There will be a keynote talk by Marco Antoniotti (Dipartimento di Informatica Sistemistica e Comunicazione, Università degli Studi di Milano-Bicocca, Italy) at the main track of the symposium:

The right mix: Common Lisp in Bioinformatics, Systems Biology and in the Larger Semantic Network World

Working with CL nowadays is a choice based on a long programming experience (and/or lazyness and or/inertia). Many times this choice is hard because of a number of entrenched limitations of the CL (or simply Lispy) world: lack of many agreed upon, modern and portable extensions, and lack of new programmers being the most visible. Yet, this talk will argue that the situation has improved and that CL is even more "the right mix" for many researchers in the sciences, and, in particular, in the fields I have been working for a few years.

For CL, being the right mix comes from the strenghts of the standard and of the nature itself of the language. The ability to build code with more than decent numerical performance and the ability to morph in any (declarative) DSL are the key characteristics that make CL the right tool for many of the sciences.

Bioinformatics and Systems Biology are two relatively broad terms that serve to describe a number of system and algorithmic solutions to problems stemming from the needs of biologists and clinicians. Very roughly speaking, these terms cover the range from "sequence analysis" (DNA, RNA, and protein) to statistical interpretation of "high throughput experiments" (micro-array and new ion-trap protein studies), to model simulation and testing of metabolic, regulatory and signaling pathways. The numerical capabilities of CL do fit well with these problems. On the other end, these problems require the support of many data manipulation, sharing and, above all, description systems that nowadays are continuously crystallized in different "ontologies" and "controlled vocabularies" which are then rendered in XML/RDF. CL systems for solving such "representation" task predate all of these efforts and it should come to no surprise that Lisp-based systems provide a very good platform to build more expressive DSL's capable of improving the inference capabilities of the tools needed by biologists and physicians.

At this point in time, the "basic library" situation for CL is good enough to support its use in the field. CLSQL and XML parsing libraries are the basis for such use. Numerical libraries abound, as well as web development frameworks. Writing inference engines and DSL's has never been a problem for CL programmers and researchers. It is therefore a well founded conclusion that CL is a "well mixed solution" for Bioinformatics and Systems Biology, life, universe and everything else. It just needs to be put together.

Marco Antoniotti is an Associate Professor at the Dipartimento di Informatica Sistemistica e Comunicazione, Università degli Studi di Milano-Bicocca, Italy. His interests concentrate in the field of Computational and Systems Biology. He is the author or co-author of several papers and software systems - SHIFT from UC Berkeley, Jester from PARADES, Simpathica and GOALIE from NYU - and co-authored three patents in the field of Genomics Optical Mapping. He received his PhD from New York University in 1995.