Cancer Biomedical Informatics Grid - caBIG

Description: Reasearch Based..
caBIG is a network that freely connects the entire cancer community and doctors all over the world together. The complexity of cancer is prompting researchers to find new ways to synthesize information from diverse data sources and to carry out coordinated research efforts that span multiple institutions. The Grid was created out of the need to share and distribute computational resources. This need was adressed by offering standard applications, common data models and software infastructure.
Patient Care
It was started by the National Cancer Institute (NCI) and puts information out there for doctors to see and try and figure out what is wrong with a patient. Some people will be showing strange symptoms that they (the doctors) are not used to seeing so they will use the network to try and see if their patient’s symptoms are the same as some of the other recorded cases. Once they do find the problem with the patient, they can also use caBIG to see possible treatments that other doctors have used. They can also see what didn’t work and tell patients the side effects, risks, and success rate of those options that will help them decide what route to go with. The only problem with this program is that it is completely voluntary and only they only have access to the information that doctors and hospitals send to them. There are always going to be extreme cases that no one using caBIG will ever know about since the doctors don’t submit the information.

The Grid has many applications that improve patient care including increased communication and security. This is only a small aspect of what they are capable of the biggest effect is the one it has had on research. This system gives doctors a standardized way to research and communicate findings.
Applications:
· CLINICAL TRIAL MANAGEMENT SYSTEMS
o Cancer Central Clinical Database (C3D): a library of standardized templates, including electronic Case Report Forms (eCRFs) for collecting specific clinical protocols-required data. Templates available through C3D can be tailored for reuse across multiple studies.
o Cancer Central Clinical Patient Registry (C3PR): This tool tracks data about an individual patient across clinical trials and at multiple sites.
o caMatch: This tool provides a system for matching eligible patients to clinical trials.
· INTEGRATIVE CANCER RESEARCH
o caARRAY: consists of a microarray database repository that can be accessed for data analysis through visualization tools, enabling researchers to “see” connections and correlations between genes and proteins.
o caWorkbench: provides a platform for the analysis of a variety of biomedical data.
o GeneConnect: a mapping service that connects key word identifiers among the hundreds of such online databases.
o Magellan: Magellan provides a common structure and context that bridges diverse sets of data so that knowledge can more easily be gleaned from the information. User-defined meta-data (information about the research data) is also uploaded to put a more refined structure and context onto the relevant fields in those entities. Lastly, Magellan provides an interface that permits researchers to apply their own analytical software algorithms to that data.
o Proteomics Laboratory Information Management System (LIMS): This software tool is used to track the laboratory processes relevant to two-dimensional gel electrophoresis, with a design to support the addition of new data types as they emerge.
o Q5: Q5 is an algorithm that tells the difference between cancer cells from normal cells based on protein expression.
o Quantitative Pathway Analysis in Cancer (QPACA): a pathway modeling and analysis system that supports exploration of quantitative biological data in the context of a pathway description.
o Transcript Annotation Prioritization and Screening System (TrAPSS): This system includes several tools for researchers searching for the mutations that cause a defect or disease.
o Visual and Statistical Data Analyzer (VISDA): is for analyzing multivariate data sets. It includes cluster-modeling (the idea of grouping data elements within the set according to a particular concept – such as therapeutic response) and visualization tools to provide a graphical view of these analyses.
· IN VIVO IMAGING
o caIMAGE: This Web portal stores cancer images, enabling researchers and scientists to retrieve and submit image and image annotations, including species, organ, tissue, and diagnosis.
· TISSUE BANKS AND PATHOLOGY TOOLS
o caTIES (cancer Text Information Extraction System): it takes information from pathology reports and puts it into electronic formats to help catalog in a standardized way.
o caTISSUE core: this software provides a standard application for biorepositories to handle and track biospecimens, as well as conduct administrative tasks that are essential for biorepository operations.
o caTISSUE Clinical Annotation Engine: This clinical data software centralizes, standardizes, and protects data for research purposes that is collected from the many external sources–such as basic medical records, drug treatments, surgery, radiology, tumor registries, and pathology laboratories–in a modern medical center.

Web Resources:
· http://cabig.cancer.gov/index.asp
· http://www.cagrid.org/mwiki/index.php?title=CaGrid
· https://cabig.nci.nih.gov/

Related Terminology:
· caGRID
· GeneConnect
· Quantitative Pathway Analysis in Cancer (QPACA)
· caIMAGE – Cancer Images Database
· caMatch
· National Human Genome Research Institute

Citations/References:
Applications from caBIG – Tools – http://cabig.cancer.gov/action/tools.asp

Graphics:
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