Morris A. Swertz

63.2k citations
118 papers · 4.5k indexed · 1 hit paper · h-index 39
  • Aging top 2%
  • Genetics top 1%
    • Genomics and Rare Diseases 18
    • Genomic variations and chromosomal abnormalities 11
    • Genetic Associations and Epidemiology 11
    • Biomedical Text Mining and Ontologies 20
    • Bioinformatics and Genomic Networks 20
    • Gene expression and cancer classification 15
    • Genomics and Phylogenetic Studies 13
    • Scientific Computing and Data Management 16

Morris A. Swertz

114 papers receiving 4.5k citations

Hit Papers

Cohort Profile: LifeLines, a three-generation cohort stud...5462014202620182022100200300400500

Peers

Morris A. Swertz
Comparison fields: 5 of 182
  • Aging 134
  • Genetics 1.3k
  • Molecular Biology 2.1k
  • Cancer Research 344
  • Information Systems and Management 154
Replace Mario Falchi with:
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Morris A. Swertz relative to Mario Falchi United Kingdom Mario Falchi's profile →
Citations per field
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Mario Falchi · 1×
Citations per year

Countries citing papers authored by Morris A. Swertz

Since Specialization
Citations

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

Fields of papers citing papers by Morris A. Swertz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Morris A. Swertz. 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 Morris A. Swertz. The network helps show where Morris A. Swertz may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20242
2 20241
3 20238
4 20232
5 202216
6 202215
7 202110
8 202038
9 202016
10 201962
11 201711
12 201566
13 2015129
14 2015238
15 20151
16 20137
17 201216
18
How to kickstart a national biobanking infrastructure – experiences and prospects of BBMRI-NL
20120
19 201114
20 201023

About Morris A. Swertz

Morris A. Swertz is a scholar working on Information Systems and Management, Aging and Genetics, having authored 118 papers that have together received 4.5k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (20 papers), Bioinformatics and Genomic Networks (20 papers), Genomics and Rare Diseases (18 papers), Scientific Computing and Data Management (16 papers), Gene expression and cancer classification (15 papers), Genomics and Phylogenetic Studies (13 papers), Genomic variations and chromosomal abnormalities (11 papers) and Genetic Associations and Epidemiology (11 papers). The work is most often cited by research in Aging (134 citations), Genetics (1.3k citations) and Molecular Biology (2.1k citations). Morris A. Swertz has collaborated with scholars based in Netherlands, United Kingdom and United States. Frequent co-authors include Cisca Wijmenga, Ritsert C. Jansen, Patrick Deelen, Lude Franke, Freerk van Dijk, Rainer Breitling, Ronald P. Stolk, Salome Scholtens, K. Joeri van der Velde and Bruce H. R. Wolffenbuttel. Their work appears in journals such as Nucleic Acids Research, Nature Medicine 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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