L Chan

1.7k citations
25 papers · 1.4k indexed · h-index 18

Impact in

Papers in

L Chan

25 papers receiving 1.3k citations

Peers

L Chan
Comparison fields: 5 of 83
  • Endocrinology, Diabetes and Metabolism 260
  • Cancer Research 233
  • Biochemistry 109
  • Biochemistry 88
  • Immunology 238
Replace Chao-Yuh Yang with:
Chao-Yuh Yang United States
S Ishibashi Japan
T Mazzone United States
Barbara Pfleger United States
Louise Brissette Canada
T L Swenson United States
Zi-Wei Gu United States
Richard Lawn United States
Winnie Eskild Norway
Stephen J. Demosky United States
L Chan relative to Chao-Yuh Yang United States Chao-Yuh Yang's profile →
Citations per field
00.5×1.5×
Chao-Yuh Yang · 1×
Citations per year

Countries citing papers authored by L Chan

Since Specialization
Citations

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

Fields of papers citing papers by L Chan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20253
2 201416
3 201118
4 200624
5 200446
6
Apolipoprotein B: from editosome to proteasome.
200023
7 1999235
8 1996203
9 199485
10 199325
11 19924
12 19928
13 199119
14
Genetic factors influencing lipoprotein structure: implications for atherosclerosis.
199020
15 198910
16 198918
17 19872
18 198757
19 1986183
20 197711

About L Chan

L Chan is a scholar working on Health Informatics, Endocrinology, Diabetes and Metabolism, Molecular Biology, Genetics and Pharmacy, having authored 25 papers that have together received 1.4k indexed citations. Recurring topics across this work include Lipoproteins and Cardiovascular Health (5 papers), Machine Learning in Bioinformatics (4 papers), RNA regulation and disease (4 papers), RNA Research and Splicing (4 papers), Virus-based gene therapy research (3 papers), RNA modifications and cancer (3 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (3 papers) and RNA and protein synthesis mechanisms (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (260 citations), Cancer Research (233 citations), Biochemistry (109 citations), Biochemistry (88 citations) and Immunology (238 citations). L Chan has collaborated with scholars based in United States, Netherlands and Belgium. Frequent co-authors include Juan Guevara, Han-Seob Kim, Wen‐Hsiung Li, Chao Yang, Paul P. Lau, Antonio M. Gotto, Guido Verhoeven, Antonio M. Gotto, Edward E. Herderick and Hartmut Kühn. Their work appears in journals such as Gene Therapy, Journal of Lipid Research, Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Seminars in Liver Disease.

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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