Mario Novković

1.9k citations
24 papers · 1.1k indexed · h-index 18
    • Antimicrobial Peptides and Activities 4
  • Immunology top 5%
    • Immune Cell Function and Interaction 4
    • IL-33, ST2, and ILC Pathways 3
  • Oncology top 10%
    • Mathematical Biology Tumor Growth 4
    • Single-cell and spatial transcriptomics 5
    • Gene Regulatory Network Analysis 4
    • Biochemical and Structural Characterization 4
    • Cell Image Analysis Techniques 4

Mario Novković

24 papers receiving 1.1k citations

Peers

Mario Novković
Comparison fields: 5 of 102
  • Microbiology 241
  • Immunology 591
  • Oncology 268
  • Modeling and Simulation 31
  • Molecular Biology 459
Replace Tobias Keßler with:
Tobias Keßler Germany
B. Angermann United States
Kaori Ide Japan
Peter C. Wilkinson United Kingdom
Rebecca J. Ormsby Australia
Mark R. Gillrie Canada
Liat Stoler‐Barak Israel
Munir Akkaya United States
Victoria Centonze Frohlich United States
Yi Wei China
Mario Novković relative to Tobias Keßler Germany Tobias Keßler's profile →
Citations per field
00.5×3.6×
Tobias Keßler · 1×
Citations per year

Countries citing papers authored by Mario Novković

Since Specialization
Citations

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

Fields of papers citing papers by Mario Novković

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 202214
2 202154
3 202081
4 202046
5 202039
6 201973
7 201843
8 201823
9 201861
10 20181
11 2017103
12 20176
13 201612
14 201668
15 201686
16 201618
17
DADP: the Database of Anuran Defense Peptides
20133
18 201272
19 2012164
20 201146

About Mario Novković

Mario Novković is a scholar working on Modeling and Simulation, Biophysics and Microbiology, having authored 24 papers that have together received 1.1k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (5 papers), Mathematical Biology Tumor Growth (4 papers), Gene Regulatory Network Analysis (4 papers), Antimicrobial Peptides and Activities (4 papers), Immune Cell Function and Interaction (4 papers), Biochemical and Structural Characterization (4 papers), Cell Image Analysis Techniques (4 papers) and IL-33, ST2, and ILC Pathways (3 papers). The work is most often cited by research in Microbiology (241 citations), Immunology (591 citations) and Oncology (268 citations). Mario Novković has collaborated with scholars based in Switzerland, Russia and Germany. Frequent co-authors include Lucas Onder, Burkhard Ludewig, Alessandro Tossi, Davor Juretić, Hung‐Wei Cheng, Viktor Bojović, Elke Scandella, Juraj Simunić, Gennady Bocharov and Natalia Pikor. Their work appears in journals such as Nature Communications, Science Immunology, Nature Immunology, Journal of Allergy and Clinical Immunology and Immunity.

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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