T.-K. Li

2.1k citations
26 papers · 1.6k indexed · h-index 21

T.-K. Li

26 papers receiving 1.5k citations

Peers

T.-K. Li
Comparison fields: 5 of 82
  • Cellular and Molecular Neuroscience 1.2k
  • Behavioral Neuroscience 149
  • Endocrine and Autonomic Systems 111
  • Molecular Biology 709
  • Nutrition and Dietetics 148
Replace M.B. Waller with:
M.B. Waller United States
Wanda Dyr Poland
Christopher L. Hubbell United States
T.‐K. Li United States
Zavie W. Brown Canada
Peter W. Marinelli Canada
Jaime L. Diaz‐Granados United States
Anna Molander Sweden
Nancy E. Badia‐Elder United States
R. Bruce Holman United Kingdom
T.-K. Li relative to M.B. Waller United States M.B. Waller's profile →
Citations per field
00.5×4.8×
M.B. Waller · 1×
Citations per year

Countries citing papers authored by T.-K. Li

Since Specialization
Citations

This map shows the geographic impact of T.-K. 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 T.-K. Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T.-K. Li more than expected).

Fields of papers citing papers by T.-K. Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 2006109
2 200497
3 200219
4
Defining alcohol-related phenotypes in humans. The Collaborative Study on the Genetics of Alcoholism.
200258
5 200116
6 200035
7 199964
8 199918
9 199940
10 1995128
11 199599
12 199438
13 199464
14 199317
15
An experimental approach to understanding the genetic and neurobiological basis of alcoholism.
19932
16 199228
17 1991190
18 199167
19 198847
20 1988117

About T.-K. Li

T.-K. Li is a scholar working on Cellular and Molecular Neuroscience, Behavioral Neuroscience, Biochemistry, Sensory Systems and Physiology, having authored 26 papers that have together received 1.6k indexed citations. Recurring topics across this work include Neurotransmitter Receptor Influence on Behavior (18 papers), Receptor Mechanisms and Signaling (8 papers), Neuroscience and Neuropharmacology Research (7 papers), Neuropeptides and Animal Physiology (5 papers), Stress Responses and Cortisol (3 papers), Peroxisome Proliferator-Activated Receptors (3 papers), Adipose Tissue and Metabolism (3 papers) and Genetic Mapping and Diversity in Plants and Animals (3 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (1.2k citations), Behavioral Neuroscience (149 citations), Endocrine and Autonomic Systems (111 citations), Molecular Biology (709 citations) and Nutrition and Dietetics (148 citations). T.-K. Li has collaborated with scholars based in United States, Sweden and Hong Kong. Frequent co-authors include Lawrence Lumeng, Janice C. Froehlich, William J. McBride, James M. Murphy, Suchitra Krishnan‐Sarin, Philip S. Portoghese, Darcie L. Kurtz, Cindy L. Ehlers, Robert B. Stewart and Charles B. Nemeroff. Their work appears in journals such as Psychopharmacology, Pharmacology Biochemistry and Behavior, Journal of Pharmacology and Experimental Therapeutics, Journal of Neuroscience and Neuroscience.

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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