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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.

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Journal ArticleDOI

Reconstructing Recombination Network from Sequence Data: The Small Parsimony Problem

TL;DR: The small parsimony problem is studied for reconstructing recombination networks from sequence data and is polynomial-time solvable for phylogenetic trees.
Journal ArticleDOI

SurVirus: a repeat-aware virus integration caller.

TL;DR: Wang et al. as mentioned in this paper proposed SurVirus, an improved virus integration caller that corrects the alignment of reads which are crucial for the discovery of integrations, and used publicly available datasets to show that existing methods predict hundreds of thousands of false positives.
Journal ArticleDOI

The Integrator Complex Prevents Dedifferentiation of Intermediate Neural Progenitors back into Neural Stem Cells

TL;DR: It is demonstrated that the Drosophila Integrator complex prevents dedifferentiation of intermediate neural progenitors (INPs) during neural stem cell (neuroblast) lineage development by regulating a key transcription factor Erm that also suppresses INP dedifferentiated.
Journal ArticleDOI

Pathway aberrations of murine melanoma cells observed in Paired-End diTag transcriptomes.

TL;DR: The highly correlated results unmistakably point to a systematic downregulation of mitochondrial activities, which is hypothesize aims to downgrade the mitochondria-mediated apoptosis and the dependency of cancer cells on angiogenesis.
Book ChapterDOI

Local gapped subforest alignment and its application in finding RNA structural motifs

TL;DR: It is proved that a special case of the local gapped subforest alignment problem is equivalent to a problem known in the literature as the local sequence-structure alignment problem (lssa) and the main algorithm is modified to obtain a much faster algorithm for lssa than the one previously proposed.