Xiaoying Jia

4.7k citations
83 papers · 2.8k indexed · h-index 26

Impact in

  • Genetics top 2%
    • Chronic Lymphocytic Leukemia Research
  • Hematology top 2%
    • Multiple Myeloma Research and Treatments

Papers in

    • Chronic Lymphocytic Leukemia Research 23
    • Multiple Myeloma Research and Treatments 10

Xiaoying Jia

82 papers receiving 2.7k citations

Peers

Xiaoying Jia
Comparison fields: 5 of 130
  • Genetics 439
  • Hematology 375
  • Pathology and Forensic Medicine 390
  • Cancer Research 317
  • Molecular Biology 1.3k
Replace John Paul Shen with:
John Paul Shen United States
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Kong‐Peng Lam Singapore
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Robert Carter United States
Xiaowei Yan United States
Ευγενία Γιαννοπούλου United States
Subrata Ghosh India
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Citations per field
00.5×3.9×
John Paul Shen · 1×
Citations per year

Countries citing papers authored by Xiaoying Jia

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoying Jia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xiaoying Jia, 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 Xiaoying Jia Line = papers co-authored together Xiaoying Jia links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20243
3 20235
4 202312
5 20237
6 20235
7 20232
8 202212
9 20217
10 202025
11 202017
12 20172
13 201542
14 2013371
15 201238
16 200915
17 20093
18 20093
19 200817
20
Genetic analysis of West Nile New York 1999 encephalitis virus (vol 354, pg 1971, 1999)
200019

About Xiaoying Jia

Xiaoying Jia is a scholar working on Genetics, Hematology, Pathology and Forensic Medicine, Infectious Diseases and Cancer Research, having authored 83 papers that have together received 2.8k indexed citations. Recurring topics across this work include Chronic Lymphocytic Leukemia Research (23 papers), Lymphoma Diagnosis and Treatment (14 papers), Cryptography and Data Security (11 papers), Multiple Myeloma Research and Treatments (10 papers), PI3K/AKT/mTOR signaling in cancer (7 papers), Mosquito-borne diseases and control (7 papers), Viral Infections and Outbreaks Research (6 papers) and SARS-CoV-2 and COVID-19 Research (5 papers). The work is most often cited by research in Genetics (439 citations), Hematology (375 citations), Pathology and Forensic Medicine (390 citations), Cancer Research (317 citations) and Molecular Biology (1.3k citations). Xiaoying Jia has collaborated with scholars based in United States, China and France. Frequent co-authors include Debiao He, Kim‐Kwang Raymond Choo, Neeraj Kumar, Irene M. Ghobrial, Hai T. Ngo, Aldo M. Roccaro, Xavier Leleu, Antonio Sacco, Kenneth C. Anderson and Judith Runnels. Their work appears in journals such as Blood, Clinical Cancer Research, IEEE Internet of Things Journal, Molecular & Cellular Proteomics and Journal of Virology.

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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