Assessing the impact of alternative splicing in thyroid cancer

• Autor(a) principal: Luís Filipe Correia Cleto
• Data de Publicação: 2016
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://repositorio-aberto.up.pt/handle/10216/85702
• topic: Ciências da computação e da informação; Computer and information sciences

All over the world there are millions of people affected by cancer. There are several possible causes for this disease, some of them being a genomic origin. While there are many alterations in cancer cells that distinguish them from healthy ones, there is also an abundance of aberrant mRNA transcripts in cancerous cells. These aberrant transcripts might lead to changes in the synthesized proteins which, in turn, will confer new, and possibly devastating, properties to the affected cell. One possible source of this defective mRNA is abnormal gene splicing.The advent of next-generation sequencing techniques has revolutionized the field of molecular biology in the past few years and brought many new approaches for cancer research. The goal of this thesis is to make use of these novel techniques, namely RNA-seq, in order to create a tool capable of detecting events of aberrant alternative splicing and assessing their impact on a cell or an organism's proteome.However, current tools of this type are commonly complex to use, require powerful computational resources and also need the user to be familiar with programming or other concepts from the field of informatics, which is often not the case for geneticists or molecular biologists. As such, this project also focuses on enabling these researchers to use the aforementioned tools through the creation of a distributed system which provides the computational resources necessary for an RNA-seq pipeline as well as a web interface to facilitate configuring and running experiments on this pipeline.Lastly, the thesis proposal is evaluated on real data from the ENCODE project.