Sjors M. Kas

1.0k citations
10 papers · 646 indexed · 1 hit paper · h-index 7
  • Oncology top 10%
    • Galectins and Cancer Biology 1
    • CRISPR and Genetic Engineering 3
    • Epigenetics and DNA Methylation 3
    • Genomics and Chromatin Dynamics 2
    • Glycosylation and Glycoproteins Research 1
    • Cell death mechanisms and regulation 1
    • 14-3-3 protein interactions 1
    • Virus-based gene therapy research 1

Sjors M. Kas

9 papers receiving 641 citations

Hit Papers

Loss of p53 triggers WNT-dependent systemic inflammation ...3612019202620212023100200300

Peers

Sjors M. Kas
Comparison fields: 5 of 70
  • Oncology 258
  • Cancer Research 131
  • Immunology 164
  • Molecular Biology 399
  • Biotechnology 28
Replace Ryosuke Moriai with:
Ryosuke Moriai Japan
Weei-Chin Lin United States
Gyu-Beom Jang South Korea
Shaheen S. Sikandar United States
Maribelis Ruiz United States
Zhengfa Mao China
Joseph Puccini Australia
Grace L. Wong United States
Sonia Mohinta United States
Katia Balmas Bourloud Switzerland
Sjors M. Kas relative to Ryosuke Moriai Japan Ryosuke Moriai's profile →
Citations per field
00.5×10×15×18.3×
Ryosuke Moriai · 1×
Citations per year

Countries citing papers authored by Sjors M. Kas

Since Specialization
Citations

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

Fields of papers citing papers by Sjors M. Kas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sjors M. Kas. 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 Sjors M. Kas. The network helps show where Sjors M. Kas may publish in the future.

Co-authorship network

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

All Works

10 of 10 papers shown
#Work
1 20250
2 20232
3 20208
4
Loss of p53 triggers WNT-dependent systemic inflammation to drive breast cancer metastasisbreakdown →
2019361
5 201830
6 201755
7 20176
8 2016100
9 201132
10 201052

About Sjors M. Kas

Sjors M. Kas is a scholar working on Molecular Biology, Immunology and Dermatology, having authored 10 papers that have together received 646 indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (3 papers), Epigenetics and DNA Methylation (3 papers), Genomics and Chromatin Dynamics (2 papers), Glycosylation and Glycoproteins Research (1 paper), Galectins and Cancer Biology (1 paper), Cell death mechanisms and regulation (1 paper), Virus-based gene therapy research (1 paper) and 14-3-3 protein interactions (1 paper). The work is most often cited by research in Oncology (258 citations), Cancer Research (131 citations) and Immunology (164 citations). Sjors M. Kas has collaborated with scholars based in Netherlands, United Kingdom and Italy. Frequent co-authors include Jos Jonkers, Eva Schut, Anne Paulien Drenth, Lodewyk F.A. Wessels, Martine H. van Miltenburg, Renske de Korte‐Grimmerink, Karin E. de Visser, Ingrid van der Heijden, Ton N. Schumacher and Linda Henneman. Their work appears in journals such as Nature, Nucleic Acids Research and Nature Genetics.

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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