The Advanced Biomedical Computational Science group 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.
We provide expertise, consultation, collaborative research, and project support in a broad range of computational science domains to Frederick National Laboratory, National Cancer Institute, National Institutes of Health, and other federal researchers and staff.  
Our team is made up of 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, scientific web applications and infrastructure, and other computational and data science applications. 

Translating biomedical data into breakthrough scientific discoveries

Computational science is key to understanding disease mechanisms and diagnostic factors and for finding treatment options for “untreatable” diseases. Whether it’s mining and integrating billions of data points or delving deep into a protein substructure or histopathological image, we are passionate about deciphering biomedical data and discovering new insights.

We work on diverse scientific aspects from basic research to clinical implementation and leverage our expertise across multiple disease domains. 


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GitHub repository

Access our software

Open access to software, including machine learning, deep learning, and AI; imaging software; bioinformatics workflows; sequence annotation algorithms; and statistics tutorials.

Computational scientists with expertise in multiple domains

The Advanced Biomedical Computational Sciences group was established three decades ago to support computational science projects at the National Cancer Institute. At the time of inception, computational scientists and informatics professionals in the group focused on protein modeling efforts requiring large computing resources. The group evolved organically and now handles multiple facets of biomedical data analysis.
We have a distinct and talented team of bioinformaticians, computational chemists, modeling experts, statisticians, web application developers, software engineers, and infrastructure management specialists who work together to solve complex challenges in disease research.

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Collaborative studies and open-access data 

Our teams regularly publish in top-tier journals on bioinformatics, cancer genomics, image analysis, computational chemistry, and knowledge integration. Software and data accessibility is a priority, and we share our algorithms and results through many open-source platforms. We also provide training and outreach to increase awareness and understanding about bioinformatics and statistics, such as bioinformatics software, sequencing workflows, statistical concepts, scientific programming, and computational science seminars.  

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Next-generation sequencing 

We 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 NCI. We work closely with investigators at the NCI Center for Cancer Research and the Sequencing Facility, providing end-to-end bioinformatics support for next-generation sequencing projects. 

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  • Computational pipelines for both routine and custom NGS workflows  

  • Processing, analysis, and interpretation of high-dimensional data sets  

  • CLIA pipelines including but not limited to targeted panels, RNA-Seq and Exome-Seq 

  • Single-cell sequencing   

  • Spatial transcriptomics   

  • Clinical translation 

  • Bioinformatics and data visualization workshops and training 

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Data integration and infrastructure management

Our team streamlines and provides integrative and innovative solutions for the National Cancer Institute and National Institutes of Health community to access and use biological information collected across diverse sources and formats. We develop interactive solutions for disease agnostic data sharing, analysis, variant impact annotations, identifier conversions across species, clinical-genomics integration, and visualization of multimodal biomedical data.

We provide scientific infrastructure, scientific workflow and data management, and scientific web application and tool development support.

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

  • Graph databases and network analysis 

  • Natural language processing and text mining 

  • Web applications for data visualization and streamlined workflows 

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Biomedical image analysis and visualization 

We support and accelerate basic research by providing expertise in image analysis and scientific visualization. Our team deploys machine learning, deep learning, and custom-built software for quantitative analysis of various medical images, including digital pathology, ultrasound, 3D electron microscopy, and light microscopy.

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  • Machine learning, artificial intelligence, and deep learning  

  • Digital pathology  

  • Biomedical image analysis 

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Computational chemistry and protein modeling 

We provide innovative solutions over a broad range of structure analysis and computational chemistry tools, often developing tools and custom workflows for structural modeling, including protein structures and drug interactions. Our team assists in drug design with small-molecule properties obtained from high-level quantum chemical calculations. 

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  • Algorithms and software for General Atomic and Molecular Electronic Structure System (GAMESS)

  • Protein structural prediction 

  • Protein-ligand interactions   

  • Quantum chemical analysis 

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Researcher Resource

Available scientific applications

The Advanced Biomedical Computational Science group provides informatics solutions for simple to advanced scientific challenges that are scalable, modular, and flexible.