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Biomedical Informatics for Cancer Research, Ochs, Casagrande, Davuluri, (EDT)-,
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Item specifics
- Condition
- PublishedOn
- 2010-05-01
- Title
- Biomedical Informatics for Cancer Research
- Artist
- Not Specified
- ISBN
- 9781441957122
About this product
Product Identifiers
Publisher
Springer
ISBN-10
144195712X
ISBN-13
9781441957122
eBay Product ID (ePID)
17038824902
Product Key Features
Number of Pages
Xviii, 354 Pages
Publication Name
Biomedical Informatics for Cancer Research
Language
English
Subject
Oncology, Research
Publication Year
2010
Type
Textbook
Subject Area
Medical
Format
Hardcover
Dimensions
Item Weight
27.9 Oz
Item Length
9.3 in
Item Width
6.1 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
2010-924049
Dewey Edition
22
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
616.994060285
Table Of Content
Concepts, Issues, and Approaches.- Biomedical Informatics for Cancer Research: Introduction.- Clinical Research Systems and Integration with Medical Systems.- Data Management, Databases, and Warehousing.- Middleware Architecture Approaches for Collaborative Cancer Research.- Federated Authentication.- Genomics Data Analysis Pipelines.- Mathematical Modeling in Cancer.- Reproducible Research Concepts and Tools for Cancer Bioinformatics.- The Cancer Biomedical Informatics Grid (caBIG,): An Evolving Community for Cancer Research.- Tools and Applications.- The caBIG, Clinical Trials Suite.- The CAISIS Research Data System.- A Common Application Framework that is Extensible: CAF-É.- Shared Resource Management.- The caBIG® Life Sciences Distribution.- MeV: MultiExperiment Viewer.- Authentication and Authorization in Cancer Research Systems.- Caching and Visualizing Statistical Analyses.- Familial Cancer Risk Assessment Using BayesMendel.- Interpreting and Comparing Clustering Experiments Through Graph Visualization and Ontology Statistical Enrichment with the ClutrFree Package.- Enhanced Dynamic Documents for Reproducible Research.
Synopsis
This is an overview of software produced to aid cancer research. It first reviews informatics in cancer research then covers authentication and authorization, data management, data pipelines and annotations, algorithms and models and the NCI caBIG initiative., view, showing that multiple molecular pathways must be affected for cancer to develop, but with different specific proteins in each pathway mutated or differentially expressed in a given tumor (The Cancer Genome Atlas Research Network 2008; Parsons et al. 2008). Different studies demonstrated that while widespread mutations exist in cancer, not all mutations drive cancer development (Lin et al. 2007). This suggests a need to target only a deleterious subset of aberrant proteins, since any tre- ment must aim to improve health to justify its potential side effects. Treatment for cancer must become highly individualized, focusing on the specific aberrant driver proteins in an individual. This drives a need for informatics in cancer far beyond the need in other diseases. For instance, routine treatment with statins has become widespread for minimizing heart disease, with most patients responding to standard doses (Wilt et al. 2004). In contrast, standard treatment for cancer must become tailored to the molecular phenotype of an individual tumor, with each patient receiving a different combination of therapeutics aimed at the specific aberrant proteins driving the cancer. Tracking the aberrations that drive cancers, identifying biomarkers unique to each individual for molecular-level di- nosis and treatment response, monitoring adverse events and complex dosing schedules, and providing annotated molecular data for ongoing research to improve treatments comprise a major biomedical informatics need.
LC Classification Number
RC254-282
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