The UCD Cancer Data lab are currently looking to recruit computational biology postdocs. We are a supportive and collaborative interdisciplinary research group based in the Conway Institute in University College Dublin. We are broadly interested in understanding how mutations in cancer alter molecular interaction networks and in identifying ways to target these alterations therapeutically. We have a particular interest in identifying genetic interactions in cancer and understanding how they influence tumour genome evolution. You can read more about areas of specific research interest here.
Are you an ambitious MSc or PhD student seeking a challenge at the forefront of genomics, computational biology and RNA therapeutics?
We are looking for a highly motivated and enthusiastic individual to study the process of inflammation. In particular, the selected candidate will investigate the role of intracellular immune receptors in shaping immune responses under physiological and pathological conditions, such as chronic inflammatory diseases. These studies will collectively advance our understanding of inflammatory disorders and improve patients’ care.
Background Gene co-expression networks have been used to define prognostic gene signatures and centrally connected genes as therapeutic targets in cancer. However, most of these studies are purely descriptive, not fully exploiting the wealth of information hidden in the constructed networks to investigate specific biological hypotheses. Moreover, networks have never been compared across breast cancer (BC) subtypes, despite the potential usefulness of such an approach to understand how specific molecular features are established and regulated. Hypothesis We posited that reconstructing BC transcriptional networks could allow us to address biological questions related both to BC in general and to specific BC sub-types. Allowing to formulate testable hypotheses about how biologically/clinically relevant gene expression patterns are established and maintained in specific BC sub-types, such an approach could be exploited to identify and validate potential key regulatory genes, developing them into therapeutic targets. Aims We have implemented a workflow based on the analysis of the METABRIC BC gene expression dataset, which we have validated both based on database analyses and on experimental approaches. We aim at confirming its validity as a tool to dissect molecular pathways linked to BC aggressiveness, particularly basal-like BC for which a targeted treatment is still lacking, identifying key regulatory genes amenable to therapeutic intervention. AIM 1) Discovering how clinically relevant BC gene expression patterns are established by identifying transcriptional regulatory hubs and validating them as therapeutic targets. AIM2 ) Identifying drugs able to target relevant co-expression modules via a drug repositioning approach. AIM 3) Identifying central regulators of specific stromal signatures. AIM 4) demonstrating siRNA-mediated in vivo target ability of identified transcriptional regulators
Applications are OPEN for the PhD program in Molecular Biomedicine of the University of Trieste (Dottorato in Biomedicina Molecolare dell'Università di Trieste)