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Different from the existing summarization approaches centered on sentence ranking and clustering, our approach discovers and extracts salient topics from a set of online reviews and further ranks these topics.
The second approach discovers underlying meaningful structures between the domains to find a common latent feature space that has predictive qualities while reducing the marginal distribution between the domains (e.g. Blitzer [5]).
Experimental results on 52 Human gene expression datasets show that proposed approach discovers biologically significant patterns.
Relying on this new concept and using gene expression correlation information, we have shown with two examples how the proposed weighted approach discovers GO terms and pathways unnoticed under the equivalent standard un-weighted functional profiling method.
As shown in Figure 4 and described in Table 2 (the details of genes in each module are shown in Additional file 4), we can find that, in addition to the biological processes appeared in the two 1-dimensional modules, the 2-dimensional approach discovers some new specific processes relevant to disease.
Most importantly we demonstrate that our approach discovers biologically meaningful modules in a lymphoma interaction network which include and extend the results reported by Rosenwald et al. (2002) which have been described to be of importance in the pathogenesis of the GCB and ABC DLBCL subtypes.
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The paper re-examines the largely abandoned 'sites and services' approach, discovering new evidence in India that demonstrates that these projects were largely successful over the long term.
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The proposed approach discovered 24 syndromes which obviously improved the diagnosis accuracy.
Our approach discovered 195 biological pathways and 31 functionally redundant pathway pairs in yeast.
In a second example, an informatics approach discovered 'phenologs', defined as overlapping sets of homologous genes associated with diverse phenotypic outcomes across various species, thus discovering novel genetic relationships between diverse phenotypes.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com