Sander Canisius

4.1k citations
36 papers · 875 · h-index 14

Impact in

Papers in

Sander Canisius

31 papers receiving 832 citations

Peers

Sander Canisius
Comparison fields: 5 of 102
  • Sensory Systems 74
  • Cancer Research 168
  • Artificial Intelligence 190
  • Nutrition and Dietetics 91
  • Molecular Biology 404
Replace Ming Shao with:
Ming Shao China
Jianpeng Chen China
Catherine Leroy France
Hui Cao China
Shiro Kadowaki Japan
Gene Cutler United States
Xianming Wang China
Pouya Khankhanian United States
Thuy Vu United States
Juan Qu China
Sander Canisius relative to Ming Shao China Ming Shao's profile →
Citations per field
00.5×2.9×
Ming Shao · 1×
Citations per year

Countries citing papers authored by Sander Canisius

Since Specialization
Citations

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

Fields of papers citing papers by Sander Canisius

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012176
2
An efficient memory-based morphosyntactic tagger and parser for Dutch
2007115
3 201189
4 201674
5 201959
6 202057
7 202039
8 201338
9 201437
10 201233
11 202019
12 200515
13 201514
14 200614
15
Bootstrapping Information Extraction from Field Books
200712
16 201811
17
Memory-based semantic role labeling: Optimizing features, algorithm, and output
200411
18 200611
19
A Constraint Satisfaction Approach to Dependency Parsing
20078
20 20198

About Sander Canisius

Sander Canisius is a scholar working on Artificial Intelligence, Molecular Biology, Genetics, Oncology and Cancer Research, having authored 36 papers that have together received 875 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (14 papers), Topic Modeling (12 papers), Genomics and Chromatin Dynamics (6 papers), Estrogen and related hormone effects (6 papers), Breast Cancer Treatment Studies (4 papers), Cancer Genomics and Diagnostics (4 papers), Cancer-related Molecular Pathways (4 papers) and Text Readability and Simplification (4 papers). The work is most often cited by research in Sensory Systems (74 citations), Cancer Research (168 citations), Artificial Intelligence (190 citations), Nutrition and Dietetics (91 citations) and Molecular Biology (404 citations). Sander Canisius has collaborated with scholars based in Netherlands, United Kingdom and United States. Frequent co-authors include Lodewyk F.A. Wessels, Antal van den Bosch, Wilbert Zwart, Walter Daelemans, John W.M. Martens, Jason S. Carroll, Marleen Kok, Sabine C. Linn, Vassiliki Theodorou and Jeroen Middelbeek. Their work appears in journals such as European Journal of Cancer, The EMBO Journal, Oncogene, Cancer Research and Clinical Cancer Research.

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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