Erinç Merdivan

618 citations
12 papers · 178 indexed · h-index 9
Topics
Computational Drug Discovery Methods (4 papers)Protein Structure and Dynamics (3 papers)Machine Learning in Materials Science (2 papers)
Partner nations
GermanyTürkiyeAustria

In The Last Decade

Erinç Merdivan

11 papers receiving 175 citations

Peers

Erinç Merdivan
Comparison fields: 5 of 83
  • Molecular Biology 51
  • Artificial Intelligence 43
  • Computational Theory and Mathematics 31
  • Biomedical Engineering 26
  • Materials Chemistry 18
Replace Manish K. Gupta with:
Manish K. Gupta India
Yatong Liu China
Zdzisław S. Hippe Poland
Gabriel Idakwo United States
Yashaswi Pathak India
Jun Mao China
Junnan Zhao China
Dennis Feng United States
Xinhao Li China
Ashwin Dhakal United States
Erinç Merdivan relative to Manish K. Gupta India Manish K. Gupta's profile →
Citations per field
00.5×1.5×
Manish K. Gupta · 1×
Citations per year

Countries citing papers authored by Erinç Merdivan

Since Specialization
Citations

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

Fields of papers citing papers by Erinç Merdivan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Erinç Merdivan

This figure shows the co-authorship network connecting the top 25 collaborators of Erinç Merdivan. A scholar is included among the top collaborators of Erinç Merdivan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Erinç Merdivan. Erinç Merdivan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
#WorkIndexed citations
1 6
2 4
3 0
4 17
5 11
6 27
7 13
8 24
9 25
10 8
11 35
12 8

About Erinç Merdivan

Erinç Merdivan is a scholar working on Computational Theory and Mathematics, Computer Vision and Pattern Recognition and Bioengineering, having authored 12 papers that have together received 178 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (4 papers), Protein Structure and Dynamics (3 papers) and Machine Learning in Materials Science (2 papers). The work is most often cited by research in Health Informatics (3 citations), Computational Theory and Mathematics (31 citations) and Analytical Chemistry (15 citations). Erinç Merdivan has collaborated with scholars based in Germany, Türkiye and Austria. Frequent co-authors include Serap Seyhan Bozkurt, Andreas Holzinger, Deepika Singh, Sten Hanke, Marie Piraud, Johannes Kropf, Alessandra Roncaglioni, Alberto Manganaro, Giuseppina Gini and Emilio Benfenati. Their work appears in journals such as Nature Communications, Genome biology and PLoS Computational Biology.

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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