Advanced Biomedical Computational Science Group

The Advanced Biomedical Computational Science (ABCS) group focuses on applications of bioinformatics, computational and data science, and artificial intelligence to support NCI researchers.

ABCS provides:

• Subject matter expertise in genomics, proteomics, and imaging.
• Machine learning/Artificial intelligence for image analysis, text mining/NLP.
• Expertise in protein and nucleotide modeling, cheminformatics and quantum chemistry.
• Statistical analysis, large scale data integration.
• Programming expertise in several languages and database skills.

Support is available at no additional cost to all NCI researchers and can be requested by submitting a project request at https://abcs-amp.nih.gov/project/request/ABCS/.

ABCS also provides training and outreach through 3 training series offered on Tuesdays at noon.

• Statistics for Lunch: explores statistics topics at an intuitive and high-level.
• FRCE and Computational Science: trainings on using large compute resources to solve various scientific challenges.
• Programmer’s Corner: series for programmers to discuss topics of interest.

Additional links of interest include:

Publications: https://bioinfo-abcc.ncifcrf.gov/bioinfo/public/publications
Scientific applications: https://bioinfo-abcc.ncifcrf.gov/ Code repositories: https://abcsfrederick.github.io/

The following outlines ABCS expertise by subject:

• Bioinformatics and next-generation sequencing (NGS)

  • Gene expression analysis.
  • SNPs/indels and large structural variant analysis.
  • Genome assembly and annotation.
  • Whole genome or targeted methylation analysis.
  • Single cell analysis.
  • Experimental design consultation.
  • Result interpretation and visualization.
  • Bioinformatics training.

• Biomedical image analysis and visualization

  • Tumor segmentation and quantification.
  • Custom analysis – cancer subtype identification, predict prognosis and survival.
  • Whole animal image and tissue slide analysis.
  • Spatial transcriptomics.
  • Support tissue analysis core (TAC) and small animal imaging program (SAIP).

• Computational chemistry

  • Elucidate biomolecular interactions.
  • Predict fluorescence spectra.

• Protein modeling

  • Drug target binding.
  • Protein-Protein interactions.
  • Molecular dynamics simulations.

• Statistics and mathematical analysis

• Biomedical data mining, annotations, and integration

  • Automatic downloads and maintenance of 100s of annotations including genes, proteins, drugs, literature, and variants.
  • Integrate annotations into existing or new applications.
  • Multi-modal large scale data integrations with omics, clinical and imaging data.

• Scientific and high-performance computing (HPC), scientific web development, and scientific infrastructure.

  • Scientific data sharing applications.
  • Develop custom websites for hosting software developed in the labs.
  • Integrate with services such as HPC, GridFTP, SQL, and NoSQL databases.
  • Applications for managing sequencing and imaging efforts, and integrating with analysis workflows.
  • Scientific catalogs, training resources.
  • Web-based services.