Texas Liver Institute

14.9k citations
328 papers ·

Impact in

  • Hepatology top 2%
    • Hepatitis C virus research
    • Liver Disease and Transplantation
    • Liver Diseases and Immunity
  • Epidemiology top 10%
    • Liver Disease Diagnosis and Treatment
    • Hepatitis B Virus Studies

Papers in

    • Hepatitis C virus research 135
    • Liver Disease and Transplantation 37
    • Liver Diseases and Immunity 28
    • Liver Disease Diagnosis and Treatment 136
    • Hepatitis B Virus Studies 37

Texas Liver Institute

289 papers receiving 13.4k citations

Peers

Texas Liver Institute
Comparison fields: 5 of 149
  • Hepatology 8.8k
  • Epidemiology 8.8k
  • Endocrinology, Diabetes and Metabolism 1.7k
  • Infectious Diseases 1.3k
  • Transplantation 103
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Texas Liver Institute relative to Autoimmune Technologies (United States) United States Autoimmune Technologies (United States)'s profile →
Citations per field
00.5×8.2×
Autoimmune Technologies (United States) · 1×
Citations per year

Countries citing scholars working at Texas Liver Institute

Since Specialization
Citations

This map shows the geographic impact of research produced by authors working at Texas Liver Institute. 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 papers produced at Texas Liver Institute with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Texas Liver Institute more than expected).

Fields of papers published by authors at Texas Liver Institute

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers affiliated with Texas Liver Institute at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Texas Liver Institute at the time of their publication.

About Texas Liver Institute

In recent decades, authors affiliated with Texas Liver Institute have published 328 papers, which have received a total of 14.9k indexed citations . Scholars at this organization have produced 182 papers in Hepatology, 162 papers in Epidemiology, 33 papers in Infectious Diseases, 19 papers in Endocrinology, Diabetes and Metabolism and 13 papers in Rheumatology on the topics of Liver Disease Diagnosis and Treatment (136 papers), Hepatitis C virus research (135 papers), Hepatitis B Virus Studies (37 papers), Liver Disease and Transplantation (37 papers), Liver Diseases and Immunity (28 papers), HIV/AIDS drug development and treatment (26 papers), Diet, Metabolism, and Disease (16 papers) and Systemic Lupus Erythematosus Research (13 papers). Their work is cited by papers focused on Hepatology (8.8k citations), Epidemiology (8.8k citations), Endocrinology, Diabetes and Metabolism (1.7k citations), Infectious Diseases (1.3k citations) and Transplantation (103 citations). Authors at Texas Liver Institute collaborate with scholars in United States, France and United Kingdom and have published in prestigious journals including Journal of Hepatology, The American Journal of Gastroenterology, Hepatology, Liver International and Clinical Gastroenterology and Hepatology. Some of Texas Liver Institute's most productive authors include Eric Lawitz, Fred Poordad, Naim Alkhouri, John G. McHutchison, Arun J. Sanyal, Rohit Loomba, Stephen A. Harrison, Mazen Noureddin, Kris V. Kowdley and Ira M. Jacobson.

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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