  We advocate here the use of computational logic for systems biology, as a
\emph{unified and safe} framework well suited for both modeling the dynamic
behaviour of biological systems, expressing properties of them, and verifying
these properties. The potential candidate logics should have a traditional
proof theoretic pedigree (including either induction, or a sequent calculus
presentation enjoying cut-elimination and focusing), and should come with
certified proof tools. Beyond providing a reliable framework, this allows the
correct encodings of our biological systems. % For systems biology in general
and biomedicine in particular, we have so far, for the modeling part, three
candidate logics: all based on linear logic. The studied properties and their
proofs are formalized in a very expressive (non linear) inductive logic: the
Calculus of Inductive Constructions (CIC). The examples we have considered so
far are relatively simple ones; however, all coming with formal semi-automatic
proofs in the Coq system, which implements CIC. In neuroscience, we are
directly using CIC and Coq, to model neurons and some simple neuronal circuits
and prove some of their dynamic properties. % In biomedicine, the study of
multi omic pathway interactions, together with clinical and electronic health
record data should help in drug discovery and disease diagnosis. Future work
includes using more automatic provers. This should enable us to specify and
study more realistic examples, and in the long term to provide a system for
disease diagnosis and therapy prognosis.
