Isabel Rojas

1.4k citations
39 papers · 1.0k · h-index 17

Impact in

Papers in

    • Biomedical Text Mining and Ontologies 15
    • Bioinformatics and Genomic Networks 12
    • Microbial Metabolic Engineering and Bioproduction 11
    • Gene Regulatory Network Analysis 9
    • Semantic Web and Ontologies 12
    • Natural Language Processing Techniques 4

Isabel Rojas

38 papers receiving 953 citations

Peers

Isabel Rojas
Comparison fields: 5 of 101
  • Molecular Biology 625
  • Information Systems and Management 46
  • Artificial Intelligence 207
  • Human-Computer Interaction 26
  • Computational Theory and Mathematics 66
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Citations per field
00.5×2.9×
Paul A. Stewart · 1×
Citations per year

Countries citing papers authored by Isabel Rojas

Since Specialization
Citations

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

Fields of papers citing papers by Isabel Rojas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011198
2 2005112
3 200194
4
Unsupervised learning of semantic relations between concepts of a molecular biology ontology
200582
5 200554
6 200449
7 200646
8 200146
9
Storing and annotating of kinetic data.
200730
10 200729
11 200825
12 200420
13 200319
14 200418
15
Unsupervised Learning of Semantic Relations for Molecular Biology Ontologies
200818
16 201016
17 200216
18 201315
19 201414
20 199513

About Isabel Rojas

Isabel Rojas is a scholar working on Molecular Biology, Artificial Intelligence, Surgery, Information Systems and Pulmonary and Respiratory Medicine, having authored 39 papers that have together received 1.0k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (15 papers), Bioinformatics and Genomic Networks (12 papers), Semantic Web and Ontologies (12 papers), Microbial Metabolic Engineering and Bioproduction (11 papers), Gene Regulatory Network Analysis (9 papers), Natural Language Processing Techniques (4 papers), Service-Oriented Architecture and Web Services (2 papers) and Head and Neck Surgical Oncology (2 papers). The work is most often cited by research in Molecular Biology (625 citations), Information Systems and Management (46 citations), Artificial Intelligence (207 citations), Human-Computer Interaction (26 citations) and Computational Theory and Mathematics (66 citations). Isabel Rojas has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Jasmin Šarić, Moritz Y. Becker, Ulrike Wittig, Andreas Weidemann, Renate Kania, Martin Golebiewski, Saqib Mir, Lars Juhl Jensen, Peer Bork and Aldo Gangemi. Their work appears in journals such as Bioinformatics, Comparative and Functional Genomics, BMC Systems Biology, FEBS Journal and IEEE Intelligent Systems.

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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