Jermey, I looked at the Lisp article you cited, I have to say I don't
agree. You yourself are quite at home with computing as are many here on
this group and naturally a Lisp approach is very attractive to computer
folk, however in the biology community it is a different matter. Most
biologists are not computer savy enough to be able to takle Lisp or most
computer languages for that matter, and frankly I don't think they
should have to either. They have enough on their plate as it is without
making them jump through hoops to get simple jobs done. Matlab is about
the limit and even then it is a small struggle to teach people how to
From: Jeremy Zucker [mailto:email@example.com]
Sent: Monday, July 11, 2005 12:03 AM
To: SBML Discussion List; firstname.lastname@example.org
Subject: Re: [sbml-discuss] Little b
Funny you should ask. I met with Aneil Mallavarapu last week to
discuss writing the SBML module for little b. We have the choice of
Martin Ginkel's libsbml lisp bindings and Marco Antoniotti's pure lisp
implementation. The export utility will be easy. What will be harder
is inferring what kinetic rate law assumptions were made when importing
SBML. We have some ideas on how to do this, and we are paying close
attention to the recent discussions on controlled vocabularies for
kinetic rate laws.
As for why lisp is useful for writing biological programming languages,
I think Jeff Shrager said it pretty well:
Aneil is a pragmatist. He started out trying to implement little b in
conventional programming languages but kept running into limitations
that eventually drove him to lisp.
But I'll let him speak for himself.
On Sun, 2005-07-10 at 17:14 -0400, email@example.com
> This is from John Russell's column in Bio-IT World last week.
> Two questions: Jeremy, do these high profile systems biologists know
> about SBML and the array of solvers that support it? Everyone else,
> why LISP?
> Harvard Tackles Systems Biology
> Towards the end of this summer, Jeremy Gunawardena and Aneil
> Mallavarapu of the Virtual Cell Program at Harvard Medical School's
> Department of Systems Biology expect to unleash b -- pronounced
> "little b" -- a new open-source computer language they hope will
> energize the biological modeling community as nothing has before.
> Today, a handful of companies and academic groups are building
> computational models of disease and biological pathways. To a
> considerable extent, these scattered efforts remain in their infancy
> (although modeling has recently gained traction inside a few
> biopharmas). Moreover, the companies charge for their services and
> tools and have a vested interest in controlling their proprietary
> technology. On balance, there has been little synergy between these
> isolated pockets of progress.
> Imagine instead a biologist-friendly language designed specifically to
> encapsulate biological knowledge and constantly pounded on and
> improved upon by an open-source community. Add to this vision a
> growing library of models (and model fragments) written in b and
> contributed by researchers worldwide for free use by other
> researchers. Based on list processing (LISP), b is designed to be
> modular, emphasizing the reusability of modules and a Lego-like
> approach to model building.
> Currently, b focuses on biochemical modeling using ordinary
> differential equations. However, Mallavarapu says, "We want to expand
> to describe other types of models like partial differential equations,
> and we're working on what it will take to write stochastic models."
> It's not a great leap to conceive of a GenBank for computational
> models that researchers could contribute to and draw from. Imagine the
> interesting and productive in silico research that an army of modelers
> might undertake.
> This is a grand vision for a language with such a diminutive name, and
> it is one of the first concrete projects emerging from Harvard's
> ambitious foray into systems biology. The department is a little more
> than a year old, has enrolled nine students in its Ph.D. program, and
> has assembled an impressive faculty led by chair Marc Kirschner,
> deputy chair Timothy Mitchison, and Lewis Cantley.
> They were "the gang of three who believed sufficiently that something
> new was happening to come together and make this [department] happen,"
> says Gunawardena, who is the director of the Virtual Cell Program.
> Language Barriers
> A self-professed "mathematician who fell from grace," Gunawardena had
> stints in academia and industry, including a long stay at Hewlett-
> Packard doing industrial research. While at HP, he caught the biology
> bug and moved to Harvard's Bauer Center for Genomic Research. That was
> his first opportunity, he says, "to actually live among biologists and
> understand what was going on. Pretty much everything I thought before
> I came [to Bauer] turned out to be...modified substantially." When
> ideas for the new systems biology department bubbled up, he was
> invited to join.
> Mallavarapu is a cell biologist and biochemist by training. He took
> his Ph.D. with Mitchison at the University of California, San
> Francisco, working on photomarking technologies to visualize
> cytoskeletal dynamics. During the past few years, Mallavarapu worked
> at Millennium Pharmaceuticals developing technology, writing software,
> and thinking about what is now b. He credits conversations with
> Gunawardena for stoking his desire to make the language a reality, and
> he recently joined the Virtual Cell Program as a research scientist.
> These guys have great jobs!
> Certainly, tricky issues remain. Defining b so that it can be easily
> compiled on various LISP platforms isn't trivial. Attracting an early
> adopter community will be important. Writing an easy-to-use graphical
> user interface is another priority, as is getting models and modeling
> techniques published in peer-reviewed literature.
> "I think [it's] the classical catch-22 problem: Until there's a
> community of people speaking [a language], why would you want to learn
> it?" Gunawardena says. "I'm very keen on little b in the context of
> some courses that we'll be teaching [and] think that's going to be a
> very influential early adopter community. I think it's likely that
> some of our colleagues at the medical school and also at MIT are very
> It will be interesting to watch how big little b becomes.