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Wing-Kin Sung
Researcher at National University of Singapore
Publications - 335
Citations - 28128
Wing-Kin Sung is an academic researcher from National University of Singapore. The author has contributed to research in topics: Gene & Genome. The author has an hindex of 64, co-authored 327 publications receiving 26116 citations. Previous affiliations of Wing-Kin Sung include University of Hong Kong & Yale University.
Papers
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Journal ArticleDOI
Fast algorithms for computing the tripartition-based distance between phylogenetic networks
TL;DR: An O(n) time algorithm is given for comparing galled-trees, which are an important, biological meaningful special case of phylogenetic network, and an $$O(n + kh)$$-time algorithm for comparing a galling-tree with another general network, where h and k are the number of hybrid nodes in the latter network and its biggest biconnected component respectively.
Journal ArticleDOI
HIVID2: an accurate tool to detect virus integrations in the host genome.
Xi Zeng,Linghao Zhao,Chenhang Shen,Yi Zhou,Guoliang Li,Wing-Kin Sung,Wing-Kin Sung,Wing-Kin Sung +7 more
TL;DR: Zeng et al. as mentioned in this paper developed a method for accurate detection of virus integration into host genomes, which is a significant upgrade of HIVID and performs a paired-end combination (PE-combination) for potentially integrated reads.
Journal ArticleDOI
D-SLIMMER: domain-SLiM interaction motifs miner for sequence based protein-protein interaction data.
TL;DR: This work proposes a method called D-SLIMMER to mine for SLiMs in PPI data on the basis of the interaction density between a nonlinear motif in one protein and a SLiM in the other protein, and shows that D- SLIMMER outperformed existing methods notably for discovering domain-SLiMs interaction motifs.
Journal ArticleDOI
SurVIndel: improving CNV calling from high-throughput sequencing data through statistical testing.
TL;DR: A novel caller, SurVIndel, which focuses on detecting deletions and tandem duplications from paired next-generation sequencing data and outperforms existing methods on both simulated and real biological datasets.
Book ChapterDOI
Greedy Consensus Tree and Maximum Greedy Consensus Tree Problems
TL;DR: This study focuses on one of the most frequently used consensus tree problems, called greedy consensus tree problem, and describes an O(k^2 n) time solution, which is the fastest when k = O(\sqrt{n} \log n)\).