Sipko van Dam

2.5k citations
17 papers · 1.0k indexed · 1 hit paper · h-index 9
Topics
Bioinformatics and Genomic Networks (5 papers)GDF15 and Related Biomarkers (3 papers)RNA Research and Splicing (3 papers)

In The Last Decade

Sipko van Dam

16 papers receiving 1.0k citations

Hit Papers

Gene co-expression analysis for functional classification...20162026201920222016200400600

Peers

Sipko van Dam
Comparison fields: 5 of 110
  • Molecular Biology 736
  • Genetics 125
  • Cancer Research 119
  • Physiology 119
  • Plant Science 83
Replace Lina Wadi with:
Lina Wadi Canada
Robin Haw Canada
Celia Pilar Martinez‐Jimenez Germany
Karolina Pakos‐Zebrucka Ireland
Ming-Tsan Su Taiwan
Satoshi Tsukamoto Japan
Boyang Chu United States
Claudia Dall’Armi United States
Abhijeet R. Sonawane United States
Sipko van Dam relative to Lina Wadi Canada Lina Wadi's profile →
Citations per field
00.5×5.5×
Lina Wadi · 1×
Citations per year

Countries citing papers authored by Sipko van Dam

Since Specialization
Citations

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

Fields of papers citing papers by Sipko van Dam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sipko van Dam. 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 Sipko van Dam. The network helps show where Sipko van Dam may publish in the future.

Co-authorship network of co-authors of Sipko van Dam

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

All Works

17 of 17 papers shown
#WorkIndexed citations
1 0
2 5
3 1
4 4
5 8
6 4
7 4
8 2
9 11
10 3
11
Gene co-expression analysis for functional classification and gene–disease predictionsbreakdown →
666
12 80
13 45
14 85
15 61
16 52
17 15

About Sipko van Dam

Sipko van Dam is a scholar working on Aging, Rheumatology and Endocrine and Autonomic Systems, having authored 17 papers that have together received 1.0k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (5 papers), GDF15 and Related Biomarkers (3 papers) and RNA Research and Splicing (3 papers). The work is most often cited by research in Aging (79 citations), Molecular Biology (736 citations) and Cancer Research (119 citations). Sipko van Dam has collaborated with scholars based in Netherlands, United Kingdom and United States. Frequent co-authors include João Pedro de Magalhães, Urmo Võsa, Adriaan van der Graaf, Lude Franke, Thomas Craig, Shona H. Wood, Anis Larbi, Gianni Monaco, Daniel Wuttke and Susan Clarke. Their work appears in journals such as Nucleic Acids Research, Bioinformatics and Scientific Reports.

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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