आईएसएसएन: 2090-4924
Fernando Limoeiro, Maria Fernanda Ribeiro Dias, Vinicius Santos de Pontes and Manuela Leal da Silva
In recent years, the development of high-throughput technologies for obtaining sequence data leveraged the possibility of analysis of protein data in silico. However, when it comes to viral polyprotein interaction studies, there is a gap in the representation of those proteins, given their size and length. To prepare for studies using state-of-the-art techniques, such as Machine Learning, a good representation of such proteins is a must. We present an alternative to this problem, implementing a fragmentation and modeling protocol to prepare those polyproteins in the form of peptide fragments. Such procedure is made by several scripts, implemented together on the workflow we call PolyPRep.