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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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Book ChapterDOI

A Decomposition Theorem for Maximum Weight Bipartite Matchings with Applications to Evolutionary Trees

TL;DR: A new decomposition theorem for maximum weight bipartite matchings is presented and used to design an O(?nW)-time algorithm for computing a maximum weight matching of G, which bridges a long-standing gap between the best known time complexity of computing amaximum weight matching and that of Computing a maximum cardinality matching.
Proceedings ArticleDOI

Fast and accurate probe selection algorithm for large genomes

TL;DR: Based on the new algorithm, optimal short (20 bases) or long (50 or 70 bases) probes can be computed efficiently for large genomes and some smart filtering techniques are used to avoid redundant computation while maintaining the accuracy.
Journal ArticleDOI

A chromosome‐level genome assembly reveals the genetic basis of cold tolerance in a notorious rice insect pest, Chilo suppressalis

TL;DR: The orthologous analysis on those gene families associated with animal cold tolerance provided the first genomic evidence revealing specific cold‐tolerant strategies in C. suppressalis, including those involved in glucose‐originated glycerol biosynthesis, triacylglycerol‐originate glycerolsynthesis, fatty acid synthesis and trehalose transport‐intermediate cold tolerance.
Journal ArticleDOI

Approximate string matching using compressed suffix arrays

TL;DR: A well-studied case in which T is fixed and preprocessed into an indexing data structure so that any pattern query can be answered faster is investigated, which allows us to exploit compressed suffix arrays to reduce the indexing space to O(n) bits, while increasing the query time by an O(log n) factor only.