LYH-P2 Identifying and visualising signatures of epigenetic mechanisms in cancer

Name of PIAsst Prof Li Yinghui
Email Addressliyh@ntu.edu.sg
Project TitleIdentifying and visualising signatures of epigenetic mechanisms in cancer
DescriptionMotivated MSc bioinformatics students are invited to apply to the LYH lab research immersion scheme (RIS). As the successful candidate, you will support the bioinformatics team in expanding statistical and visualisation solutions to highlight key changes in the epigenetic regulatory mechanisms (ERMs) underlying the progression of myeloma and lymphoma cancers. Your goal will be to facilitate the identification of trends and patterns from processed and integrated datasets containing valuable information on chromatin properties (ChIP-Seq, ATAC-Seq), gene transcription (RNA-Seq, GRO-Seq) and chromatin interactions (HiChip). First you will familiarise yourself with the biological context of the experiments and how the data they generate was processed. Subsequently you will then master how available methods and tools can be programmatically applied to identify statistically significant trends in the data as well as their visualisation. Depending on your aspirations you may then choose to focus on improving or expanding models, algorithms and dashboards with your own ideas in coordination with senior colleagues. In order for you to progress at a desirable pace you will be expected to have fluent Python or R skills as well as familiarity with bash and version control (Git). Experience with data science libraries such as scikit-learn, NumPy, Pandas and Plotly is also desirable for more advanced analyses and data visualisations. You should record your research regularly (ideally using Jupyter) and at the end of your RIS you will present how your contributions offered new insights into understanding ERMs in multiple myeloma and lymphoma. Candidates capable of committing to the research full time will be offered student assistant pay. Our scheme should provide you with valuable working experience suitable for applying to bioinformatics or data science positions inside and outside academia. Students showing exceptional interest and potential can be offered a Research Associate job in the LYH lab after they graduate.