The con nuous muta ons that take place in the gene c material of a certain virus constantly trigger the crea on of new types of the virus. Because of these muta ons, the new virus types obtain features that differen ate the severity of their infec on (e.g., the human papillomavirus which appears in both oncogenic and non-oncogenic types). In these cases the iden fica on of the exact type(s) of a virus that have infected a pa ent, namely the task of typing the virus, has acquired great importance with regards to the efficient treatment of its infec on.Due to the importance of virus typing, several molecular biology methods that aim at efficiently discrimina ng among the various types of a virus based on their genotypic differences have been developed during the last decades. Among them, the molecular method called PCR-RFLP gel electrophoresis is currently employed widely over the world. However, the procedure of virus typing via the discussed method remains, in contrast to the other methods, heavily manual. This shortcoming of the PCR-RFLP method with respect to automa on makes the conven onal typing protocol of the method error-prone -especially in complex cases of mul ple infec ons -and laborious for the molecular biologists who execute it.The aforemen oned issues of the PCR-RFLP method can be tackled with the help of digital signal processing techniques along with the es ma on and decision theory. For this purpose, the present thesis develops a series of novel computa onal methodologies that undertake the en re task of virus typing via the PCR-RFLP method in a consistent and effec ve manner.In order to ensure the correctness of the typing decisions, the proposed methodologies employ addi onal informa on that has been ignored by the conven onal typing protocol, namely the concentra on of the viral gene c material. The introduc on of a factual observa on model of the PCR-RFLP examina on product sets the ground for the proposed methodologies to employ the addi onal informa on. On top of this model, the present thesis develops an integrated computa onal typing methodology (the sta c methodology), which analyzes the examina on product and reaches typing decisions. The performance of the sta c methodology is evaluated thoroughly through theore c inves ga ons and experiments on real as well as simulated typing data. Moreover, the viii sta c methodology is implemented in its en rety as a graphical so ware applica on.Apart from the sta c methodology, the present thesis introduces also the dynamic typing methodology, which is capable of making typing decisions while the PCR-RFLP examina on is s ll in progress. Dynamic typing is achieved through the establishment of communica on between the previously isolated phases of the conven onal typing protocol and it tackles several open issues associated with the sta c approach. An integrated hardware-so ware system is designed in order to implement the dynamic methodology. The feasibility of the dynamic typing approach is validated through an experiment that emulates the opera o...