August 17, 2012

What is the collective noun for a group of Systems Biologists?

From helix to hairball

According to Arthur Lander, “hairball” networks like the one of human proteins above, are the new icon of biology, taking over from the famous double-helix. Image originally published in BMC Biology [1].

What happened was, I was looking for a creatively commons licensed picture of Pedro Mendes to upload to commons.wikimedia.org. Not the footballing Pedro Mendes who played for Rangers, Spurs, Pompey and Porto but the systems biologist Pedro Mendes who plays for Virginia Tech and Manchester. Thankfully, another systems biologist, Michael Hucka kindly pointed to his impressive collection of pictures, taken at various events over the years which include some shots of Pedro. Looking at these pictures made me idly wonder: What is the collective noun for a group of systems biologists?

Systems biology is the study networks of various kinds [2,3] so it’s ripe for a collective noun, and there were several suggested on twitter. Since twitter has recently developed a nasty habit of disappearing tweets, here is a collection gathered and preserved for posterity from the twitterome*:

A jamboree of systems biologists?

Tom Williamson and Mike Hucka initially plumped for a Jamboree of systems biologists:

A loop or an ome of systems biologists?

Mike Hucka and Nathan Pearson voted for a Loop or an Ome of systems biologists:

A cluster of systems biologists?

Then again, maybe it should be a cluster of biologists?

A network of systems biologists?

Douglas Kell reckoned on a network of systems biologists:

A system of systems biologists?

Ewan Birney thought it had be be a system:

So there you have it, according to the twitterome, the collective noun for a group of systems biologists is a system, network, cluster, ome, jamboree or loop (delete as appropriate). No doubt there are many more, that’s what twitter hashtags are for, #SysBiologists.


  1. Arthur D. Lander (2010). The edges of understanding, BMC Biology, 8 (1) DOI: 10.1186/1741-7007-8-40
  2. Hiroaki Kitano (2002). Systems Biology: A Brief Overview, Science, 295 (5560) 1664. DOI: 10.1126/science.1069492
  3. Trey Ideker, Timothy Galitski & Leroy Hood (2001). Systems Biology: A new approach to decoding life, Annual Review of Genomics and Human Genetics, 2 (1) 372. DOI: 10.1146/annurev.genom.2.1.343

* That’s another #badomics award for Jonathan Eisen’s growing collection…don’t blame me, blame Leonid Kruglyak

September 4, 2009

XML training in Oxford

XML Summer School 2009The XML Summer School returns this year at St. Edmund Hall, Oxford from 20th-25th September 2009. As always, it’s packed with high quality technical training for every level of expertise, from the Hands-on Introduction for beginners through to special classes devoted to XQuery and XSLT, Semantic Technologies, Open Source Applications, Web 2.0, Web Services and Identity. The Summer School is also a rare opportunity to experience what life is like as a student in one of the world’s oldest university cities while enjoying a range of social events that are a part of the unique summer school experience.

This year, classes and sessions are taught and chaired by:

W3C XML 10th anniversaryThe Extensible Markup Language (XML) has been around for just over ten years, quickly and quietly finding its niche in many different areas of science and technology. It has been used in everything from modelling biochemical networks in systems biology [1], to electronic health records [2], scientific publishing, the provision of the PubMed service (which talks XML) [3] and many other areas. As a crude measure of its importance in biomedical science, PubMed currently has no fewer than 800 peer-reviewed publications on XML. It’s hard to imagine life without it. So whether you’re a complete novice looking to learn more about XML or a seasoned veteran wanting to improve your knowledge, register your place and find out more by visiting xmlsummerschool.com. I hope to see you there…


  1. Hucka, M. (2003). The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models Bioinformatics, 19 (4), 524-531 DOI: 10.1093/bioinformatics/btg015
  2. Bunduchi R, Williams R, Graham I, & Smart A (2006). XML-based clinical data standardisation in the National Health Service Scotland. Informatics in primary care, 14 (4) PMID: 17504574
  3. Sayers, E., Barrett, T., Benson, D., Bryant, S., Canese, K., Chetvernin, V., Church, D., DiCuccio, M., Edgar, R., Federhen, S., Feolo, M., Geer, L., Helmberg, W., Kapustin, Y., Landsman, D., Lipman, D., Madden, T., Maglott, D., Miller, V., Mizrachi, I., Ostell, J., Pruitt, K., Schuler, G., Sequeira, E., Sherry, S., Shumway, M., Sirotkin, K., Souvorov, A., Starchenko, G., Tatusova, T., Wagner, L., Yaschenko, E., & Ye, J. (2009). Database resources of the National Center for Biotechnology Information Nucleic Acids Research, 37 (Database) DOI: 10.1093/nar/gkn741

June 4, 2009

Improving the OBO Foundry Principles

The Old Smithy Pub by loop ohThe Open Biomedical Ontologies (OBO) are a set of reference ontologies for describing all kinds of biomedical data, see [1-5] for examples. Every year, users and developers of these ontologies gather from around the globe for a workshop at the EBI near Cambridge, UK. Following on from the first workshop last year, the 2nd OBO workshop 2009 is fast approaching.

In preparation, I’ve been revisiting the OBO Foundry documentation, part of which establishes a set of principles for ontology development. I’m wondering how they could be improved because these principles are fundamental to the whole effort. We’ve been using one of the OBO ontologies (called Chemical Entities of Biological Interest (ChEBI)) in the REFINE project to mine data from the PubMed database. OBO Ontologies like ChEBI and the Gene Ontology are really crucial to making sense of the massive data which are now common in biology and medicine – so this is stuff that matters.

The OBO Foundry Principles, a sort of Ten Commandments of Ontology (or Obology if you prefer) currently look something like this (copied directly from obofoundry.org/crit.shtml):

  1. The ontology must be open and available to be used by all without any constraint other than (a) its origin must be acknowledged and (b) it is not to be altered and subsequently redistributed under the original name or with the same identifiers.The OBO ontologies are for sharing and are resources for the entire community. For this reason, they must be available to all without any constraint or license on their use or redistribution. However, it is proper that their original source is always credited and that after any external alterations, they must never be redistributed under the same name or with the same identifiers.
  2. The ontology is in, or can be expressed in, a common shared syntax. This may be either the OBO syntax, extensions of this syntax, or OWL. The reason for this is that the same tools can then be usefully applied. This facilitates shared software implementations. This criterion is not met in all of the ontologies currently listed, but we are working with the ontology developers to have them available in a common OBO syntax.
  3. The ontologies possesses a unique identifier space within the OBO Foundry. The source of a term (i.e. class) from any ontology can be immediately identified by the prefix of the identifier of each term. It is, therefore, important that this prefix be unique.
  4. The ontology provider has procedures for identifying distinct successive versions.
  5. The ontology has a clearly specified and clearly delineated content. The ontology must be orthogonal to other ontologies already lodged within OBO. The major reason for this principle is to allow two different ontologies, for example anatomy and process, to be combined through additional relationships. These relationships could then be used to constrain when terms could be jointly applied to describe complementary (but distinguishable) perspectives on the same biological or medical entity. As a corollary to this, we would strive for community acceptance of a single ontology for one domain, rather than encouraging rivalry between ontologies.
  6. The ontologies include textual definitions for all terms. Many biological and medical terms may be ambiguous, so terms should be defined so that their precise meaning within the context of a particular ontology is clear to a human reader.
  7. The ontology uses relations which are unambiguously defined following the pattern of definitions laid down in the OBO Relation Ontology.
  8. The ontology is well documented.
  9. The ontology has a plurality of independent users.
  10. The ontology will be developed collaboratively with other OBO Foundry members.

ResearchBlogging.orgI’ve been asking all my frolleagues what they think of these principles and have got some lively responses, including some here from Allyson Lister, Mélanie Courtot, Michel Dumontier and Frank Gibson. So what do you think? How could these guidelines be improved? Do you have any specific (and preferably constructive) criticisms of these ambitious (and worthy) goals? Be bold, be brave and be polite. Anything controversial or “off the record” you can email it to me… I’m all ears.

CC-licensed picture above of the Old Smithy (pub) by Loop Oh. Inspired by Michael Ashburner‘s standing OBO joke (Ontolojoke) which goes something like this: Because Barry Smith is one of the leaders of OBO, should the project be called the OBO Smithy or the OBO Foundry? 🙂


  1. Noy, N., Shah, N., Whetzel, P., Dai, B., Dorf, M., Griffith, N., Jonquet, C., Rubin, D., Storey, M., Chute, C., & Musen, M. (2009). BioPortal: ontologies and integrated data resources at the click of a mouse Nucleic Acids Research DOI: 10.1093/nar/gkp440
  2. Côté, R., Jones, P., Apweiler, R., & Hermjakob, H. (2006). The Ontology Lookup Service, a lightweight cross-platform tool for controlled vocabulary queries BMC Bioinformatics, 7 (1) DOI: 10.1186/1471-2105-7-97
  3. Smith, B., Ashburner, M., Rosse, C., Bard, J., Bug, W., Ceusters, W., Goldberg, L., Eilbeck, K., Ireland, A., Mungall, C., Leontis, N., Rocca-Serra, P., Ruttenberg, A., Sansone, S., Scheuermann, R., Shah, N., Whetzel, P., & Lewis, S. (2007). The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration Nature Biotechnology, 25 (11), 1251-1255 DOI: 10.1038/nbt1346
  4. Smith, B., Ceusters, W., Klagges, B., Köhler, J., Kumar, A., Lomax, J., Mungall, C., Neuhaus, F., Rector, A., & Rosse, C. (2005). Relations in biomedical ontologies Genome Biology, 6 (5) DOI: 10.1186/gb-2005-6-5-r46
  5. Bada, M., & Hunter, L. (2008). Identification of OBO nonalignments and its implications for OBO enrichment Bioinformatics, 24 (12), 1448-1455 DOI: 10.1093/bioinformatics/btn194

April 17, 2009

The Unreasonable Effectiveness of Google

GoogleVia the Official Google Research Blog at the University of Google, Alon Halevy, Peter Norvig and Fernando Pereira have published an interesting expert opinion piece in the  March/April 2009 edition of IEEE Intelligent Systems: computer.org/intelligent. The paper talks about embracing complexity and making use of the “the unreasonable effectiveness of data” [1] drawing analogies with the “unreasonable effectiveness of mathematics” [2]. There is plenty to agree and disagree with in this provocative article which makes it an entertaining read. So what can we learn from those expert Googlers in the Googleplex? (more…)

October 14, 2008

Open Access Day: Why It Matters

Open Access Day 14th October 2008Today, Tuesday the 14th of October 2008, is Open Access Day. Like many others, this blog post is joining in by describing why Open Access matters – from a personal point of view. According to the wikipedia article Open Access (OA) is “free, immediate, permanent, full-text, online access, for any user, web-wide, to digital scientific and scholarly material, primarily research articles published in peer-reviewed journals. OA means that any individual user, anywhere, who has access to the Internet, may link, read, download, store, print-off, use, and data-mine the digital content of that article. An OA article usually has limited copyright and licensing restrictions.” What does all this mean and why does it matter? Well, in four question-and-answer points, here goes… (more…)

March 19, 2008

Genomes to Systems 2008: Day Two

Space Travel and Genomics in SpaceGenomes to Systems is a biannual conference held in Manchester covering the latest post-genome developments. Here are some brief and incomplete notes on some of the speakers and topics from day two of the 2008 conference. (more…)

May 31, 2007

Google Metabolic Maps

Google in the Palm of my HandThese days, new Google products and code seem to appear on a weekly basis. Take, for example, Google Gears which takes advantage of SQLite, mentioned on nodalpoint recently. They certainly don’t hang about at the Googleplex in Mountain View, California. Wouldn’t it be great if Google applied some of that engineering expertise and agility to science and bioinformatics? Just imagine: we could have Google Metabolic Maps, a virtual globe of the cell for scientists everywhere…

Scientists have been drawing metabolic maps for a very long time, but unfortunately when it comes to charting and understanding metabolic pathways, we’re still at the “here be dragons” stage of bio-cartography. I’m obviously not the first person to dream of this, but imagine maps of metabolic pathways looked more like Google Earth or Google Maps, than the old fashioned style maps, many life scientists will be familiar with. Now imagine just a little more, that these maps weren’t just available on conventional screens, but we’re given the Minority Report treatment, courtesy of Mr Bill Gates and his wizzy surface magic at Microsoft. Wouldn’t that be great? Metabolic maps on an interactive tabletop computer. Just like Tom Cruise in the movies, we’d be able to effortlessly swish around metabolism (or the metabolome / proteome / genome / [insert-your-favourite]ome). Imagine if it was all open-source too, no boundaries, no passports…

Now, you may say that I’m a dreamer, but I’m not the only one [1,2,3].


  1. Zhenjun Hu, Joe Mellor, Jie Wu, Minoru Kanehisa, Joshua M. Stuart and Charles DeLisi (2007) Towards zoomable multidimensional maps of the cell Nature biotechnology 25 (5), 547-54. DOI:10.1038/nbt1304
  2. Hiroaki Kitano, Akira Funahashi, Yukiko Matuoka and Kanae Oda (2005) Using process diagrams for the graphical representation of biological networks Nature biotechnology 23 (8), 961-6. DOI:10.1038/nbt1111
  3. John Lennon and Yoko Ono (1971) Imagine
  4. this post originally published on nodalpoint with comments

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