What is he best known for?
The fields of study he is best known for:
- Gene
- DNA
- Artificial intelligence
Wing-Kin Sung spends much of his time researching Genetics, Genome, Chromatin, Cancer research and Chromatin immunoprecipitation.
Genetics and Computational biology are frequently intertwined in his study.
His Genome study incorporates themes from ENCODE, Sequence analysis and Systems biology.
In his research, GATA3 and Estrogen receptor alpha is intimately related to Enhancer, which falls under the overarching field of Chromatin.
His Chromatin immunoprecipitation study combines topics in areas such as CTCF and Transcription factor, Transcriptional regulation.
His research in ChIA-PET intersects with topics in ChIP-sequencing, RNA polymerase II, Bivalent chromatin and Cell biology.
His most cited work include:
- Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project (4297 citations)
- Integration of External Signaling Pathways with the Core Transcriptional Network in Embryonic Stem Cells (2126 citations)
- An oestrogen-receptor-α-bound human chromatin interactome (1273 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Genetics, Combinatorics, Computational biology, Algorithm and Genome.
His study in Human genome, Chromatin, Chromatin immunoprecipitation, Genomics and Transcription factor is carried out as part of his studies in Genetics.
He works on Chromatin which deals in particular with ChIA-PET.
Wing-Kin Sung has researched Combinatorics in several fields, including Discrete mathematics, Matching and Phylogenetic tree.
He has included themes like Bioinformatics, DNA sequencing, Reference genome, DNA microarray and Virus Integration in his Computational biology study.
His Genome research is multidisciplinary, incorporating perspectives in Sequence analysis and Sequence assembly.
He most often published in these fields:
- Genetics (35.14%)
- Combinatorics (25.06%)
- Computational biology (34.89%)
What were the highlights of his more recent work (between 2016-2021)?
- Computational biology (34.89%)
- Gene (21.62%)
- Genome (29.98%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Computational biology, Gene, Genome, Algorithm and Combinatorics.
His work deals with themes such as Human genome, DNA microarray, Task, Virus Integration and Transcription, which intersect with Computational biology.
Gene is a subfield of Genetics that he explores.
His Genetics study frequently links to adjacent areas such as Molecular ecology.
When carried out as part of a general Genome research project, his work on Genome size is frequently linked to work in Pest control, Trehalose transport and FHIT, therefore connecting diverse disciplines of study.
As part of the same scientific family, he usually focuses on Algorithm, concentrating on Integer and intersecting with Hamming distance.
Between 2016 and 2021, his most popular works were:
- Immune genes are primed for robust transcription by proximal long noncoding RNAs located in nuclear compartments (75 citations)
- Immune genes are primed for robust transcription by proximal long noncoding RNAs located in nuclear compartments (75 citations)
- Algorithms in Bioinformatics: A Practical Introduction (50 citations)
In his most recent research, the most cited papers focused on:
- Gene
- DNA
- Artificial intelligence
Wing-Kin Sung focuses on Computational biology, Gene, Genome, Human genome and Gene expression.
His Computational biology study integrates concerns from other disciplines, such as Reference genome, DNA microarray, Heterochromatin, Transcription and Transposable element.
His Gene study is focused on Genetics in general.
Wing-Kin Sung studies Genetics, focusing on Virus Integration in particular.
The various areas that Wing-Kin Sung examines in his Genome study include Molecular ecology and Sequence assembly.
Wing-Kin Sung has researched Gene expression in several fields, including Carcinogenesis, Cancer, Cancer research and Transcription factor.
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