The advent of long-read sequencing technologies, combined with spatial
transcriptomics assays, provided new long-read data, measuring isoform expression
at spatial resolutions. Each location in spatial data typically captures transcripts from
multiple cells. Cell type deconvolution aims to estimate the proportions of cell types
within each location, enabling the association of specific cell types to each location. I
will develop methods for cell type deconvolution from spatial isoform-resolution
expression data, both with and without the use of cell-type signature genes. The
expression patterns of those signature genes are known to be characteristic of specific
cell types .
The University of Melbourne
Yichen Jiang is a third year undergraduate student at the University of Melbourne, majoring in Data Science. His interest lies in using statistical methods and Machine Learning tools to solve real world problems. As a recipient of Melbourne Chancellor’s scholarship, Yichen’s interest in mathematical research was sparked in his second year study, where he received the Maurice H.Belz prize in statistics in 2022.
For Yichen, dealing with large amount of real data while deriving valuable inferences from it has always been an exciting and rewarding experience. He started the journey by taking a research subject in his last year of undergraduate study; he wishes to further explore the power of big data and statistical modelling now and in the future.
Outside of mathematics, Yichen is passionate about learning AI and how it is applied in our everyday life. Over the winter break in 2023, he worked on a team project to develop a bot that plays Gomoku (also known as Five in a row) and he aims to improve this bot in the future after learning about more advanced algorithms. Apart from studying, Yichen enjoys basketball, music and travelling as leisure activities. He also really likes teaching mathematics to younger students, delivering difficult concepts in an intuitive way has always been his goal.