Peter Bias

41 papers receiving 1.0k citations

Peers

Peter Bias
Comparison fields: 5 of 79
  • Oncology 302
  • Rheumatology 155
  • Reproductive Medicine 81
  • Genetics 247
  • Hematology 88
Replace Wanlong Tan with:
Wanlong Tan China
Danish Mazhar United Kingdom
Glenn Tisman United States
Jianhui Zhang China
Salvatore Mancuso Italy
MORITO MARUTA Japan
Tze‐Kiong Er Taiwan
Ioan Nicolae Mateș France
Diljit Kaur‐Knudsen Denmark
Juhani Mäenpää Finland
Peter Bias relative to Wanlong Tan China Wanlong Tan's profile →
Citations per field
00.5×2×3×4.5×
Wanlong Tan · 1×
Citations per year

Countries citing papers authored by Peter Bias

Since Specialization
Citations

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

Fields of papers citing papers by Peter Bias

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008143
2 200785
3 200482
4 200580
5 201375
6 201674
7 200954
8 202045
9 200339
10 200935
11 200833
12 201428
13 200424
14 201322
15 201622
16 200120
17 201419
18 201019
19 201516
20
First clinical results of licofelone (ml3000), an inhibitor of COX-1, COX-2 and 5-LOX, for the treatment of osteoarthritis
200215

About Peter Bias

Peter Bias is a scholar working on Oncology, Hematology, Reproductive Medicine, Genetics and Pharmacology, having authored 42 papers that have together received 1.1k indexed citations. Recurring topics across this work include Neutropenia and Cancer Infections (17 papers), Blood disorders and treatments (6 papers), Erythropoietin and Anemia Treatment (5 papers), Ovarian function and disorders (4 papers), Acute Lymphoblastic Leukemia research (3 papers), Biosimilars and Bioanalytical Methods (3 papers), Osteoarthritis Treatment and Mechanisms (3 papers) and Inflammatory mediators and NSAID effects (3 papers). The work is most often cited by research in Oncology (302 citations), Rheumatology (155 citations), Reproductive Medicine (81 citations), Genetics (247 citations) and Hematology (88 citations). Peter Bias has collaborated with scholars based in Germany, Russia and Ukraine. Frequent co-authors include Anton Buchner, Stefan Laufer, Christoph Behrens, Oleg A. Gladkov, Waldemar Kuczyński, T. Strowitzki, Igor Bondarenko, Heinz Lubenau, Johanne Martel-Pelletier and Boulos Paul Haraoui. Their work appears in journals such as Supportive Care in Cancer, Reproductive Biology and Endocrinology, Current Medical Research and Opinion, Alimentary Pharmacology & Therapeutics and Annals of the Rheumatic Diseases.

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.

Explore authors with similar magnitude of impact