Profiling the human immune system with machine learning algorithms and bioinformatics software
Project Abstract:
Recent advances in DNA sequencing technology in bulk tissue and single cells are poised to dramatically transform our understanding of molecular biology and human health In particular sequencing the T cell and B cell repertoire in an individual has the potential to revolutionize immunebased diagnostics vaccine profiling and monoclonal antibody engineering However the development of powerful and accessible computational tools to analyze the diverse immune repertoire has lagged behind preventing widespread adoption of immune sequencing in the bench and industry Moreover the prohibitive computational expertise needed to interpret the data has further stymied adoption of immune sequencing as a valuable diagnostic and prognostic in the clinic We propose to develop commercial machine learning and bioinformatics software that will facilitate the processing and analysis of large complex data sets generated by sequencing many cells from the adaptive immune system The intended users are biological researchers and clinicians In this pilot project computational biologists will work with experimental data to develop preliminary analyses of vast collections of single cell data and determine the feasibility of a commercial powerful and easytouse software service for users that will aid both diagnoses and development of effective immunebased therapies
