Today we have the technology to identify almost any genetic alteration in cancer genomes. However, we still lack efficient bioinformatic tools that can help us extract biologically important mutations from background noise, both in clinical diagnostics and basic science.
Objectives:
- Develop a user-friendly and accessible application that enables data integration, matching mutations identified in tumor genomes with information available in literature and relevant databases.
- Automatic connection of genetic information from public sources to specific genetic changes found in the tumor samples.
- Integration of input formatting for the app.
Expected Results
This project will integrate genomic and transcriptomic information to extract previously reported and novel genetic alterations. It will be designed for medical staff and biologists without the need for advanced bioinformatics skills and can thereby be used without previous knowledge in bioinformatics. The connection of genetic information from public sources to specific genetic changes will remove the need for users to have prior knowledge or manually sift through data, which can be overwhelming and biased.
Project requirement
The project is set at the Division of Clinical Genetics at Lund University, in a unique multidisciplinary environment, fusing biology, bioinformatics, and medicine. We are looking for an ambitious student in data science, machine learning, computational science, bioinformatics, or a related field. You must have experience in programming languages such as Python, R, Java and/or other, as well as familiarity with bioinformatics tools and databases.
Contact
Valeria Difilippo, valeria.difilippo@med.lu.se