Complex datasets are being rapidly generated in reproductive sciences, but the data remain poorly integrated. The main objective of the Computational Biology Research Core is to centralize the processing and integration of the heterogeneous datasets to be generated by the project Investigators and to apply powerful analysis methods to discover novel genetic and epigenetic regulators of human development and implantation. This Core will develop and apply rigorous, effective analysis methods that will ensure consistent and reproducible analysis results. The Core will synergize with the proposed research projects as well as other Cores and will also contribute towards advancing the field of computational developmental biology. It will be responsible for managing the flow of data transfer and retrieval, performing rigorous quality control, establishing analysis pipelines, integrating the data, and disseminating the analysis results to the project Investigators as well as the public. Specifically, the proposed closed Core will be able to (1) perform rigorous quality control tests, (2) analyze mRNA expression profiles obtained from microarrays and Next-Generation Sequencing (NGS), (3) infer transcription factor (TF) binding sites and epigenetic modifications from sequencing and microarray experiments, (4) study the biogenesis and functions of small non-coding RNA, and (5) integrate these heterogeneous datasets to formulate probabilistic models of regulatory networks that govern the early stages of human embryo development and implantation.
The results of our research will help model and understand the molecular processes underlying implantation and early human development. Our findings will contribute towards discovering novel regulators of human reproductive health and will help treat diseases leading to poor pregnancy outcomes.
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