What is he best known for?
The fields of study he is best known for:
His primary areas of investigation include Genetics, Computational biology, Proteomics, Protein–protein interaction prediction and Interactome.
Haiyuan Yu combines subjects such as Bioinformatics, Human genome, Protein–protein interaction and Genomics with his study of Computational biology.
His study in Genomics is interdisciplinary in nature, drawing from both Exome sequencing, Genome-wide association study, Genetic variability, Genetic association and Genetic variation.
His studies deal with areas such as Fungal protein and Genomic library as well as Proteomics.
His Protein–protein interaction prediction research is multidisciplinary, incorporating elements of Phenome, In silico, Caenorhabditis elegans and Functional genomics.
Many of his studies on Interactome apply to Interaction network as well.
His most cited work include:
- A global reference for human genetic variation. (7825 citations)
- Global landscape of protein complexes in the yeast Saccharomyces cerevisiae (2539 citations)
- A Map of the Interactome Network of the Metazoan C. elegans (1453 citations)
What are the main themes of his work throughout his whole career to date?
Haiyuan Yu mostly deals with Computational biology, Genetics, Interactome, Gene and Bioinformatics.
His study explores the link between Computational biology and topics such as Proteome that cross with problems in Data mining.
His research in Saccharomyces cerevisiae, Transcription factor, Missense mutation, Proteomics and Allele are components of Genetics.
His Proteomics research includes themes of DNA microarray and Protein–protein interaction prediction.
Haiyuan Yu works on Interactome which deals in particular with Human interactome.
His biological study spans a wide range of topics, including Disease and Bayes' theorem.
He most often published in these fields:
- Computational biology (47.69%)
- Genetics (37.69%)
- Interactome (21.54%)
What were the highlights of his more recent work (between 2018-2021)?
- Computational biology (47.69%)
- Gene (17.69%)
- Proteome (11.54%)
In recent papers he was focusing on the following fields of study:
Haiyuan Yu mainly investigates Computational biology, Gene, Proteome, Genetics and Interactome.
Haiyuan Yu undertakes multidisciplinary studies into Computational biology and Massively parallel in his work.
His study on Genome is often connected to Drug repositioning as part of broader study in Gene.
His Proteome study integrates concerns from other disciplines, such as Data mining and Word error rate.
His Genetics study frequently draws connections to adjacent fields such as Drug discovery.
The study incorporates disciplines such as Genomic data, Mutational hotspot, Specific protein and Protein–protein interaction in addition to Interactome.
Between 2018 and 2021, his most popular works were:
- Extensive disruption of protein interactions by genetic variants across the allele frequency spectrum in human populations (17 citations)
- MaXLinker: Proteome-wide Cross-link Identifications with High Specificity and Sensitivity. (15 citations)
- SAAMBE-3D: Predicting Effect of Mutations on Protein-Protein Interactions. (12 citations)
In his most recent research, the most cited papers focused on:
His main research concerns Computational biology, Proteome, Protein structure, Phosphorylation and Budding yeast.
His research in Computational biology is mostly focused on Systems biology.
His Systems biology research incorporates elements of Protein protein, Proteomics and Protein protein interaction network.
His studies in Proteome integrate themes in fields like Data mining, Structure validation and Word error rate.
His Protein structure research is multidisciplinary, relying on both Eukaryotic cell, DNA damage, Saccharomyces cerevisiae and Phosphorylation sites, Mutant.
His Interaction network research is multidisciplinary, incorporating perspectives in Mammalian brain, Function and Interactome.
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