Julia Haag

440 citations
8 papers · 60 · h-index 4

Impact in

    • Evolution and Paleontology Studies
    • Genetic diversity and population structure

Papers in

    • Genomics and Phylogenetic Studies 5
    • Biomedical Text Mining and Ontologies 1
    • Fractal and DNA sequence analysis 1
    • Genetic diversity and population structure 3
    • Genetic Associations and Epidemiology 1

Julia Haag

7 papers receiving 60 citations

Peers

Julia Haag
Comparison fields: 5 of 27
  • Paleontology 15
  • Genetics 22
  • Molecular Biology 42
  • Sensory Systems 1
  • Molecular Medicine 1
Replace Yueyu Jiang with:
Yueyu Jiang United States
Zhouzhi Wang China
Z. Tu Taiwan
Jae Joseph Russell B. Rodriguez Philippines
Verena Ras South Africa
Cody Parker Germany
Barbara Piasecka Switzerland
Valentín Ruano-Rubio Ireland
Erika Tamm Estonia
Bárbara Sousa da Mota Switzerland
Julia Haag relative to Yueyu Jiang United States Yueyu Jiang's profile →
Citations per field
00.5×
Yueyu Jiang · 1×
Citations per year

Countries citing papers authored by Julia Haag

Since Specialization
Citations

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

Fields of papers citing papers by Julia Haag

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 8 scholars most cited alongside Julia Haag, 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 Julia Haag Line = papers co-authored together Julia Haag links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1 202223
2 202314
3 202313
4 20245
5 20233
6 20211
7 20241
8 20240

About Julia Haag

Julia Haag is a scholar working on Molecular Biology, Genetics, Paleontology, Computer Vision and Pattern Recognition and Aerospace Engineering, having authored 8 papers that have together received 60 indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (5 papers), Evolution and Paleontology Studies (3 papers), Genetic diversity and population structure (3 papers), Robotics and Sensor-Based Localization (1 paper), Soft Robotics and Applications (1 paper), Biomedical Text Mining and Ontologies (1 paper), Fractal and DNA sequence analysis (1 paper) and Genetic Associations and Epidemiology (1 paper). The work is most often cited by research in Paleontology (15 citations), Genetics (22 citations), Molecular Biology (42 citations), Sensory Systems (1 citation) and Molecular Medicine (1 citation). Julia Haag has collaborated with scholars based in Germany, Greece and Czechia. Frequent co-authors include Alexandros Stamatakis, Laurent Jacob, Bastien Boussau, Alexey M. Kozlov, Benoît Morel, Thomas Klenzner, Franziska Mathis-Ullrich and Alexander I. Jordan. Their work appears in journals such as Molecular Biology and Evolution, Frontiers in Surgery and Bioinformatics Advances.

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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