Wilma Β. Bias

9.6k citations
160 papers · 7.3k indexed · 1 hit paper · h-index 47
Topics
T-cell and B-cell Immunology (32 papers)Systemic Lupus Erythematosus Research (26 papers)Allergic Rhinitis and Sensitization (17 papers)

In The Last Decade

Wilma Β. Bias

157 papers receiving 6.9k citations

Hit Papers

Marrow Transplantation for Acute Nonlymphocytic Leukemia ...19832026199720111983200400600

Peers

Wilma Β. Bias
Comparison fields: 5 of 122
  • Immunology 2.7k
  • Rheumatology 2.2k
  • Physiology 1.3k
  • Hematology 1.1k
  • Genetics 1.1k
Replace Pierre Youinou with:
Pierre Youinou France
David A. Horwitz United States
Thomas J. Lawley United States
Lorenzo Cosmi Italy
Falk Hiepe Germany
L Aarden Netherlands
Robert I. Fox United States
Francesco Liotta Italy
Francesco Tedesco Italy
Jane H. Buckner United States
Wilma Β. Bias relative to Pierre Youinou France Pierre Youinou's profile →
Citations per field
00.5×1.5×
Pierre Youinou · 1×
Citations per year

Countries citing papers authored by Wilma Β. Bias

Since Specialization
Citations

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

Fields of papers citing papers by Wilma Β. Bias

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wilma Β. Bias. 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 Wilma Β. Bias. The network helps show where Wilma Β. Bias may publish in the future.

Co-authorship network of co-authors of Wilma Β. Bias

This figure shows the co-authorship network connecting the top 25 collaborators of Wilma Β. Bias. A scholar is included among the top collaborators of Wilma Β. Bias based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Wilma Β. Bias. Wilma Β. Bias is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 23
2 9
3 22
4 60
5 48
6 139
7 54
8 76
9 144
10 159
11 3
12 12
13 14
14
Immune response to Amb a VI (Ra6) is associated with HLA-DR5 in allergic humans
1
15 78
16
Selected genetic markers of blood and secretions for youths 12-17 years of age.
3
17 1
18
Human gene mapping 3 : Baltimore Conference (1975)
11
19 4
20 0

About Wilma Β. Bias

Wilma Β. Bias is a scholar working on Immunology and Allergy, Immunology and Rheumatology, having authored 160 papers that have together received 7.3k indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (32 papers), Systemic Lupus Erythematosus Research (26 papers) and Allergic Rhinitis and Sensitization (17 papers). The work is most often cited by research in Immunology and Allergy (911 citations), Rheumatology (2.2k citations) and Immunology (2.7k citations). Wilma Β. Bias has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Frank C. Arnett, David G. Marsh, Thomas T. Provost, Marc C. Hochberg, Deborah A. Meyers, Morris Reichlin, Susan H. Hsu, Elaine L. Alexander, John B. Harley and Mary Betty Stevens. Their work appears in journals such as Science, New England Journal of Medicine and Proceedings of the National Academy of Sciences.

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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