Overview of the Platforms

Overview

This resources aims to improve access to bioinformatics computing platforms many of which are funded by the ITCR (Informatics Technology for Cancer Research) program of the NCI (National Cancer Institute). Here is the glossary for relevant terms used in these tables:

• Platforms are web or cloud-based websites/webpages that allow users to analyze their own data and/or publicly available data.

• A scientific platform is a set of web or cloud-based tools, resources, and infrastructure that allows scientists to analyze data and conduct research. It involves working with data generated by laboratory equipment, clinical treatments, computational resources, and data management systems. The goal is always to provide scientists with the necessary resources to advance their understanding and utilization of a particular subject or phenomenon while recognizing that the specific components of a scientific platform will vary depending on the field of research.

• ITCR platforms, funded by the NCI (National Cancer Institute), are such tools and resources that are designed to assist scientists and researchers in the field of cancer research and provide them with the supporting tools and resources required to effectively study cancer and develop existing and new treatments. These platforms include a variety of different components including, but not limited to, data management systems, analytical tools, and computational resources that help researchers collect, store, and analyze large amounts of data related to cancer research such as genetic information, medical records, and imaging data.

• Multi-data type platforms allow users to work with more than one type of data, including a wide variety of data types, from imaging, histological, omics, and clinical data.

• Imaging platforms work with clinical and pre-clinical images containing pathology imaging to radiographic imaging (e.g., CT, MRI, PET) obtained by specialized medical imaging devices.

• Omics platforms work with proteomic, transcriptomic, genomic, metabolomic, lipidomic, and epigenomic data, which correspond to global analyses of data on proteins, RNA, genes, metabolites, lipids, and methylated DNA or modified histone proteins in chromosomes.

• Clinical platforms work with several types of clinical data, such as EMR Text and Clinical Notes, utilizing Natural Language Processing techniques, AI and machine learning algorithms.

• Data resources are remotely hosted sources of curated or collaborative bioinformatics data containing genomics, proteomics, imaging (histology and radiology), as well as other various types of data. See the Data Resource page for more information.