Jos de Graaf

2.0k total citations · 1 hit paper
14 papers, 1.4k citations indexed

About

Jos de Graaf is a scholar working on Molecular Biology, Immunology and Cancer Research. According to data from OpenAlex, Jos de Graaf has authored 14 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 6 papers in Immunology and 5 papers in Cancer Research. Recurrent topics in Jos de Graaf's work include Immunotherapy and Immune Responses (3 papers), Cancer Genomics and Diagnostics (3 papers) and Genomics and Rare Diseases (2 papers). Jos de Graaf is often cited by papers focused on Immunotherapy and Immune Responses (3 papers), Cancer Genomics and Diagnostics (3 papers) and Genomics and Rare Diseases (2 papers). Jos de Graaf collaborates with scholars based in Germany, United States and Netherlands. Jos de Graaf's co-authors include Uğur Şahin, Özlem Türeci, Mustafa Diken, Sebastian Boegel, Claudia Paret, Sebastian Kreiter, Martin Löwer, John C. Castle, Valesca Boisguérin and Michael Koslowski and has published in prestigious journals such as Nature Genetics, Bioinformatics and Circulation Research.

In The Last Decade

Jos de Graaf

14 papers receiving 1.4k citations

Hit Papers

Exploiting the Mutanome for Tumor Vaccination 2012 2026 2016 2021 2012 200 400 600

Peers

Jos de Graaf
Jacki Kornbluth United States
Niklas K. Finnberg United States
Garvin L. Warner United States
Nupur Bhattacharya United States
Marieke Griffioen Netherlands
Xinhui Wang United States
Jos de Graaf
Citations per year, relative to Jos de Graaf Jos de Graaf (= 1×) peers Marie‐Françoise Bourgeade

Countries citing papers authored by Jos de Graaf

Since Specialization
Citations

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

Fields of papers citing papers by Jos de Graaf

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jos de Graaf. 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 Jos de Graaf. The network helps show where Jos de Graaf may publish in the future.

Co-authorship network of co-authors of Jos de Graaf

This figure shows the co-authorship network connecting the top 25 collaborators of Jos de Graaf. A scholar is included among the top collaborators of Jos de Graaf 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 Jos de Graaf. Jos de Graaf is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
2.
Becker, Julia Powers, Jos de Graaf, Martin Löwer, et al.. (2020). Integrative analysis of structural variations using short-reads and linked-reads yields highly specific and sensitive predictions. PLoS Computational Biology. 16(11). e1008397–e1008397. 6 indexed citations
3.
Castle, John C., Martin Löewer, Sebastian Boegel, et al.. (2014). Immunomic, genomic and transcriptomic characterization of CT26 colorectal carcinoma. BMC Genomics. 15(1). 190–190. 280 indexed citations
4.
Castle, John C., Martin Löewer, Sebastian Boegel, et al.. (2014). Mutated tumor alleles are expressed according to their DNA frequency. Scientific Reports. 4(1). 4743–4743. 33 indexed citations
5.
Scholtalbers, Jelle, Patrick Sorn, Jos de Graaf, et al.. (2013). Galaxy LIMS for next-generation sequencing. Bioinformatics. 29(9). 1233–1234. 21 indexed citations
6.
Castle, John C., Sebastian Kreiter, Jan Diekmann, et al.. (2012). Exploiting the Mutanome for Tumor Vaccination. Cancer Research. 72(5). 1081–1091. 617 indexed citations breakdown →
7.
Löwer, Martin, Bernhard Y. Renard, Jos de Graaf, et al.. (2012). Confidence-based Somatic Mutation Evaluation and Prioritization. PLoS Computational Biology. 8(9). e1002714–e1002714. 28 indexed citations
8.
Boegel, Sebastian, Martin Löwer, Michael K. E. Schäfer, et al.. (2012). HLA typing from RNA-Seq sequence reads. Genome Medicine. 4(12). 102–102. 170 indexed citations
9.
Kreiter, Sebastian, Jan Diekmann, Martin Löwer, et al.. (2012). P2.06 Exploiting The Mutanome for Tumor Vaccination. Annals of Oncology. 23. v24–v24. 1 indexed citations
10.
Roy, Cindy N., Jos de Graaf, Susanne A. Schneider, et al.. (2004). An Hfe-dependent pathway mediates hyposideremia in response to lipopolysaccharide-induced inflammation in mice. Nature Genetics. 36(5). 481–485. 101 indexed citations
11.
Fontaine, Véronique, Els van der Meijden, Jos de Graaf, Jan ter Schegget, & Linda Struyk. (2000). A Functional NF-κB Binding Site in the Human Papillomavirus Type 16 Long Control Region. Virology. 272(1). 40–49. 39 indexed citations
12.
Weisser, Burkhard, R Locher, Jos de Graaf, & W. Vetter. (1993). Low density lipoprotein subfractions and [Ca2+]i in vascular smooth muscle cells.. Circulation Research. 73(1). 118–124. 23 indexed citations
13.
Huang, Li‐Shin, Jos de Graaf, Margaret E. Cooper, et al.. (1990). Exclusion of linkage between the human apolipoprotein B gene and abetalipoproteinemia.. PubMed. 46(6). 1141–8. 16 indexed citations
14.
Huang, Li‐Shin, Jos de Graaf, & Jan L. Breslow. (1988). ApoB gene MspI RFLP in exon 26 changes amino acid 3611 from Arg to Gln.. Journal of Lipid Research. 29(1). 63–67. 37 indexed citations

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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