Lang Li

6.9k citations
158 papers · 5.2k · h-index 39

Impact in

  • Pharmacology top 0.5%
    • Pharmacogenetics and Drug Metabolism
  • Oncology top 2%
    • Cancer Treatment and Pharmacology
    • Drug Transport and Resistance Mechanisms

Papers in

    • Biomedical Text Mining and Ontologies 16
    • Gene expression and cancer classification 12
    • Genomics and Chromatin Dynamics 10
    • Cancer Treatment and Pharmacology 8

Lang Li

154 papers receiving 5.1k citations

Peers

Lang Li
Comparison fields: 5 of 158
  • Pharmacology 565
  • Oncology 1.1k
  • Cancer Research 474
  • Family Practice 51
  • Toxicology 99
Replace Ross A. McKinnon with:
Ross A. McKinnon Australia
Ewan R. Pearson United Kingdom
Donald E. Mager United States
Todd C. Skaar United States
Jorge Plutzky United States
Jesse J. Swen Netherlands
Russell A. Wilke United States
James M. Rae United States
Michael J. Sorich Australia
Jogarao Gobburu United States
Lang Li relative to Ross A. McKinnon Australia Ross A. McKinnon's profile →
Citations per field
00.5×3.9×
Ross A. McKinnon · 1×
Citations per year

Countries citing papers authored by Lang Li

Since Specialization
Citations

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

Fields of papers citing papers by Lang Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 158 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012290
2 2004226
3 2007184
4 2015178
5 2003172
6 2004160
7 2015154
8 2010149
9 2010142
10 2006119
11 2006112
12 2012103
13 2007100
14 2003100
15 200699
16 201097
17 200796
18 200687
19 200384
20 200480

About Lang Li

Lang Li is a scholar working on Molecular Biology, Oncology, Pharmacology, Computational Theory and Mathematics and Genetics, having authored 158 papers that have together received 5.2k indexed citations. Recurring topics across this work include Pharmacogenetics and Drug Metabolism (20 papers), Computational Drug Discovery Methods (19 papers), Biomedical Text Mining and Ontologies (16 papers), Gene expression and cancer classification (12 papers), Estrogen and related hormone effects (11 papers), Genomics and Chromatin Dynamics (10 papers), Statistical Methods in Clinical Trials (10 papers) and Cancer Treatment and Pharmacology (8 papers). The work is most often cited by research in Pharmacology (565 citations), Oncology (1.1k citations), Cancer Research (474 citations), Family Practice (51 citations) and Toxicology (99 citations). Lang Li has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include David A. Flockhart, John N. Eble, Stephen D. Hall, Michael O. Koch, Liang Cheng, Zeruesenay Desta, Todd C. Skaar, Anne Nguyen, Thomas M. Ulbright and Anna Maria Storniolo. Their work appears in journals such as BMC Genomics, Breast Cancer Research and Treatment, PLoS ONE, Clinical Cancer Research and Journal of Clinical Oncology.

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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