Re: Systems Biology Task Force Kick-Off - tomorrow (Feb 22) at 11AM EDT

Dear All,

[nothing to do with the current discussion but... ]
I've created a google group for discussing Systems Biology Task Force
issues - for now, anyone can join, so please feel free to join at
http://groups.google.com/group/systems_biology_w3c

Best,
Lena



On Fri, Feb 24, 2012 at 8:28 PM, Michael Miller
<mmiller@systemsbiology.org>wrote:

> hi all,
>
> i definitely echo your thoughts, oliver. and there is, in some cases, the
> raw and processed data from gene expression (microarray and ngs),
> proteomics (ms and ms/ms) and so on which the paper will reference as
> deposited at some public repository.  the BioRDF group has shown how this
> can be converted into RDF.
>
> cheers,
> michael
>
> Michael Miller
> Software Engineer
> Institute for Systems Biology
>
> > -----Original Message-----
> > From: Oliver Ruebenacker [mailto:curoli@gmail.com]
> > Sent: Friday, February 24, 2012 12:14 PM
> > To: Bob Futrelle
> > Cc: Waard, Anita de A (ELS-NYC); Helena Deus; public-semweb-lifesci
> > Subject: Re: Systems Biology Task Force Kick-Off - tomorrow (Feb 22) at
> > 11AM EDT
> >
> >      Hello Bob, Anita, All,
> >
> >   I'm not claiming that numbers determine the content of a paper
> > entirely. But I do claim they play a central role. I guess it is not
> > entirely impossible to publish a paper with no numbers, but it appears
> > to be extremely rare. I would estimate the fraction of biology papers
> > with no numbers to be less than one percent.
> >
> >   Images are numbers - radiation intensity measured as a function of
> > space. Most biologists I know would use images to estimate the amounts
> > or concentrations of the substances that cause the radiation.
> >
> >   I suppose it is possible to derive conclusions without numbers. But
> > in my experience it is extremely rare. Who would report A grows faster
> > than B without reporting, by how much? How can you even talk about
> > chemical compositions without providing any numbers about what these
> > compositions are?
> >
> >   If you have data plots, that means you have lots of numbers. Most
> > biologists I know would try to fit the data to a mathematical model.
> > Who would report that graph A has a bigger slope than graph B without
> > reporting, what those slopes are?
> >
> >   Certainly, papers contain other things besides data. It is possible
> > that two different authors, given the same data, arrive at different
> > conclusions. But why should I care about things not derived from data?
> > If it is about established knowledge, I don't need to get it from that
> > paper - I can get it from somewhere else. And if some statement is
> > neither derived from the data nor established knowledge, why would I
> > believe it?
> >
> >      Take care
> >      Oliver
> >
> > On Fri, Feb 24, 2012 at 2:24 PM, Bob Futrelle <bob.futrelle@gmail.com>
> > wrote:
> > > Statements are based on a wide variety of things.  Statements are
> > produced
> > > by author/experimenters who may describe and evaluate gels and other
> > images
> > > without ever reducing them to numbers. Statements often compare  (not
> > > numerically) growth, morphology, chemical composition, to those
> aspects
> > > found in other portions of an experiment or reported in other papers.
>  A
> > > paper will often include data plots, but the authors may report
> particular
> > > characteristics of the data behavior or correlation in the plots by
> looking
> > > at the plots, not reducing them to numbers.
> > >
> > > You cannot discard the authors' evaluations and hope to reach the
> > > conclusions that those humans have by some analysis of the numbers.
> > >
> > > Your system for doing that would have to include the world knowledge
> of
> > the
> > > authors.  In other words, these problems are AI-Complete, as are so
> many
> > > important, complex, and interesting problems in the real (biological)
> world.
> > >
> > > Anita's comments that followed mine are in the same spirit.
> > >
> > >   - Bob
> > >
> > >
> > > On Fri, Feb 24, 2012 at 2:14 PM, Oliver Ruebenacker <curoli@gmail.com>
> > > wrote:
> > >>
> > >>     Hello Bob,
> > >>
> > >>  There are many statements which contain no numbers. But isn't the
> > >> evidence that they are true usually based on numbers?
> > >>
> > >>  My suggestion is to structure quantitative data based on the
> > >> statements for which this data is used as evidence.
> > >>
> > >>     Take care
> > >>     Oliver
> > >>
> > >> On Fri, Feb 24, 2012 at 1:59 PM, Bob Futrelle
> <bob.futrelle@gmail.com>
> > >> wrote:
> > >> > A great deal of the content of papers is not about numbers, but
> > >> > statements
> > >> > intertwined with propositional attitudes. Good evidence for this is
> in
> > >> > the
> > >> > use of hedging.  See,
> > >> >
> > >> > Hyland, K., Hedging in scientific research articles. Pragmatics &
> > >> > beyond,1998, Amsterdam ; Philadelphia: John Benjamins Pub. Co. ix,
> 307
> > >> > p.
> > >> >
> > >> >
> > >> >  - Bob Futrelle
> > >> >    BioNLP.org
> > >> >
> > >> > On Fri, Feb 24, 2012 at 1:46 PM, Oliver Ruebenacker
> <curoli@gmail.com>
> > >> > wrote:
> > >> >>
> > >> >>     Hello Anita, All,
> > >> >>
> > >> >>  I'm mostly interested in numbers. Presumably, these statements
> have
> > >> >> been derived from numbers that can be found in these papers. The
> > >> >> challenge is to classify numbers and group them into systems and
> > >> >> states. Could your epistemic model help do that?
> > >> >>
> > >> >>     Take care
> > >> >>     Oliver
> > >> >>
> > >> >> On Fri, Feb 24, 2012 at 12:15 PM, Waard, Anita de A (ELS-NYC)
> > >> >> <A.dewaard@elsevier.com> wrote:
> > >> >> > All,
> > >> >> >
> > >> >> > I was struck by the phrase 'turning biological knowledge into
> > >> >> > mathematical models' and wondering if anyone is interested to
> > model
> > >> >> > 'epistemic information' in biology articles, added to the
> knowledge
> > >> >> > of the
> > >> >> > type that Oliver mentioned?
> > >> >> >
> > >> >> > In particular I am interested in modelling clauses such as 1 a.,
> 2
> > >> >> > a., 3
> > >> >> > a., and 3.b in the sentences below - I have a model to classify
> these
> > >> >> > and
> > >> >> > would like to add this 'knowledge attribution' layer to existing
> > >> >> > representations of triples in papers.
> > >> >> >
> > >> >> > 1 a. These studies have shown that
> > >> >> > 1.b. the 5' untranslated region (5'UTR) can be complex
> > >> >> >
> > >> >> > vs.
> > >> >> >
> > >> >> > 2. a. It has been reported that
> > >> >> > 2. b. 5' untranslated exons, and sometimes introns, can regulate
> the
> > >> >> > expression of genes in two different ways.
> > >> >> >
> > >> >> > vs.
> > >> >> >
> > >> >> > 3. a. Thus, our analysis revealed areas of active chromatin
> > >> >> > remodeling
> > >> >> > in the vicinity of exon 1
> > >> >> > 3. b. suggesting that
> > >> >> > 3. c. this area may be important for CCR3 transcription.
> > >> >> >
> > >> >> > Is this part of the remit of this group and/or is anyone
> interested
> > >> >> > in
> > >> >> > collaborating on this topic?
> > >> >> >
> > >> >> > Thanks,
> > >> >> > Best,
> > >> >> >
> > >> >> > - Anita.
> > >> >> >
> > >> >> > Anita de Waard
> > >> >> > Disruptive Technologies Director, Elsevier Labs
> > >> >> > http://elsatglabs.com/labs/anita/
> > >> >> > a.dewaard@elsevier.com
> > >> >> >
> > >> >> >
> > >> >> >
> > >> >> > -----Original Message-----
> > >> >> > From: Oliver Ruebenacker [mailto:curoli@gmail.com]
> > >> >> > Sent: Fri 2/24/2012 11:55
> > >> >> > To: Helena Deus; public-semweb-lifesci
> > >> >> > Subject: Re: Systems Biology Task Force Kick-Off - tomorrow (Feb
> 22)
> > >> >> > at
> > >> >> > 11AM EDT
> > >> >> >
> > >> >> >
> > >> >> >     Hello Helena, All,
> > >> >> >
> > >> >> >  I'm interested in joining the Systems Biology Taskforce. Sorry
> I
> > >> >> > could not make the initial call. My interest is turning
> biological
> > >> >> > knowledge into mathematical models, automatically. A brief
> > >> >> > description
> > >> >> > is below.
> > >> >> >
> > >> >> >  Thanks!
> > >> >> >
> > >> >> >     Take care
> > >> >> >     Oliver
> > >> >> >
> > >> >> >  Living organisms are so enormously complex that we need
> computer
> > >> >> > simulations to understand the consequences of their vast
> > biochemical
> > >> >> > reaction networks. As we uncover an increasing part of these
> > >> >> > networks,
> > >> >> > our established knowledge is increasingly stored in free web
> > >> >> > databases
> > >> >> > and available for query and download in machine-readable
> formats,
> > >> >> > especially in the RDF/OWL-based community standard Biological
> > >> >> > Pathways
> > >> >> > Exchange (BioPAX) [1]. The available data is massive and
> growing,
> > >> >> > e.g.
> > >> >> > Pathway Commons [2] stores 1,700 pathways, 414 organisms,
> > 440,000
> > >> >> > interactions and 86,000 substances. This data is fully linked
> with
> > >> >> > open controlled terminologies such as gene ontology (e.g.
> > anatomical
> > >> >> > features) [3] and other free online databases such as ChEBI
> > >> >> > (chemicals) [4], KEGG (genes a.o.) [5], UniProt (proteins) [6]
> and
> > >> >> > PubMed (publications) [7].
> > >> >> >
> > >> >> >  Automatic use of this knowledge for computer simulations of
> > >> >> > biological organisms has been an ongoing challenge [8,9,10].
> Now,
> > >> >> > Systems Biology Pathway Exchange (SBPAX) [11], a BioPAX
> > extension,
> > >> >> > allows the inclusion of quantitative data and systems biology
> terms,
> > >> >> > especially the Systems Biology Ontology (SBO) [12]. SBPAX
> support
> > has
> > >> >> > been implemented by the Virtual Cell [13], Signaling Gateway
> > Molecule
> > >> >> > Pages [14] and System for the Analysis of Biochemical Pathways -
> > >> >> > Reaction Kinetics (SABIO-RK) [15]. For the first time, a
> mathematical
> > >> >> > model can be automatically built and fully annotated from a
> pathway
> > >> >> > of
> > >> >> > interest.
> > >> >> >
> > >> >> >  Citations:
> > >> >> >
> > >> >> >  [1] Biological Pathway Exchange (BioPAX), www.biopax.org
> > >> >> >  [2] Pathway Commons, www.pathwaycommons.org
> > >> >> >  [3] Gene Ontology (GO), www.geneontology.org/
> > >> >> >  [4] Chemical Entities of Biological Interest (ChEBI),
> > >> >> > www.ebi.ac.uk/chebi/
> > >> >> >  [5] Kyoto Encyclopedia of Genes and Genomes (KEGG),
> > >> >> > wwww.genome.jp/kegg/
> > >> >> >  [6] UniProt, www.uniprot.org
> > >> >> >  [7] PubMed, www.ncbi.nlm.nih.gov/pubmed/
> > >> >> >  [8] Modeling without Borders: Creating and Annotating VCell
> Models
> > >> >> > Using the Web, Michael L. Blinov, Oliver Ruebenacker, James C.
> > Schaff
> > >> >> > and Ion I. Moraru,  Lecture Notes in Computer Science, 2010,
> Volume
> > >> >> > 6053 (2010).
> > >> >> >  [9] Using views of Systems Biology Cloud: application for model
> > >> >> > building, Oliver Ruebenacker, Michael Blinov, Theory in
> Biosciences,
> > >> >> > Volume 130, Number 1, 45-54 (2010).
> > >> >> >  [10] Integrating BioPAX pathway knowledge with SBML models,
> > Michael
> > >> >> > L Blinov, Oliver Ruebenacker, Ion I Moraru, IET Syst. Biol.,
> 2009,
> > >> >> > Vol. 3, Iss. 5, pp. 317-328 (2009).
> > >> >> >  [11] Systems Biology Pathway Exchange (SBPAX), www.sbpax.org
> > >> >> >  [12] Systems Biology Ontology, www.ebi.ac.uk/sbo/main/
> > >> >> >  [13] Virtual Cell, http://vcell.org
> > >> >> >  [14] Signaling Gateway Molecule Pages,
> > >> >> > www.signaling-gateway.org/molecule/
> > >> >> >  [15] System for the Analysis of Biological Pathways - Reaction
> > >> >> > Kinetics (SABIO-RK), http://sabio.villa-bosch.de/
> > >> >> >
> > >> >> > On Tue, Feb 21, 2012 at 4:32 PM, Helena Deus
> > <helenadeus@gmail.com>
> > >> >> > wrote:
> > >> >> >> Dear All,
> > >> >> >>
> > >> >> >> Please join me tomorrow for the kick-off telco of the Systems
> > >> >> >> Biology
> > >> >> >> Task
> > >> >> >> Force. Systems Biology is about looking at biological systems
> from
> > >> >> >> an
> > >> >> >> integrated perspective and to use that perspective to
> understand
> > >> >> >> disease. We
> > >> >> >> will be discussing the general goals, strategy and structure of
> the
> > >> >> >> task
> > >> >> >> force.
> > >> >> >>
> > >> >> >> Please see http://www.w3.org/wiki/HCLSIG/SysBio for an initial
> > >> >> >> motivation,
> > >> >> >> and description, of what this task will be focused on (with due
> > >> >> >> flexibility
> > >> >> >> according to participants input).
> > >> >> >>
> > >> >> >>
> > >> >> >> * Date of Call: Tuesday February 21, 2012
> > >> >> >> * Time of Call: 11:00am Eastern Daylight Time (EDT)
> > >> >> >> * Dial-In #: +1.617.761.6200 (Cambridge, MA)
> > >> >> >> * [Note: limited access to European dial in numbers below]
> > >> >> >> * Dial-In #: +33.4.26.46.79.03 (Nice, France)
> > >> >> >> * Dial-In #: +44.203.318.0479 (Bristol, UK)
> > >> >> >> * Participant Access Code: 4257 ("HCLS").
> > >> >> >> * IRC Channel: irc.w3.org port 6665 channel #HCLS
> > >> >> >> For instant IRC access:
> > >> >> >> see [http://www.w3.org/Project/IRC/ W3C IRC page] for details,
> or
> > >> >> >> see [http://cgi.w3.org/member-bin/irc/irc.cgi Web IRC]), Quick
> > >> >> >> Start:
> > >> >> >> Click
> > >> >> >> on
> > >> >> >>
> > >> >> >>
> > >> >> >>
> > [http://www.mibbit.com/chat/?server=irc.w3.org:6665&channel=%23hcls mi
> > bbit]
> > >> >> >>
> > >> >> >> * Duration: ~1h
> > >> >> >> * Convener: Helena
> > >> >> >> * Scribe: TBD
> > >> >> >>
> > >> >> >> Kind regards,
> > >> >> >> Helena
> > >> >> >
> > >> >> >
> > >> >> >
> > >> >> > --
> > >> >> > Oliver Ruebenacker, Computational Cell Biologist
> > >> >> > Virtual Cell (http://vcell.org)
> > >> >> > SBPAX: Turning Bio Knowledge into Math Models
> > (http://www.sbpax.org)
> > >> >> > http://www.oliver.curiousworld.org
> > >> >> >
> > >> >> >
> > >> >> > Elsevier B.V. Registered Office: Radarweg 29, 1043 NX Amsterdam,
> > The
> > >> >> > Netherlands, Registration No. 33156677 (The Netherlands)
> > >> >> >
> > >> >>
> > >> >>
> > >> >>
> > >> >> --
> > >> >> Oliver Ruebenacker, Computational Cell Biologist
> > >> >> Virtual Cell (http://vcell.org)
> > >> >> SBPAX: Turning Bio Knowledge into Math Models
> > (http://www.sbpax.org)
> > >> >> http://www.oliver.curiousworld.org
> > >> >>
> > >> >
> > >>
> > >>
> > >>
> > >> --
> > >> Oliver Ruebenacker, Computational Cell Biologist
> > >> Virtual Cell (http://vcell.org)
> > >> SBPAX: Turning Bio Knowledge into Math Models (http://www.sbpax.org)
> > >> http://www.oliver.curiousworld.org
> > >
> > >
> >
> >
> >
> > --
> > Oliver Ruebenacker, Computational Cell Biologist
> > Virtual Cell (http://vcell.org)
> > SBPAX: Turning Bio Knowledge into Math Models (http://www.sbpax.org)
> > http://www.oliver.curiousworld.org
>



-- 
Helena F. Deus
Post-Doctoral Researcher at DERI/NUIG
http://lenadeus.info/