William Wierda

998 citations
11 papers · 609 · h-index 8

Impact in

  • Hematology top 2%
    • Chronic Myeloid Leukemia Treatments
    • Acute Myeloid Leukemia Research
  • Genetics top 5%
    • Chronic Lymphocytic Leukemia Research

Papers in

    • Chronic Lymphocytic Leukemia Research 6
    • Myeloproliferative Neoplasms: Diagnosis and Treatment 1
    • Chronic Myeloid Leukemia Treatments 7
    • Acute Myeloid Leukemia Research 2

William Wierda

11 papers receiving 597 citations

Peers

William Wierda
Comparison fields: 5 of 43
  • Hematology 407
  • Genetics 287
  • Rheumatology 144
  • Pathology and Forensic Medicine 96
  • Public Health, Environmental and Occupational Health 149
Replace Rainer Krahl with:
Rainer Krahl Germany
Beata Stella‐Hołowiecka Poland
Kirsten Merx Germany
Jerry Radich United States
D Inverardi Italy
M. Hoffknecht Germany
Marie‐Pierre Noël France
Guru Subramanian Guru Murthy United States
Laura Cannella Italy
TL Smith United States
William Wierda relative to Rainer Krahl Germany Rainer Krahl's profile →
Citations per field
00.5×
Rainer Krahl · 1×
Citations per year

Countries citing papers authored by William Wierda

Since Specialization
Citations

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

Fields of papers citing papers by William Wierda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

11 of 11 papers shown
#Work
1 2003153
2 2008138
3 200395
4 200359
5 201358
6 200552
7 201341
8 20089
9 20042
10 20251
11 20071

About William Wierda

William Wierda is a scholar working on Genetics, Hematology, Pathology and Forensic Medicine, Oncology and Organic Chemistry, having authored 11 papers that have together received 609 indexed citations. Recurring topics across this work include Chronic Myeloid Leukemia Treatments (7 papers), Chronic Lymphocytic Leukemia Research (6 papers), Acute Myeloid Leukemia Research (2 papers), Lymphoma Diagnosis and Treatment (2 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (1 paper), Gastrointestinal Tumor Research and Treatment (1 paper), Cancer therapeutics and mechanisms (1 paper) and Neutropenia and Cancer Infections (1 paper). The work is most often cited by research in Hematology (407 citations), Genetics (287 citations), Rheumatology (144 citations), Pathology and Forensic Medicine (96 citations) and Public Health, Environmental and Occupational Health (149 citations). William Wierda has collaborated with scholars based in United States, Japan and Spain. Frequent co-authors include Jörge E. Cortes, Hagop M. Kantarjian, Stefan Faderl, Francis J. Giles, Susan O’Brien, Deborah A. Thomas, Guillermo Garcia‐Manero, Mary Beth Rios, Moshe Talpaz and Michael J. Keating. Their work appears in journals such as Blood, Cancer, American Journal of Hematology, Annals of the American Thoracic Society and Cancers.

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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