Jay Yang

3.3k citations
103 papers · 1.3k indexed · h-index 18

Impact in

  • Hematology top 5%
    • Acute Myeloid Leukemia Research
    • DNA Repair Mechanisms
    • Histone Deacetylase Inhibitors Research
    • Protein Degradation and Inhibitors
    • Epigenetics and DNA Methylation
    • Cancer therapeutics and mechanisms
    • Ubiquitin and proteasome pathways

Papers in

    • Acute Myeloid Leukemia Research 35
    • Chronic Myeloid Leukemia Treatments 16
    • Myeloproliferative Neoplasms: Diagnosis and Treatment 13

Jay Yang

92 papers receiving 1.3k citations

Peers

Jay Yang
Comparison fields: 5 of 93
  • Hematology 318
  • Molecular Biology 810
  • Cancer Research 156
  • Oncology 281
  • Genetics 103
Replace Olga Goloubeva with:
Olga Goloubeva United States
William Tse United States
Masamichi Mori Japan
Donna Shields United States
HM Pinedo Netherlands
Betty Glinsmann‐Gibson United States
Ofer Margalit Israel
David Cervi United States
B Soehnlen United States
Kathy Chun Canada
Jay Yang relative to Olga Goloubeva United States Olga Goloubeva's profile →
Citations per field
00.5×5.9×
Olga Goloubeva · 1×
Citations per year

Countries citing papers authored by Jay Yang

Since Specialization
Citations

This map shows the geographic impact of Jay Yang'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 Jay Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay Yang more than expected).

Fields of papers citing papers by Jay Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jay Yang. 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 Jay Yang. The network helps show where Jay Yang may publish in the future.

Co-authors

The 25 scholars most cited alongside Jay Yang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jay Yang Line = papers co-authored together Jay Yang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 103 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008165
2 2020143
3 200286
4 202285
5 200578
6 201057
7 201956
8 201948
9 202038
10 201435
11 201830
12 201227
13 201226
14 202226
15 201623
16 201820
17 202218
18 201517
19 201916
20 202216

About Jay Yang

Jay Yang is a scholar working on Hematology, Genetics, Pathology and Forensic Medicine, Molecular Biology and Oncology, having authored 103 papers that have together received 1.3k indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (35 papers), Chronic Myeloid Leukemia Treatments (16 papers), Protein Degradation and Inhibitors (13 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (13 papers), Lymphoma Diagnosis and Treatment (13 papers), Histone Deacetylase Inhibitors Research (11 papers), Cancer-related gene regulation (11 papers) and DNA Repair Mechanisms (7 papers). The work is most often cited by research in Hematology (318 citations), Molecular Biology (810 citations), Cancer Research (156 citations), Oncology (281 citations) and Genetics (103 citations). Jay Yang has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Grant W. Brown, Ian D. Hickson, Csanád Z. Bachrati, Yongwei Su, Yubin Ge, Holly Edwards, Jeffrey W. Taub, Alexandra Sobeck, Rong Guo and Dongyi Xu. Their work appears in journals such as Blood, Journal of Clinical Oncology, Hematological Oncology, Journal of Pain and Haematologica.

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.

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