Genetics, Social Semantic Web, Computational biology, Data science and Data Web are his primary areas of study. His research in Genetics focuses on subjects like Database, which are connected to Computer graphics. In his research on the topic of Social Semantic Web, Semantic Web is strongly related with Web standards.
As part of his studies on Computational biology, Kei-Hoi Cheung frequently links adjacent subjects like Proteome. His Data Web research incorporates themes from Data integration and Semantic Web Stack. His work in the fields of Linkage disequilibrium and Allele frequency overlaps with other areas such as Population genetics.
His primary areas of study are Semantic Web, Information retrieval, World Wide Web, Database and Data science. In his study, Open Biomedical Ontologies is inextricably linked to Text mining, which falls within the broad field of Semantic Web. His Information retrieval study which covers Data integration that intersects with Bioinformatics.
His research in Database intersects with topics in Interoperation, Genome and Allele frequency. His work carried out in the field of RDF brings together such families of science as Linked data and The Internet. His study on Carcinogenesis is covered under Genetics.
Kei-Hoi Cheung focuses on Psychiatry, Veterans Affairs, Genome-wide association study, Ontology and Metadata. His Genome-wide association study study combines topics from a wide range of disciplines, such as Locus and Clinical psychology. His Ontology research incorporates elements of Gating, World Wide Web and Natural language processing.
As part of the same scientific family, Kei-Hoi Cheung usually focuses on Metadata, concentrating on Interoperability and intersecting with Software framework and FASTQ format. His Data Annotation study frequently draws connections between adjacent fields such as Semantic Web. His Semantic Web research focuses on Semantics and how it connects with The Internet.
His primary scientific interests are in Metadata, Ontology, Extracellular RNA, Terminology and Genome-wide association study. His Metadata research is within the category of World Wide Web. Kei-Hoi Cheung interconnects Software framework, Interoperability, FASTQ format and Discoverability in the investigation of issues within Ontology.
His Extracellular RNA study spans across into subjects like Ribonucleoprotein, Extracellular vesicles, Atlas, Computational biology and Information retrieval. He integrates several fields in his works, including Terminology, Extracellular vesicle, Faceted search, Context, Repertoire and Biotechnology. The Genome-wide association study study combines topics in areas such as Biobank, Genetic risk and Locus.
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Subcellular localization of the yeast proteome
Anuj Kumar;Seema Agarwal;John A. Heyman;Sandra Matson.
Genes & Development (2002)
Global Patterns of Linkage Disequilibrium at the CD4 Locus and Modern Human Origins
S. A. Tishkoff;E. Dietzsch;W. Speed;A. J. Pakstis.
The BioPAX community standard for pathway data sharing
Emek Demir;Emek Demir;Michael P. Cary;Suzanne Paley;Ken Fukuda.
Nature Biotechnology (2010)
Large-scale analysis of the yeast genome by transposon tagging and gene disruption
P. Ross-Macdonald;P. S. R. Coelho;T. Roemer;S. Agarwal.
Advancing translational research with the Semantic Web
Alan Ruttenberg;Tim Clark;William J. Bug;Matthias Samwald.
BMC Bioinformatics (2007)
exRNA Atlas Analysis Reveals Distinct Extracellular RNA Cargo Types and Their Carriers Present across Human Biofluids
Oscar D. Murillo;William Thistlethwaite;Joel Rozowsky;Sai Lakshmi Subramanian.
X!!Tandem, an Improved Method for Running X!Tandem in Parallel on Collections of Commodity Computers
Robert D. Bjornson;Nicholas J. Carriero;Christopher Colangelo;Mark Shifman.
Journal of Proteome Research (2008)
YeastHub: a semantic web use case for integrating data in the life sciences domain
Kei-Hoi Cheung;Kevin Y. Yip;Andrew Smith;Remko Deknikker.
An integrated approach for finding overlooked genes in yeast
Anuj Kumar;Paul M. Harrison;Kei Hoi Cheung;Ning Lan.
Nature Biotechnology (2002)
A Statistical Framework to Predict Functional Non-Coding Regions in the Human Genome Through Integrated Analysis of Annotation Data
Qiongshi Lu;Yiming Hu;Jiehuan Sun;Yuwei Cheng.
Scientific Reports (2015)
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