Marek Tutaj

10.2k citations
26 papers · 584 · h-index 13

Impact in

    • Bioinformatics and Genomic Networks
    • Biomedical Text Mining and Ontologies
    • Gene expression and cancer classification
    • Genomics and Phylogenetic Studies
    • Molecular Biology Techniques and Applications
    • Metabolomics and Mass Spectrometry Studies
    • Genomics and Rare Diseases
    • Genetic Mapping and Diversity in Plants and Animals

Papers in

    • Bioinformatics and Genomic Networks 17
    • Biomedical Text Mining and Ontologies 12
    • Gene expression and cancer classification 8
    • Molecular Biology Techniques and Applications 4
    • Metabolomics and Mass Spectrometry Studies 3
    • Genetic Mapping and Diversity in Plants and Animals 5
    • Genomics and Rare Diseases 3

Marek Tutaj

25 papers receiving 577 citations

Peers

Marek Tutaj
Comparison fields: 5 of 91
  • Molecular Biology 416
  • Genetics 148
  • Aging 7
  • Cancer Research 55
  • Small Animals 17
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Citations per field
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Citations per year

Countries citing papers authored by Marek Tutaj

Since Specialization
Citations

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

Fields of papers citing papers by Marek Tutaj

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014164
2 2019104
3 201465
4 202327
5 201327
6 201623
7 201622
8 201319
9 201218
10 201618
11 201616
12 201116
13 201914
14 20219
15 20139
16 20187
17 20147
18 20234
19 20153
20 20143

About Marek Tutaj

Marek Tutaj is a scholar working on Molecular Biology, Genetics, Artificial Intelligence, Cancer Research and Infectious Diseases, having authored 26 papers that have together received 584 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (17 papers), Biomedical Text Mining and Ontologies (12 papers), Gene expression and cancer classification (8 papers), Genetic Mapping and Diversity in Plants and Animals (5 papers), Molecular Biology Techniques and Applications (4 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Genomics and Rare Diseases (3 papers) and Semantic Web and Ontologies (2 papers). The work is most often cited by research in Molecular Biology (416 citations), Genetics (148 citations), Aging (7 citations), Cancer Research (55 citations) and Small Animals (17 citations). Marek Tutaj has collaborated with scholars based in United States and Brazil. Frequent co-authors include Melinda R. Dwinell, G. Thomas Hayman, Jennifer R. Smith, Mary Shimoyama, Stanley J. F. Laulederkind, Shur‐Jen Wang, Jeff De Pons, Victoria Petri, Rajni Nigam and Elizabeth A. Worthey. Their work appears in journals such as Database, Human Genomics, Physiological Genomics, Genetics and Journal of Biomedical Semantics.

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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