Difference between revisions of "Template:Article of the week"

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(Updated article of the week text.)
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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Genome sequencing costs 2011.jpg|250px]]</div>
'''[[Cancer informatics]]''' is a multidisciplinary field of science that "deals with the resources, devices, and methods required to optimize the acquisition, storage, retrieval, and use of [[information]] in cancer" research and treatment. Like many other fields of science, researchers in cancer biology have seen a dramatic increase in the amount of clinical and research data, in particular with genomic and molecular cancer data. While this data can benefit researchers' understanding of cancer behavior and development of better therapies, new and improved data management and analysis tools are needed. Cancer informatics attempts to provide those tools "that interconnect research, clinical activities, and data in an organized and efficient manner, with as broad a database as possible." For many, the coupling of cancer informatics and other bioinformatics tools with computational modeling and statistical analysis will accelerate the goal of making cancer a more treatable if not curable disease.  
'''[[Genome informatics]]''' is a field of computational molecular biology and branch of [[Informatics (academic field)|informatics]] that uses computers, software, and computational solution techniques to make observations, resolve problems, and manage data related to the genomic function of DNA sequences, comparison of gene structures, determination of the tertiary structure of all proteins, and other molecular biological activities. The informatics side of genomics has largely focused on analytical tools and methodologies. DNA-microarray and sequencing technology helped researchers for the Human Genome Project, for example, analyze and understand thousands of genes and their expressions. By 2000, artificial neural networks were being theorized as a possible informatics tools to aid with data analysis and the problem of "high dimensionality" of the outputted data; by 2014 artificial neural networks were being proposed for cancer genomic research.


Cancer informatics can help tackle problems and tasks such as the development of computational diagnosis, prognosis, and predictive models; the development of standards for the entry, annotation, and sharing of clinical cancer data; and the management and distribution of annotated molecular data for further research. ('''[[Cancer informatics|Full article...]]''')<br />
Genome informatics can help tackle problems and tasks such as analyzing DNA sequences, recognizing genes and proteins and predicting their structures, and predicting the biochemical function of new genes or fragments, as well as molecular profiling. ('''[[Genome informatics|Full article...]]''')<br />
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''Recently featured'': [[Evolutionary informatics]], [[Scientific data management system]], [[Centers for Disease Control and Prevention]]
''Recently featured'': [[Cancer informatics]], [[Evolutionary informatics]], [[Scientific data management system]]

Revision as of 17:10, 2 February 2015

Genome sequencing costs 2011.jpg

Genome informatics is a field of computational molecular biology and branch of informatics that uses computers, software, and computational solution techniques to make observations, resolve problems, and manage data related to the genomic function of DNA sequences, comparison of gene structures, determination of the tertiary structure of all proteins, and other molecular biological activities. The informatics side of genomics has largely focused on analytical tools and methodologies. DNA-microarray and sequencing technology helped researchers for the Human Genome Project, for example, analyze and understand thousands of genes and their expressions. By 2000, artificial neural networks were being theorized as a possible informatics tools to aid with data analysis and the problem of "high dimensionality" of the outputted data; by 2014 artificial neural networks were being proposed for cancer genomic research.

Genome informatics can help tackle problems and tasks such as analyzing DNA sequences, recognizing genes and proteins and predicting their structures, and predicting the biochemical function of new genes or fragments, as well as molecular profiling. (Full article...)

Recently featured: Cancer informatics, Evolutionary informatics, Scientific data management system

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