Ivan Matić

9.3k citations
98 papers · 5.8k · h-index 40

Impact in

Papers in

    • DNA Repair Mechanisms 36
    • CRISPR and Genetic Engineering 18
    • RNA and protein synthesis mechanisms 8
    • Evolution and Genetic Dynamics 40
    • Bacterial Genetics and Biotechnology 37

Ivan Matić

96 papers receiving 5.6k citations

Peers

Ivan Matić
Comparison fields: 5 of 152
  • Molecular Medicine 1.0k
  • Endocrinology 650
  • Genetics 2.7k
  • Aging 129
  • Molecular Biology 3.3k
Replace Philippe Bouvet with:
Philippe Bouvet France
Susan M. Rosenberg United States
Remy Chait United States
Daniel H. Haft United States
Balázs Papp Hungary
Colin Manoil United States
Jan‐Willem Veening Netherlands
Vaughn S. Cooper United States
Dirk Bumann Switzerland
Daniel N. Wilson Germany
Ivan Matić relative to Philippe Bouvet France Philippe Bouvet's profile →
Citations per field
00.5×2.8×
Philippe Bouvet · 1×
Citations per year

Countries citing papers authored by Ivan Matić

Since Specialization
Citations

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

Fields of papers citing papers by Ivan Matić

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 98 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003443
2 2001381
3 2013309
4 2006276
5 1997244
6 1995239
7 2004217
8 2000192
9 1995153
10 2002142
11 2002140
12 1996119
13 2008108
14 2007106
15 2004105
16 2018101
17 2001101
18 2018100
19 201093
20 201885

About Ivan Matić

Ivan Matić is a scholar working on Molecular Biology, Genetics, Molecular Medicine, Ecology and Endocrinology, having authored 98 papers that have together received 5.8k indexed citations. Recurring topics across this work include Evolution and Genetic Dynamics (40 papers), Bacterial Genetics and Biotechnology (37 papers), DNA Repair Mechanisms (36 papers), CRISPR and Genetic Engineering (18 papers), Antibiotic Resistance in Bacteria (14 papers), Genetic factors in colorectal cancer (9 papers), Escherichia coli research studies (8 papers) and RNA and protein synthesis mechanisms (8 papers). The work is most often cited by research in Molecular Medicine (1.0k citations), Endocrinology (650 citations), Genetics (2.7k citations), Aging (129 citations) and Molecular Biology (3.3k citations). Ivan Matić has collaborated with scholars based in France, United States and Spain. Frequent co-authors include Miroslav Radman, François Taddéi, Olivier Tenaillon, Érick Denamur, Erick Denamur, Jesús Blázquez, C Rayssiguier, Antoine Giraud, Claude Saint‐Ruf and Marina Elez. Their work appears in journals such as Trends in Microbiology, Journal of Bacteriology, Genetics, Science and Nucleic Acids Research.

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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