A major class of problems in computational biology is related to
infer repeated or common sequences and structures in biological data.
Given the considerable size of input data and the necessity of
a certain degree of approximation in this inference, these
studies require a strong
algorithmic expertise, and must be conducted in cooperation with
molecular biologists in order to be driven from the specific goal.
We also wrote a contribution on motifs inference in the
Applied Combinatorics on words volume of the Lothaire
series for Cambridge University Press ([15]).
A PhD student of our group is the co-authour of a book
aiming at bridging the gap between the computer and natural
sciences, by describing the core concepts behind computer modeling in way
accessible to natural scientists ([1]).
This group has also studied the computation of genomic distances,
and it has realised in the past a tool named PATRE
conceived for the inference of hystory of duplications in a
family of paralog genes. The tool was based on the notion
of Transformation Distance whose computation had resulted
the bootleneck of the method. ([14])
We have also investigated the problem of aligning sequences
with substitutions whose cost depends on the context, with
negative tractability results. ([6])
Our group includes a biologist that has recently created a company named ProteogenBio that is a spin-off of the University of Pisa. It is specialised in the enalysis and critical interpretation of raw biological data, offering services and assistance to modern molecular biology laboratories.