To best understand complex human diseases, data should be efficiently collected at various levels and analyzed in an integrated manner. In this context, ‘Bioinformatics’ plays an important role in many aspects, including data storage and retrieval, software development, and data visualization. These are especially critical these days when trying to summarize massive data sets and highly complex analytical outcomes in research.

The Cancer Bioinformatics Core at Cedars-Sinai will provide state-of-the-art bioinformatics services and consulting, proposing the best practice of existing computational pipelines, mathematical modeling, statistical analysis methods, and machine learning approaches. For example, with this resource, our investigators will be able to target these topic areas: 

  1. Identification of novel therapeutic targets through network-based master regulator analysis.
  2. Centralized interpretation of single cell multi-omics data for decoding cellular heterogeneity and identifying cell type specific molecular profile.
  3. Characterization of potential immune and microenvironmental interactions through computational deconvolution methods and multimodal data integration.
  4. Development of machine learning algorithms for biomedicine in the clinic evaluating best practices and validating efficacy for predicting patient outcomes and therapies within institution.
  5. Significant advances in computational infrastructure to provide web resources for community model development and distribution.

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Last updated
September 27, 2023