Ma Xiaoling

846 citations
4 papers · 698 · h-index 3

Impact in

    • PI3K/AKT/mTOR signaling in cancer
    • Protein Kinase Regulation and GTPase Signaling
    • Cell death mechanisms and regulation
    • Cancer-related gene regulation
    • Ubiquitin and proteasome pathways
    • Ovarian cancer diagnosis and treatment

Papers in

Ma Xiaoling

4 papers receiving 686 citations

Peers

Ma Xiaoling
Comparison fields: 5 of 77
  • Molecular Biology 586
  • Reproductive Medicine 70
  • Pathology and Forensic Medicine 140
  • Cancer Research 101
  • Oncology 159
Replace Pierluigi Benedetti Panici with:
Pierluigi Benedetti Panici Italy
Minghong Wan United States
Andrew K. Godwin United States
Martina L. Skrede Norway
Mattia Cremona Ireland
Ines Koch Germany
Christopher G. Danes United States
Mahrukh M. Hussain United States
Marco Mazzoletti Italy
Jun-Ying Zhou United States
Ma Xiaoling relative to Pierluigi Benedetti Panici Italy Pierluigi Benedetti Panici's profile →
Citations per field
00.5×1.6×
Pierluigi Benedetti Panici · 1×
Citations per year

Countries citing papers authored by Ma Xiaoling

Since Specialization
Citations

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

Fields of papers citing papers by Ma Xiaoling

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 19 scholars most cited alongside Ma Xiaoling, 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 Ma Xiaoling Line = papers co-authored together Ma Xiaoling links everyone, so they are left out of the graph.

All Works

About Ma Xiaoling

Ma Xiaoling is a scholar working on Molecular Biology, Pathology and Forensic Medicine, Automotive Engineering, Civil and Structural Engineering and Oncology, having authored 4 papers that have together received 698 indexed citations. Recurring topics across this work include PI3K/AKT/mTOR signaling in cancer (2 papers), Cancer Mechanisms and Therapy (2 papers), Cytokine Signaling Pathways and Interactions (1 paper), Plant Pathogens and Fungal Diseases (1 paper), Plant Disease Management Techniques (1 paper), Ovarian cancer diagnosis and treatment (1 paper), Transportation Planning and Optimization (1 paper) and Transportation and Mobility Innovations (1 paper). The work is most often cited by research in Molecular Biology (586 citations), Reproductive Medicine (70 citations), Pathology and Forensic Medicine (140 citations), Cancer Research (101 citations) and Oncology (159 citations). Ma Xiaoling has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Mei Sun, Jin Q. Cheng, Gen Wang, Richard I. Feldman, Santo V. Nicosia, Chen Chen Jiang, Domenico Coppola, June E. Paciga, Richard Jove and Sue A. Shelley. Their work appears in journals such as Journal of soil science and plant nutrition, Oncogene and American Journal Of Pathology.

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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