What is he best known for?
The fields of study he is best known for:
Young Ki Paik mostly deals with Proteome, Proteomics, Molecular biology, Biochemistry and Human proteome project.
His Proteome research incorporates themes from Computational biology and Personalized medicine.
His biological study spans a wide range of topics, including Blood proteins and Fractionation, Chromatography.
His study in Molecular biology is interdisciplinary in nature, drawing from both Hepatocellular carcinoma, Gene, Phosphorylation, Phorbol and Mesenchymal stem cell.
His study in the field of NeXtProt is also linked to topics like Comparability, Error analysis and Process management.
His research in NeXtProt intersects with topics in PeptideAtlas, Genome and Data science.
His most cited work include:
- Overview of the HUPO Plasma Proteome Project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database. (707 citations)
- Mutations in the Δ7-sterol reductase gene in patients with the Smith–Lemli–Opitz syndrome (325 citations)
- Guidelines for the next 10 years of proteomics (291 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Proteomics, Biochemistry, Proteome, Molecular biology and Human proteome project.
His Proteomics research focuses on Computational biology and how it relates to Bioinformatics.
His Proteome research integrates issues from Blood proteins and Database.
His Molecular biology research is multidisciplinary, incorporating perspectives in Complementary DNA, Molecular cloning, Gene and Cell culture.
His work carried out in the field of Human proteome project brings together such families of science as Human Protein Atlas, Chromosome, Human genome and Data science.
His Caenorhabditis elegans study incorporates themes from Pheromone, Sex pheromone, Mutant, Cell biology and Peroxisome.
He most often published in these fields:
- Proteomics (22.90%)
- Biochemistry (22.14%)
- Proteome (18.70%)
What were the highlights of his more recent work (between 2014-2020)?
- Human proteome project (16.79%)
- Computational biology (14.89%)
- Proteome (18.70%)
In recent papers he was focusing on the following fields of study:
Young Ki Paik focuses on Human proteome project, Computational biology, Proteome, Proteomics and NeXtProt.
His work deals with themes such as Human proteins, Human genome, Alternative splicing, Chromosome and Data science, which intersect with Human proteome project.
His Computational biology study also includes fields such as
- Gene that connect with fields like Molecular biology,
- MEDLINE which connect with Chromosome,
- Genomics, which have a strong connection to Chromatography liquid.
His Proteome study combines topics in areas such as Quantitative proteomics and Identification.
Young Ki Paik interconnects Dauer larva, Tandem mass spectrometry, Phenotype, Reprogramming and Peptide sequence in the investigation of issues within Proteomics.
He has researched NeXtProt in several fields, including Human Protein Atlas, Proteogenomics and PeptideAtlas.
Between 2014 and 2020, his most popular works were:
- Human Proteome Project Mass Spectrometry Data Interpretation Guidelines 2.1 (98 citations)
- Integrated GlycoProteome Analyzer (I-GPA) for Automated Identification and Quantitation of Site-Specific N-Glycosylation (48 citations)
- In-depth N-glycome profiling of paired colorectal cancer and non-tumorigenic tissues reveals cancer-, stage- and EGFR-specific protein N-glycosylation (48 citations)
In his most recent research, the most cited papers focused on:
Young Ki Paik spends much of his time researching Human proteome project, Proteome, Computational biology, NeXtProt and Proteomics.
Young Ki Paik combines subjects such as Chromosome, Protein identification, Proteomic Profiling and Data science with his study of Human proteome project.
His Proteome study combines topics from a wide range of disciplines, such as GNB4, False positive paradox and Biomarker discovery.
His Computational biology research includes elements of Human genome, Annotation, Online database, Homology and Open reading frame.
Young Ki Paik has included themes like Human Protein Atlas, Proteogenomics, PeptideAtlas and Data mining in his NeXtProt study.
Young Ki Paik studies Quantitative proteomics, a branch of Proteomics.
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