Shaw‐Hwa Lo

73 total papers · 1.4k total citations
52 papers, 967 citations indexed

About

Shaw‐Hwa Lo is a scholar working on Genetics, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Shaw‐Hwa Lo has authored 52 papers receiving a total of 967 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Genetics, 16 papers in Molecular Biology and 15 papers in Artificial Intelligence. Recurrent topics in Shaw‐Hwa Lo's work include Genetic Associations and Epidemiology (22 papers), Statistical Methods and Inference (14 papers) and Bioinformatics and Genomic Networks (10 papers). Shaw‐Hwa Lo is often cited by papers focused on Genetic Associations and Epidemiology (22 papers), Statistical Methods and Inference (14 papers) and Bioinformatics and Genomic Networks (10 papers). Shaw‐Hwa Lo collaborates with scholars based in United States, Hong Kong and Taiwan. Shaw‐Hwa Lo's co-authors include Tian Zheng, Kesar Singh, Herman Chernoff, Adeline Lo, Kani Chen, Min‐Te Chao, Inchi Hu, Vicki Addesso, Simon Maybaum and Donald J. McMahon and has published in prestigious journals such as New England Journal of Medicine, Proceedings of the National Academy of Sciences and SHILAP Revista de lepidopterología.

In The Last Decade

Shaw‐Hwa Lo

50 papers receiving 906 citations

Author Peers

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

Author						Papers	Cites
Shaw‐Hwa Lo	332	189	178	172	88	52	967
Mauro Gasparini	276 0.8×	92 0.5×	133 0.7×	110 0.6×	42 0.5×	60	1.1k
Keying Ye	305 0.9×	155 0.8×	199 1.1×	70 0.4×	21 0.2×	67	1.2k
Anuradha Roy	287 0.9×	69 0.4×	126 0.7×	47 0.3×	93 1.1×	58	1.1k
Ying Wu	242 0.7×	158 0.8×	188 1.1×	57 0.3×	65 0.7×	84	999
Dehan Kong	254 0.8×	147 0.8×	125 0.7×	61 0.4×	12 0.1×	55	898
Xin Zhou	124 0.4×	147 0.8×	440 2.5×	46 0.3×	76 0.9×	68	1.2k
Joon Jin Song	124 0.4×	65 0.3×	229 1.3×	73 0.4×	24 0.3×	61	1.2k
Yiwei Zhang	72 0.2×	87 0.5×	262 1.5×	121 0.7×	66 0.8×	77	1.1k
Weimin Huang	283 0.9×	158 0.8×	89 0.5×	13 0.1×	35 0.4×	56	1.2k
Lu Lin	241 0.7×	88 0.5×	127 0.7×	21 0.1×	29 0.3×	50	966

Countries citing papers authored by Shaw‐Hwa Lo

Since Specialization

Citations

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

Fields of papers citing papers by Shaw‐Hwa Lo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shaw‐Hwa Lo. 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 Shaw‐Hwa Lo. The network helps show where Shaw‐Hwa Lo may publish in the future.

Co-authorship network of co-authors of Shaw‐Hwa Lo

This figure shows the co-authorship network connecting the top 25 collaborators of Shaw‐Hwa Lo. A scholar is included among the top collaborators of Shaw‐Hwa Lo 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 Shaw‐Hwa Lo. Shaw‐Hwa Lo 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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