Bioinformatics Biostatistics and Computing

The CCR Collaborative Bioinformatics Resource (CCBR) is a centrally-funded resource group which provides a mechanism for CCR researchers to obtain many different types of bioinformatics assistance to further their research goals. The group has expertise in a broad range of bioinformatics topics, and as such, its goal is to provide a simplified central access point for CCR researchers. Requests for any type of Bioinformatics support should be through the CCBR Project Submission Form. Types of Collaborative Expertise: Next Generation Sequence (NGS) data analysis (RNAseq, scRNAseq, ATAC-seq,… [learn more]

Radiation Oncology Branch is part of CCR. Bioinformatics core is a collaborative resource to support ROB branch and provide service to ROB investigators from NCI and other Institutes access to new technologies, bioinformatics, statistical analysis related to genetics/genomics, and offers access to in-house built software tools. Bioinformatics analysis: work with research scientists to provide consulting prior to experiments, analysis of high-throughput sequencing, gene expression, metabolomics, proteomics, and other biological data to identify: prognostic biomarkers, transcriptio… [learn more]

The Advanced Biomedical Computational Sciences (ABCS) group provides technology development, scientific consultation, collaboration and training, research, software development, and high-performance computing support. ABCS 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 addition, ABCS offers access to databases and software resources for bioinformatics, image a… [learn more]

The goal of Artificial Intelligence Resource (AIR) is to make AI tools available to Clinical Cancer Research (CCR) investigators. The strength of AI is that algorithms can be trained to seek specific information that may scientifically or clinically important. AIR will mainly focus on “Computer Vision” which analyzes medical images, such as radiologic, digital pathology, video/endoscopy and optical imaging among others. Examples of potential projects include developing better screening, detection methods or predictive markers, or improving procedures among many others. Both clinical … [learn more]

The goals of the Bioinformatics Training and Education Program within NCI/CCR are: (1) to make researchers aware of the bioinformatics resources available to them, (2) to provide training and guidance on these resources regularly and at the appropriate level for the researcher throughout their training or tenure, and (3) to enable them to perform as much of the bioinformatics analyses of their data as they wish to learn. [learn more]

We are a bioinformatics team within the Center for Biomedical Informatics and Information Technology’s (CBIIT’s) Cancer Informatics Branch (CIB)—soon to be referred to as the Informatics and Data Science (IDS) Program. Headed by our chief, Dr. Daoud Meerzaman. Collectively, we have an extensive knowledge of data analysis fields and methodologies. We’ve even developed some of our own analytics tools! List of Services: We provide bioinformatics analysis support for life sciences and clinical & translational research for intramural investigators in NCI’s Division of Cancer Epidemi… [learn more]

The NCI Cloud Resources are components of the NCI Cancer Research Data Commons (CRDC) that bring data and computational power together to enable cancer research and discovery. These cloud-based platforms eliminate the need for researchers to download and store large data sets by allowing them to bring analysis tools to the data in the cloud, instead of the traditional process of bringing the data to the tools on local hardware. Cancer Research Data Commons (CRDC): Access harmonized, multi-omics cancer data – Data are available in nodes, harmonized and stored in a format that is re… [learn more]

The NCI Genomic Data Commons (GDC) was established by the NCI Center for Cancer Genomics (CCG) to support the receipt, harmonization, distribution, and analysis of genomic and clinical data from cancer research programs. The GDC provides the cancer research community with a repository and computational platform for cancer researchers who need to understand cancer, its clinical progression, and response to therapy. The GDC accomplishes this by harmonizing raw sequence data against a common reference genome (GrCH38), applying state-of-the-art methods for generating high-level data such a… [learn more]

Established Technologies: The Miner Suite of Bioinformatic Applications, These applications are freely available for public use. Our characterization and analysis of the NCI-60 cancer cell lines, the DNA, RNA, protein, epigenetic and pharmacological levels is accessible through CellMiner, with the expended version including additional cell line sets available through CellMinerCDB., , CellMinerCDB, url:  https://discover.nci.nih.gov/rsconnect/cellminercdb/, CellMiner Cross Database (CDB) is the first web application to allow translational researchers to conduct analyses across all major… [learn more]

Proteomic Data Common (PDC) represents the NCI’s largest public repository of proteogenomic comprehensive tumor datasets, essentially a Proteogenomic Cancer Atlas. It was developed to advance our understanding of how proteins help shape the risk, diagnosis, development, progression, and treatment of cancer. The objectives are (1) to make cancer-related proteomic data sets easily accessible to the public, and (2) facilitate multi-omic integration in support of precision medicine through interoperability with other resources. The PDC uses a cloud-based approach by storing all data sets with … [learn more]

Office of Collaborative Biostatistics, Office of the Clinical Director, is the statistical and data management component of CCR. The Section provides statistical leadership and data management consultation for CCR’s major clinical activities and is involved in the design, review, conduct, monitoring and analysis of intramural clinical trials of experimental treatments for cancer and AIDS-related malignancies. BDMS also provides support, on occasion, for national/multi-center clinical trials. The BDMS also provides a broad range of data analysis and consultation services to CCR labo… [learn more]

The centrally funded Statistics team within the Advanced Biomedical Computational Science group at the Frederick National Lab provides statistical consultation and data analysis support for NCI laboratories. We have broad-range expertise in biomedically relevant areas of applied and computational statistics, as well as related subjects. The team can help with both advanced and standard statistical analyses. These include data-sample comparisons (such as pairwise comparisons and ANOVA), linear or nonlinear regression, linear or nonlinear mixed-effects modeling, survival analysis, power and … [learn more]