J. Haessler

1.0k citations
7 papers · 147 · h-index 4

Impact in

  • Hematology top 10%
    • Multiple Myeloma Research and Treatments
    • Peptidase Inhibition and Analysis
    • Cancer Treatment and Pharmacology

Papers in

    • Protein Degradation and Inhibitors 4
    • Ubiquitin and proteasome pathways 2
    • Multiple Myeloma Research and Treatments 5

J. Haessler

6 papers receiving 144 citations

Peers

J. Haessler
Comparison fields: 5 of 25
  • Hematology 140
  • Oncology 80
  • Molecular Biology 116
  • Genetics 14
  • Complementary and Manual Therapy 1
Replace José-María Arguiñano with:
José-María Arguiñano Spain
Christopher Maisel United States
Rafael Martínez-Martinez Mexico
Ana-Isabel Teruel Spain
C. Hulin France
Karin H. Herbschleb United Kingdom
S Caltagirone Italy
Sandra Wear United States
R. Alexanian United States
Carol Delaney United States
J. Haessler relative to José-María Arguiñano Spain José-María Arguiñano's profile →
Citations per field
00.5×6.3×
José-María Arguiñano · 1×
Citations per year

Countries citing papers authored by J. Haessler

Since Specialization
Citations

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

Fields of papers citing papers by J. Haessler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

7 of 7 papers shown
#Work
1 2012126
2 200910
3 20085
4 20073
5 20102
6 20101
7 20090

About J. Haessler

J. Haessler is a scholar working on Molecular Biology, Hematology, Oncology, Infectious Diseases and Pathology and Forensic Medicine, having authored 7 papers that have together received 147 indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (5 papers), Protein Degradation and Inhibitors (4 papers), HIV/AIDS drug development and treatment (2 papers), Cancer Treatment and Pharmacology (2 papers), Ubiquitin and proteasome pathways (2 papers), Lymphoma Diagnosis and Treatment (1 paper), Bone health and treatments (1 paper) and Genetic factors in colorectal cancer (1 paper). The work is most often cited by research in Hematology (140 citations), Oncology (80 citations), Molecular Biology (116 citations), Genetics (14 citations) and Complementary and Manual Therapy (1 citation). J. Haessler has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Bart Barlogie, Brian G.M. Durie, John Crowley, Gareth J. Morgan, Michèle Cavo, Philippe Moreau, Pieter Sonneveld, Orhan Sezer, Michel Attal and Juan José Lahuerta. Their work appears in journals such as Journal of Clinical Oncology and Leukemia.

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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