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Increasingly, data sources from literature and online sources are combined with the traditional types of data [ 18] for summarization of complex information, extraction of knowledge, decision support, and predictive analytics.
We present different algorithmic methods to address this question, and discuss case studies that show its usefulness for information summarization and presentation.
Beyond the summarization of such information for trend analyses, extracted and grounded mutation impact annotations will also aid protein engineers when reviewing 3D visualizations of protein structures, as described by [ 7].
Chiang et al. (2006) developed a text-mining-based gene information summarization technique for a cluster of genes based on information extracted from PubMed abstracts followed by processing using a Finite State Automaton.
This may be required for limiting the usage of resources, for instance transmission bandwidth or storage memory; for summarization purposes; or even for relieving the user from information overload.
For summarization and easy reference to the readers, a table (Additional file 14 Table S10) summarizing the various supplementary information provided by RNA-Seq study to the current genome annotation was listed in the supplemental materials.
The centerpiece of this work is an objective function for summarization that I call "maximum coverage".
Fig. 8 Multiple representations for summarization.
Single-document summarization is easy to handle since only one text document needs to be analyzed for summarization, whereas handling multi-document summarization is a complex and difficult task.
RMA algorithm was applied for summarization, and the normalization was performed by the quantile method.
However, patient records offer a significantly different 'document context' for summarization research.
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