Advanced Biomedical Computational Science

Overview

The Advanced Biomedical Computational Science team focuses on applications of bioinformatics, computational and data science, and artificial intelligence to problems in cancer, infectious disease, immunology, rare disease, HIV and other specialized areas in biomedical research.  

Our scientists provide expertise, consultation, collaborative research, and project support in a broad range of computational and data science domains to Frederick National Laboratory, National Cancer Institute and National Institutes of Health and other federal researchers and staff.  

Our Advanced Biomedical Computational Science team encompasses specialized groups focusing on machine learning applied to the interpretation of 2D and 3D biomedical images, clinical and genomics integration, computational chemistry, bioinformatic analysis of omics data, and other applications of computational and data science.  

In 2019 and 2020, we won medical imaging AI challenges on cancer tumor segmentation. In 2020, we benchmarked single-cell RNA sequencing technologies as part of a multicenter study and in 2022, a publication with our quantum chemistry calculations was selected as one of the most interesting articles in the journal of Photochemistry and Photobiology. 

Our groups regularly publish in top-tier journals on bioinformatics, immunology, image analysis, computational chemistry, and knowledge integration. 

Focus

NextGen Sequencing 

  • Specialize in next-generation sequencing data analysis and quality control, sequencing technology consultation, exploration and assessment of new protocols and technologies, and data analysis and management for the National Cancer Institute.  

  • Work closely with CCR researchers and the CCR sequencing facility core and provide end-to-end bioinformatics support for next-generation sequencing projects. 

  • Develop computational pipelines for both routine and custom NGS workflows 

  • Provide processing, analysis, and interpretation of high-dimensional data sets. 

  • Support the clinical sequencing facility in running CLIA pipelines including but not limited to targeted panels, RNA-Seq and Exome-Seq. 

  • Support the Bioinformatics Training and Education Program, providing classes and workshops featuring subject matter experts, and training offered in bioinformatics and data visualization, to enable CCR researchers to analyze their own NGS data. 

Data Solutions and Systems Biology 

  • Streamline and provide integrative and innovative solutions for the National Cancer Institute and National Institutes of Health community to access and use biological information collected across different sources and formats.  

  • Develop interactive solutions for disease-agnostic data sharing, analysis, variant impact annotations, identifier conversions across species, clinical-genomics integration and visualization of multi-modal biomedical data.  

  • Provide scientific infrastructure, scientific workflow management and innovative scientific web application and tool development support.  

  • Create applications and web interfaces for dynamic queries and interaction with biomedical data and scientific applications.

Biomedical Image Analysis and Visualization 

  • Support and accelerate basic research by developing and implementing technologies in image analysis and scientific visualization.  

  • Use machine learning and deep learning for digital pathology 3D electron microscopy, light microscopy, image volume registration, and web-based, real-time visualization.  

  • Facilitate data access, collaboration, and reuse to reduce duplicate efforts.  

Mathematical and Statistical Analysis 

  • Collaborate on projects requiring mathematical and statistical analysis, study design, visualization of study results, and modeling of cancer and HIV/AIDS.  

  • Create mathematical and statistical modeling for computational simulations, regression analysis, and survival analysis.  

  • Provide study design consultation.  

  • Provide training and outreach to increase awareness and understanding of statistics such as statistical reasoning seminars and tutorials, scientific programming seminars and tutorials, and software carpentry workshops.  

Computational Chemistry and Protein Modeling 

  • Provide innovative solutions over a wide range of structure analysis and computational chemistry tools.  

  • Develop tools and custom workflows for structural modeling including protein structures and drug interactions.  

  • Assist in drug design with small molecule properties obtained from high-level quantum chemical calculations.  

  • Develop algorithms and software for GAMESS.

Technology

Machine learning and artificial intelligence 

  • Deep learning 

  • Digital Pathology 

  • NLP/Text mining 

Advanced structural studies 

  • Protein structural prediction 

  • Protein/Ligand interactions 

  • Quantum chemical analysis 

 Advanced genomics technologies 

  • Single cell sequencing  

  • Spatial transcriptomics  

  • Clinical translation 

Data integration technologies 

  • Graph databases 

  • SQL/NoSQL 

Our Services

Other