Evolution and functional impact of gene silencing by hairpin derived RNAs. This project aims to study RNA-mediated gene silencing in genome evolution. RNA interference (RNAi) has been widely used as an experimental tool since its Nobel Prize-winning discovery in 1998, but little is known about endogenous RNAi or its evolution. This project uses bioinformatics, high-throughput sequencing and molecular approaches to study hpRNAs, a class of small interfering RNAs, their adaptive evolution across f ....Evolution and functional impact of gene silencing by hairpin derived RNAs. This project aims to study RNA-mediated gene silencing in genome evolution. RNA interference (RNAi) has been widely used as an experimental tool since its Nobel Prize-winning discovery in 1998, but little is known about endogenous RNAi or its evolution. This project uses bioinformatics, high-throughput sequencing and molecular approaches to study hpRNAs, a class of small interfering RNAs, their adaptive evolution across fly species and vertebrates, and their functional effect on testis morphogenesis and distortion of female/male sex-ratio. The project also studies splicing-dependent small RNAs and miRNA-target interaction. This research could have applications from animal development to human pathology.Read moreRead less
The systems biology of stem cells. Using new bioinformatic methods, this project aims to identify new classifiers of different stem cell populations, develop statistical models that address population heterogeneity and provide molecular predictors of the differentiation potential of stem cells. Understanding, predicting and directing the processes of differentiation are major goals in the disciplines of stem cell biology, developmental biology, tissue engineering and regenerative medicine. Molec ....The systems biology of stem cells. Using new bioinformatic methods, this project aims to identify new classifiers of different stem cell populations, develop statistical models that address population heterogeneity and provide molecular predictors of the differentiation potential of stem cells. Understanding, predicting and directing the processes of differentiation are major goals in the disciplines of stem cell biology, developmental biology, tissue engineering and regenerative medicine. Molecular atlas projects have successfully revealed rules of genome output and regulation, by mining patterns that are evident across multiple cell types and datasets. By applying this philosophy to relevant, well-curated stem cell experiments, this project aims to create new methods for the integration and interrogation of smaller individual datasets. These methods should have broad utility and enable new avenues in tissue engineering.Read moreRead less
Exploring novel coding genomic features through integrative proteogenomics. Knowledge of the full extent to which the human genome is made into proteins is of fundamental importance in the study of health and disease. New technological advances are now enabling functional studies of genomes with increasing detail. This project aims to develop and apply cutting edge bioinformatics methods to perform an integrative and comprehensive exploration of the extent to which the genes of a human cell line ....Exploring novel coding genomic features through integrative proteogenomics. Knowledge of the full extent to which the human genome is made into proteins is of fundamental importance in the study of health and disease. New technological advances are now enabling functional studies of genomes with increasing detail. This project aims to develop and apply cutting edge bioinformatics methods to perform an integrative and comprehensive exploration of the extent to which the genes of a human cell line are made into proteins. The project will improve our understanding of the human genome and deliver cutting edge methodology applicable for genome annotation in all living organisms.Read moreRead less
Developing bioinformatics methods for single cell transcriptomics. This project aims to develop novel bioinformatics methods for single cell transcriptomic data that seek to model variability in cell populations. The project expects to generate new approaches using Bayesian statistics that will act as high-end enablers of discovery in transcriptional regulatory processes. Through an interdisciplinary combination of experimental and computational research, insights into fundamental biological pro ....Developing bioinformatics methods for single cell transcriptomics. This project aims to develop novel bioinformatics methods for single cell transcriptomic data that seek to model variability in cell populations. The project expects to generate new approaches using Bayesian statistics that will act as high-end enablers of discovery in transcriptional regulatory processes. Through an interdisciplinary combination of experimental and computational research, insights into fundamental biological processes will be elucidated, specifically the robustness of cellular systems. Expected outcomes include a suite of novel tools that will push the boundaries of current bioinformatics solutions with potential to deliver significant benefits to every domain of biological science, particularly tissue engineering and synthetic biology.Read moreRead less