Kai Ye
Impact in
- Genetics top 0.05%
- Genetic Associations and Epidemiology
- Genomic variations and chromosomal abnormalities
- Genomics and Rare Diseases
- Forensic and Genetic Research
- Cancer Research top 0.05%
- Cancer Genomics and Diagnostics
Papers in
-
- Cancer Genomics and Diagnostics 30
- Genetics 53
- Genomic variations and chromosomal abnormalities 25
- Genomics and Rare Diseases 11
- Genetic Associations and Epidemiology 11
- Forensic and Genetic Research 5
- Co-authors
- Zemin Ning (6 shared papers)Quan Long (3 shared papers)Rolf Apweiler (2 shared papers)Marcel H. Schulz (1 shared paper)Li Ding (6 shared papers)Michael C. Wendl (6 shared papers)Beifang Niu (5 shared papers)Michael D. McLellan (5 shared papers)
- Journals
- Nature Communications (21 papers)Nature (16 papers)Bioinformatics (10 papers)Genomics Proteomics & Bioinformatics (10 papers)Nature Genetics (9 papers)
- Partner nations
- ChinaUnited StatesNetherlands
In The Last Decade
Kai Ye
206 papers receiving 52.3k citations
Kai Ye's Hit Papers
Peers
Comparison fields: 5 of 202
- Genetics 18.4k
- Cancer Research 8.2k
- Molecular Biology 13.8k
- Oncology 4.6k
- Pulmonary and Respiratory Medicine 3.8k
Countries citing papers authored by Kai Ye
This map shows the geographic impact of Kai Ye's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kai Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai Ye more than expected).
Fields of papers citing papers by Kai Ye
This network shows the impact of papers produced by Kai Ye. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kai Ye. The network helps show where Kai Ye may publish in the future.
Co-authors
The 25 scholars most cited alongside Kai Ye, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 220 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A global reference for human genetic variation Hit paper breakdown → | 2015 | 12887 |
| 2 | A map of human genome variation from population-scale sequencing Hit paper breakdown → | 2010 | 6377 |
| 3 | Comprehensive molecular profiling of lung adenocarcinoma Hit paper breakdown → | 2014 | 4597 |
| 4 | Mutational landscape and significance across 12 major cancer types Hit paper breakdown → | 2013 | 3554 |
| 5 | The repertoire of mutational signatures in human cancer Hit paper breakdown → | 2020 | 2401 |
| 6 | Pan-cancer analysis of whole genomes Hit paper breakdown → | 2020 | 2169 |
| 7 | An integrated map of structural variation in 2,504 human genomes Hit paper breakdown → | 2015 | 1657 |
| 8 | Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads Hit paper breakdown → | 2009 | 1599 |
| 9 | A comprehensive catalogue of somatic mutations from a human cancer genome Hit paper breakdown → | 2009 | 1344 |
| 10 | A Systematic Survey of Loss-of-Function Variants in Human Protein-Coding Genes Hit paper breakdown → | 2012 | 937 |
| 11 | Mapping copy number variation by population-scale genome sequencing Hit paper breakdown → | 2011 | 860 |
| 12 | The evolutionary history of 2,658 cancers Hit paper breakdown → | 2020 | 730 |
| 13 | MSIsensor: microsatellite instability detection using paired tumor-normal sequence data Hit paper breakdown → | 2013 | 657 |
| 14 | Multi-platform discovery of haplotype-resolved structural variation in human genomes Hit paper breakdown → | 2019 | 577 |
| 15 | High-coverage whole-genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios Hit paper breakdown → | 2022 | 575 |
| 16 | Patterns of somatic structural variation in human cancer genomes Hit paper breakdown → | 2020 | 564 |
| 17 | Whole-genome sequence variation, population structure and demographic history of the Dutch population Hit paper breakdown → | 2014 | 531 |
| 18 | Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing Hit paper breakdown → | 2020 | 489 |
| 19 | Haplotype-resolved diverse human genomes and integrated analysis of structural variation Hit paper breakdown → | 2021 | 438 |
| 20 | Analyses of non-coding somatic drivers in 2,658 cancer whole genomes Hit paper breakdown → | 2020 | 428 |
About Kai Ye
Kai Ye is a scholar working on Cancer Research, Genetics, Molecular Biology, Plant Science and Physiology, having authored 220 papers that have together received 53.2k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (33 papers), Cancer Genomics and Diagnostics (30 papers), Genomic variations and chromosomal abnormalities (25 papers), Chromosomal and Genetic Variations (16 papers), Genomics and Rare Diseases (11 papers), Genetic Associations and Epidemiology (11 papers), Heavy metals in environment (6 papers) and Forensic and Genetic Research (5 papers). The work is most often cited by research in Genetics (18.4k citations), Cancer Research (8.2k citations), Molecular Biology (13.8k citations), Oncology (4.6k citations) and Pulmonary and Respiratory Medicine (3.8k citations). Kai Ye has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Zemin Ning, Quan Long, Rolf Apweiler, Marcel H. Schulz, Li Ding, Michael C. Wendl, Beifang Niu, Michael D. McLellan, Mingchao Xie and Qunyuan Zhang. Their work appears in journals such as Nature Communications, Nature, Bioinformatics, Genomics Proteomics & Bioinformatics and Nature Genetics.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.