Filip Miljković
- Computational Theory and Mathematics top 1%
- Molecular Biology
- Materials Chemistry
- Organic Chemistry
- Pharmacology top 10%
- Co-authors
- Jürgen BajorathHaiping LuBino JohnRaquel Rodríguez-PérezHuabin HuBeth WilliamsonNigel GreeneJovana B. Veselinović
- Topics
- Computational Drug Discovery Methods (36 papers)Microbial Natural Products and Biosynthesis (11 papers)Protein Structure and Dynamics (9 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of Medicinal ChemistryMolecules
- Partner nations
- GermanySwedenUnited States
In The Last Decade
Filip Miljković
41 papers receiving 788 citations
Hit Papers
Peers
Comparison fields: 5 of 100
- Computational Theory and Mathematics 554
- Molecular Biology 460
- Materials Chemistry 163
- Organic Chemistry 97
- Pharmacology 91
Countries citing papers authored by Filip Miljković
This map shows the geographic impact of Filip Miljković'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 Filip Miljković with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Filip Miljković more than expected).
Fields of papers citing papers by Filip Miljković
This network shows the impact of papers produced by Filip Miljković. 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 Filip Miljković. The network helps show where Filip Miljković may publish in the future.
Co-authorship network of co-authors of Filip Miljković
This figure shows the co-authorship network connecting the top 25 collaborators of Filip Miljković. A scholar is included among the top collaborators of Filip Miljković 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 Filip Miljković. Filip Miljković is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 5 | |
| 6 | 6 | |
| 7 | 10 | |
| 8 | Interpretable bilinear attention network with domain adaptation improves drug–target predictionbreakdown → | 170 |
| 9 | 10 | |
| 10 | 46 | |
| 11 | 22 | |
| 12 | 9 | |
| 13 | 12 | |
| 14 | 25 | |
| 15 | 7 | |
| 16 | 2 | |
| 17 | 30 | |
| 18 | 59 | |
| 19 | 15 | |
| 20 | 9 |
About Filip Miljković
Filip Miljković is a scholar working on Computational Theory and Mathematics, Pharmacology and Pharmacology, having authored 43 papers that have together received 806 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (36 papers), Microbial Natural Products and Biosynthesis (11 papers) and Protein Structure and Dynamics (9 papers). The work is most often cited by research in Computational Theory and Mathematics (554 citations), Pharmacology (71 citations) and Molecular Biology (460 citations). Filip Miljković has collaborated with scholars based in Germany, Sweden and United States. Frequent co-authors include Jürgen Bajorath, Haiping Lu, Bino John, Raquel Rodríguez-Pérez, Huabin Hu, Beth Williamson, Nigel Greene, Jovana B. Veselinović, Andrey A. Toropov and Alla P. Toropova. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of Medicinal Chemistry and Molecules.
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.