• 한국언어정보학회지:언어와정보
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• 제10권2호
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• pp.21-45
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• 2006

Connectivity effects have been central issues in dealing with specificational pseudoclefts. While syntactic approaches motivate their analysis in order to explain connectivity effects in terms of a connected clause, these accounts have numerous problems including a wide range of anti-connectivity effects that constitute crucial counterevidence. On the other hand, semantic accounts of connectivity effects treat BV and BT connectivity by independent interpretive mechanisms providing a more fundamental explanation for connectivity effects. Yet existing semantic accounts have limitations in explaining syntactic properties and syntactic connectivity effects in SPCs, and in accounting for BV anti-connectivity effects in English. Focusing on BV connectivity, this paper explores how the relevant (anti-)connectivity facts can be accounted for by an analysis that provides both an elaborate syntactic analysis of SPCs and a semantic mechanism for bound anaphora. Based on Yoo's (2005) non-deletion based, question-answer pair analysis of SPCs, this paper shows that a functional question analysis of a specificational subject, when combined with a theory of operator scope and a non-configurational condition on bound anaphora, can explain various BV (anti-)connectivity patterns in SPCs and related constructions.

• Molecules and Cells
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• 제42권8호
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• pp.579-588
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• 2019

Gene set enrichment analysis (GSEA) is a popular tool to identify underlying biological processes in clinical samples using their gene expression phenotypes. GSEA measures the enrichment of annotated gene sets that represent biological processes for differentially expressed genes (DEGs) in clinical samples. GSEA may be suboptimal for functional gene sets; however, because DEGs from the expression dataset may not be functional genes per se but dysregulated genes perturbed by bona fide functional genes. To overcome this shortcoming, we developed network-based GSEA (NGSEA), which measures the enrichment score of functional gene sets using the expression difference of not only individual genes but also their neighbors in the functional network. We found that NGSEA outperformed GSEA in identifying pathway gene sets for matched gene expression phenotypes. We also observed that NGSEA substantially improved the ability to retrieve known anti-cancer drugs from patient-derived gene expression data using drug-target gene sets compared with another method, Connectivity Map. We also repurposed FDA-approved drugs using NGSEA and experimentally validated budesonide as a chemical with anti-cancer effects for colorectal cancer. We, therefore, expect that NGSEA will facilitate both pathway interpretation of gene expression phenotypes and anti-cancer drug repositioning. NGSEA is freely available at www.inetbio.org/ngsea.

• 대한의용생체공학회:의공학회지
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• 제39권3호
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• pp.124-133
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• 2018

We tried to investigate the changes in cortical activities according to emotional valence states during watching video clips. We examined the neural basis of two emotional states (positive and negative) using spectral power analysis and brain functional connectivity analysis of cortical current density time-series reconstructed from high-density electroencephalograms (EEGs). Fifteen healthy participants viewed a series of thirty-two 2 min emotional video clips. Sixty-four channel EEGs were recorded. Distributed cortical sources were reconstructed using weighted minimum norm estimation. The temporal and spatial characteristics of spectral source powers showing significant differences between positive and negative emotion were examined. Also, correlations between gamma-band activities and affective valence ratings were determined. We observed the changes of cortical current density time-series according to emotional states modulated by video clip. Gamma-band activities showed significant difference between emotional states for thirty seconds at the middle and the latter half of the video clip, mainly in prefrontal area. It was also significantly anti-correlated with the self-ratings of emotional valence. In addition, the gamma-band activities in frontal and temporal areas were strongly phase-synchronized, more strongly for negative emotional states. Cortical activities in frontal and temporal areas showed high spectral power and inter-regional phase synchronization in gamma-band during negative emotional states. It is inferred that the higher amygdala activation induced by negative stimuli resulted in strong emotional effects and caused strong local and global synchronization of neural activities in gamma-band in frontal and temporal areas.