Haiming Ma

686 citations
51 papers · 473 · h-index 12

Impact in

Papers in

    • Genomics and Phylogenetic Studies 11
    • Machine Learning in Bioinformatics 8
    • Circular RNAs in diseases 7
    • RNA and protein synthesis mechanisms 5
    • Cancer-related molecular mechanisms research 19
    • MicroRNA in disease regulation 7

Haiming Ma

46 papers receiving 462 citations

Peers

Haiming Ma
Comparison fields: 5 of 72
  • Cancer Research 117
  • Animal Science and Zoology 85
  • Genetics 103
  • Molecular Biology 239
  • Physiology 77
Replace Liangzhi Zhang with:
Liangzhi Zhang China
Qinyang Jiang China
Shuo Zhou China
Yukio Taniguchi Japan
Sang-Je Park South Korea
Meixia Fang China
Xiaoyi Zhang China
Yeunsu Suh United States
Carine Bernard France
Haiming Ma relative to Liangzhi Zhang China Liangzhi Zhang's profile →
Citations per field
00.5×1.5×2.4×
Liangzhi Zhang · 1×
Citations per year

Countries citing papers authored by Haiming Ma

Since Specialization
Citations

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

Fields of papers citing papers by Haiming Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201659
2 200356
3 201839
4 201727
5 202324
6 202020
7 202118
8 202315
9 202115
10 202114
11 202313
12 202011
13 202110
14 202310
15 201310
16 202210
17 202210
18 20139
19 20239
20 20218

About Haiming Ma

Haiming Ma is a scholar working on Molecular Biology, Cancer Research, Genetics, Physiology and Animal Science and Zoology, having authored 51 papers that have together received 473 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (19 papers), Genomics and Phylogenetic Studies (11 papers), Genetic and phenotypic traits in livestock (8 papers), Adipose Tissue and Metabolism (8 papers), Machine Learning in Bioinformatics (8 papers), Circular RNAs in diseases (7 papers), MicroRNA in disease regulation (7 papers) and RNA and protein synthesis mechanisms (5 papers). The work is most often cited by research in Cancer Research (117 citations), Animal Science and Zoology (85 citations), Genetics (103 citations), Molecular Biology (239 citations) and Physiology (77 citations). Haiming Ma has collaborated with scholars based in China, Estonia and United States. Frequent co-authors include Xing-Li Xu, Yang Hu, Jun Jiang, Xiujuan Fu, Jun He, Xu Dong, Kang Xu, Qinghua Zeng, Ming Yang and Shannon Lee. Their work appears in journals such as Genes, Biology, International Journal of Molecular Sciences, Animals and BMC Genomics.

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.

Explore authors with similar magnitude of impact