is the hypothesis? The complementary roles of inductive and hypothesis-driven science in the post-genomic era. , 2004, BioEssays : news and reviews in molecular, cellular and developmental biology.

[21]  Christine Hine,et al.  Databases as Scientific Instruments and Their Role in the Ordering of Scientific Work , 2006 .

[22]  Ulrich Krohs,et al.  Data without models merging with models without data , 2007 .

[23]  Donald R Ort,et al.  Plant Physiology and TAIR Partnership , 2008, Plant Physiology.

[24]  Sabina Leonelli Centralising Labels to Distribute Data: The Regulatory Role of Genomic Consortia , 2009 .

[25]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[26]  J. Woodward,et al.  Saving the phenomena , 1988 .

[27]  Siobain Duffy,et al.  Rosalind Franklin: the Dark Lady of DNA , 2003, The Yale Journal of Biology and Medicine.

[28]  T. D. Wu,et al.  Bioinformatics in the post-genomic era. , 2001, Trends in biotechnology.

[29]  A. Pickering Science as practice and culture , 1992 .