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Molecular Cavity Topological Representation for Pattern Analysis: A NLP Analogy-Based Word2Vec Method
<span title="2019-11-29">2019</span>
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<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/3loumxx7kzamnlu4h6x3xoz6ay" style="color: black;">International Journal of Molecular Sciences</a>
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Cavity analysis in molecular dynamics is important for understanding molecular function. However, analyzing the dynamic pattern of molecular cavities remains a difficult task. In this paper, we propose a novel method to topologically represent molecular cavities by vectorization. First, a characterization of cavities is established through Word2Vec model, based on an analogy between the cavities and natural language processing (NLP) terms. Then, we use some techniques such as dimension
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<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/ijms20236019">doi:10.3390/ijms20236019</a>
<a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/31795343">pmid:31795343</a>
<a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6928730/">pmcid:PMC6928730</a>
<a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vxme5vblcrbm7g5en3dh25t7ly">fatcat:vxme5vblcrbm7g5en3dh25t7ly</a>
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... and clustering to conduct an exploratory analysis of the vectorized molecular cavity. On a real data set, we demonstrate that our approach is applicable to maintain the topological characteristics of the cavity and can find the change patterns from a large number of cavities.
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