Phylogenetic tree reconciliation is a general framework for investigating the mutual influence between related biological systems. It has many applications in medicine and biology.
Even if it is widely exploited, there are many cases in which it is necessary to slightly tune the definition, in order to apply it. For example, there are cases in which the involved phylogenetic trees are not binary, cases in which gene transfers are allowed and cases in which they are forbidden, cases in which the structure representing the first system is not a tree anymore and becomes a network, ans cases in which the structure corresponding to the second system can have cycles.
In this project, we would like to deeply study phylogenetic tree reconciliations, exactly delimiting the application scenarios, surveying the generalizations known in the literature and proposing new possibilities of use.
We are convinced that a systematic organization among all the alternative and very similar definitions would be strongly useful to the community.
Moreover, new solutions aiming at making the models more adherent to the real life will be very useful for a correct application of algorithms.
The listed references (many of them very recent) should make clear that the problems we are going to approach are very topical.
Researchers in medicine take a great advantage from the study of reconciliations, since they clarify how viruses accomplishes their evolution on the basis of the modifications of the host organisms and show how they can "jump" from one species to another.
Moreover, biologists are very interested in the full comprehension of reconciliations because, although the evolution of species and their genes are closely related, they are not the same, due to a number of evolutionary processes which affect genes but not species (or vice-versa); studying the discrepancy between these two histories can yield much information about the evolutionary events which have shaped the tree of life.
We are convinced that a systematic organization among all the alternative and very similar definitions of reconciliations would be strongly useful to the community.
Furthermore, the exact delimitation of application feasibility we would like to delineate will make much easier for researchers to decide whether the reconciliation approach can be efficiently used or not.
Aware that bioinformatics and computer science applied to medicine have a lot in common, the members of this research group are within the Interdepartment Center S.T.I.T.C.H. (Sapienza information-based Technology InnovaTion Center for Health https://web.uniroma1.it/stitch/). This is for us a great opportunity to interact with researchers in medicine, who will provide us some interesting real life applicative scenarios to lead our experiments.
We finally observe that this research group has variegated competences, from theoretical computer science to algorithmics, from machine learning to logic, from paralle systems to wireless networks.
This is a richness, because we will have the opportunity to apply the techniques used in our original scientific fields to the subject of this project and will be able to retrieve the many results present in the literature that are hidden under several names and contexts and have been designed to solve completely different problems.
We have already experienced that this approach of meeting all togehter on a problem, each coming from a different field of computer science, is successfull and leads to strong results.