Jun Ling

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We introduce a missing data recovery methodology based on a weighted least squares iterative adaptive approach (IAA). The proposed method is referred to as the missing-data IAA (MIAA) and it can be used for uniform or non-uniform sampling as well as for arbitrary data missing patterns. MIAA uses the IAA spectrum estimates to retrieve the missing data, based(More)
The precise mechanism by which glucocorticoid receptor (GR) regulates the transcription of its target genes is largely unknown. This is, in part, due to the lack of structural and functional information about GR's N-terminal activation function domain, AF1. Like many steroid hormone receptors (SHRs), the GR AF1 exists in an intrinsically disordered (ID)(More)
This paper presents an automata-based algorithm for answering the \emph{provenance-aware} regular path queries (RPQs) over RDF graphs on the Semantic Web. The provenance-aware RPQs can explain why pairs of nodes in the classical semantics appear in the result of an RPQ. We implement a parallel version of the automata-based algorithm using the Pregel(More)
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