Damjan Krstajić

1.3k citations
8 papers · 786 indexed · 1 hit paper · h-index 5
Topics
Computational Drug Discovery Methods (3 papers)Machine Learning in Materials Science (2 papers)Telomeres, Telomerase, and Senescence (2 papers)

In The Last Decade

Damjan Krstajić

8 papers receiving 764 citations

Hit Papers

Cross-validation pitfalls when selecting and assessing re...20142026201820222014200400600

Peers

Damjan Krstajić
Comparison fields: 5 of 179
  • Molecular Biology 132
  • Artificial Intelligence 110
  • Computational Theory and Mathematics 96
  • Radiology, Nuclear Medicine and Imaging 69
  • Analytical Chemistry 64
Replace Ljubomir Buturović with:
Ljubomir Buturović United States
Simon Thomas United Kingdom
Tadayoshi Fushiki Japan
Chuan Lü China
B. Michael Kelm Germany
Bernhard Steiert Germany
Alexandre Perera-Lluna Spain
Zhiyuan Luo United Kingdom
Samantha Riccadonna Italy
Damjan Krstajić relative to Ljubomir Buturović United States Ljubomir Buturović's profile →
Citations per field
00.5×1.5×
Ljubomir Buturović · 1×
Citations per year

Countries citing papers authored by Damjan Krstajić

Since Specialization
Citations

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

Fields of papers citing papers by Damjan Krstajić

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Damjan Krstajić

This figure shows the co-authorship network connecting the top 25 collaborators of Damjan Krstajić. A scholar is included among the top collaborators of Damjan Krstajić 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 Damjan Krstajić. Damjan Krstajić is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
#WorkIndexed citations
1 2
2 14
3 1
4
Cross-validation pitfalls when selecting and assessing regression and classification modelsbreakdown →
701
5 19
6 1
7
Competitive Workflow: novel software architecture for automating drug design.
9
8 39

About Damjan Krstajić

Damjan Krstajić is a scholar working on Computational Theory and Mathematics, Hematology and Information Systems and Management, having authored 8 papers that have together received 786 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (3 papers), Machine Learning in Materials Science (2 papers) and Telomeres, Telomerase, and Senescence (2 papers). The work is most often cited by research in Analytical Chemistry (64 citations), Computational Theory and Mathematics (96 citations) and Health Informatics (8 citations). Damjan Krstajić has collaborated with scholars based in United States, Serbia and Netherlands. Frequent co-authors include David E. Leahy, Ljubomir Buturović, Simon Thomas, Steven J. Enoch, Nenad Filipović, Miloš Ivanović, Miloš Kojić, David J. Loftus, Katharina Fleischhauer and Tao Wang. Their work appears in journals such as Blood, Bone Marrow Transplantation and Journal of Computer-Aided Molecular Design.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026