Haibo Luo

96 total papers · 1.2k total citations
61 papers, 697 citations indexed

About

Haibo Luo is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Haibo Luo has authored 61 papers receiving a total of 697 indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Molecular Biology, 39 papers in Genetics and 9 papers in Cancer Research. Recurrent topics in Haibo Luo's work include Forensic and Genetic Research (35 papers), Molecular Biology Techniques and Applications (32 papers) and Genetic diversity and population structure (10 papers). Haibo Luo is often cited by papers focused on Forensic and Genetic Research (35 papers), Molecular Biology Techniques and Applications (32 papers) and Genetic diversity and population structure (10 papers). Haibo Luo collaborates with scholars based in China, Germany and United States. Haibo Luo's co-authors include Yiping Hou, Feng Song, Weibo Liang, Miao Liao, Zheng Wang, Xiong‐Fei Pan, Jing Yan, Wei Wei, Lushun Zhang and Jin Wu and has published in prestigious journals such as PLoS ONE, Scientific Reports and Journal of Colloid and Interface Science.

In The Last Decade

Haibo Luo

56 papers receiving 685 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Haibo Luo 471 406 143 54 34 61 697
Toshimichi Yamamoto 320 0.7× 287 0.7× 29 0.2× 34 0.6× 19 0.6× 58 572
Rodrigo S. Moura‐Neto 300 0.6× 246 0.6× 24 0.2× 24 0.4× 38 1.1× 62 654
Tenzin Gayden 275 0.6× 487 1.2× 65 0.5× 141 2.6× 24 0.7× 36 731
Gavin R. Turbett 295 0.6× 115 0.3× 124 0.9× 15 0.3× 27 0.8× 35 676
Katja Anslinger 441 0.9× 439 1.1× 35 0.2× 81 1.5× 9 0.3× 51 660
Paolo Fattorini 329 0.7× 301 0.7× 45 0.3× 69 1.3× 8 0.2× 66 585
Benjamin Kelly 339 0.7× 203 0.5× 40 0.3× 20 0.4× 46 1.4× 38 572
Rohina Rubicz 165 0.4× 219 0.5× 67 0.5× 43 0.8× 94 2.8× 33 637
Zhipeng Zhao 291 0.6× 136 0.3× 92 0.6× 10 0.2× 9 0.3× 42 707
Silva Da 278 0.6× 421 1.0× 19 0.1× 68 1.3× 40 1.2× 81 785

Countries citing papers authored by Haibo Luo

Since Specialization
Citations

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

Fields of papers citing papers by Haibo Luo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haibo Luo

This figure shows the co-authorship network connecting the top 25 collaborators of Haibo Luo. A scholar is included among the top collaborators of Haibo Luo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Haibo Luo. Haibo Luo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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