Mary E. Vail

819 citations
19 papers · 602 · h-index 12

Impact in

  • Hepatology top 10%
    • Liver physiology and pathology
    • Drug-Induced Hepatotoxicity and Protection

Papers in

Mary E. Vail

19 papers receiving 589 citations

Peers

Mary E. Vail
Comparison fields: 5 of 81
  • Hepatology 82
  • Pharmacology 80
  • Cellular and Molecular Neuroscience 163
  • Cell Biology 114
  • Oncology 163
Replace Suihai Wang with:
Suihai Wang China
Raquel Parı́s Spain
Lindsey N. Jackson United States
Kunihiko Tatsumi Japan
Liangru Contois United States
Simone Radtke Germany
N Li China
Yoshiaki Sunami Germany
Virginie Maire France
Sudhakiranmayi Kuravi United States
Mary E. Vail relative to Suihai Wang China Suihai Wang's profile →
Citations per field
00.5×5.1×
Suihai Wang · 1×
Citations per year

Countries citing papers authored by Mary E. Vail

Since Specialization
Citations

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

Fields of papers citing papers by Mary E. Vail

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mary E. Vail. 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 Mary E. Vail. The network helps show where Mary E. Vail may publish in the future.

Co-authors

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

All Works

19 of 19 papers shown
#Work
1 200185
2 201467
3 200266
4 200255
5 201055
6 201453
7 202041
8
Bcl-2 delays and alters hepatic carcinogenesis induced by transforming growth factor alpha.
200135
9 200234
10 201234
11 202029
12 201418
13 20238
14 20227
15 20105
16 20095
17 20242
18 20112
19 20011

About Mary E. Vail

Mary E. Vail is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Oncology, Hepatology and Information Systems and Management, having authored 19 papers that have together received 602 indexed citations. Recurring topics across this work include Axon Guidance and Neuronal Signaling (8 papers), Angiogenesis and VEGF in Cancer (7 papers), Liver physiology and pathology (5 papers), Cancer-related Molecular Pathways (4 papers), Hippo pathway signaling and YAP/TAZ (3 papers), HER2/EGFR in Cancer Research (3 papers), Scientific Computing and Data Management (3 papers) and Cancer, Hypoxia, and Metabolism (2 papers). The work is most often cited by research in Hepatology (82 citations), Pharmacology (80 citations), Cellular and Molecular Neuroscience (163 citations), Cell Biology (114 citations) and Oncology (163 citations). Mary E. Vail has collaborated with scholars based in Australia, United States and Belgium. Frequent co-authors include Peter W. Janes, Andrew M. Scott, Robert H. Pierce, Nelson Fausto, Martin Lackmann, Lakmali Atapattu, Cynthia C.T. Sprenger, Stephen R. Plymate, K S Evans and N Fausto. Their work appears in journals such as Cancers, Molecular Pharmacology, Oncogene, Cancer Research and Growth Factors.

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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