Mile Šikić
Impact in
- Molecular Biology top 2%
- Genomics and Phylogenetic Studies
- RNA and protein synthesis mechanisms
- Protein Structure and Dynamics
- Machine Learning in Bioinformatics
- RNA modifications and cancer
- Molecular Medicine top 5%
Papers in
-
- Genomics and Phylogenetic Studies 26
- RNA and protein synthesis mechanisms 17
- Machine Learning in Bioinformatics 6
- Protein Structure and Dynamics 5
- RNA modifications and cancer 5
- Co-authors
- Robert VaserNiranjan NagarajanIvan SovićPauline C. NgSwarnaseetha AdusumalliSanja TomićKristian VlahovičekIvan Dokmanić
- Journals
- Bioinformatics (5 papers)Nature Communications (3 papers)Nucleic Acids Research (2 papers)Genome Research (2 papers)Information Sciences (1 paper)
- Partner nations
- CroatiaSingaporeUnited States
In The Last Decade
Mile Šikić
45 papers receiving 4.3k citations
Hit Papers
Peers
Comparison fields: 5 of 167
- Molecular Biology 2.9k
- Molecular Medicine 165
- Endocrinology 158
- Genetics 766
- Ecology 693
Countries citing papers authored by Mile Šikić
This map shows the geographic impact of Mile Šikić'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 Mile Šikić with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mile Šikić more than expected).
Fields of papers citing papers by Mile Šikić
This network shows the impact of papers produced by Mile Šikić. 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 Mile Šikić. The network helps show where Mile Šikić may publish in the future.
Co-authors
The 25 scholars most cited alongside Mile Šikić, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 15 | |
| 2 | 2024 | 13 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 1 | |
| 6 | 2023 | 1 | |
| 7 | Time- and memory-efficient genome assembly with Raven Hit paper breakdown → | 2021 | 211 |
| 8 | 2017 | 46 | |
| 9 | 2016 | 131 | |
| 10 | 2016 | 20 | |
| 11 | 2016 | 37 | |
| 12 | 2016 | 245 | |
| 13 | 2015 | 9 | |
| 14 | SIFT missense predictions for genomes Hit paper breakdown → | 2015 | 873 |
| 15 | Approaches to DNA de novo assembly | 2013 | 3 |
| 16 | Protein database search optimization based on CUDA and MPI | 2013 | 1 |
| 17 | 2011 | 4 | |
| 18 | 2011 | 1 | |
| 19 | Parallel Protein Docking Tool | 2010 | 1 |
| 20 | 2008 | 196 |
About Mile Šikić
Mile Šikić is a scholar working on Modeling and Simulation, Molecular Biology, Statistical and Nonlinear Physics, Ecology and Artificial Intelligence, having authored 46 papers that have together received 4.4k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (26 papers), RNA and protein synthesis mechanisms (17 papers), Machine Learning in Bioinformatics (6 papers), Complex Network Analysis Techniques (6 papers), Protein Structure and Dynamics (5 papers), Opinion Dynamics and Social Influence (5 papers), RNA modifications and cancer (5 papers) and Algorithms and Data Compression (5 papers). The work is most often cited by research in Molecular Biology (2.9k citations), Molecular Medicine (165 citations), Endocrinology (158 citations), Genetics (766 citations) and Ecology (693 citations). Mile Šikić has collaborated with scholars based in Croatia, Singapore and United States. Frequent co-authors include Robert Vaser, Niranjan Nagarajan, Ivan Sović, Pauline C. Ng, Swarnaseetha Adusumalli, Sanja Tomić, Kristian Vlahoviček, Ivan Dokmanić, Swaine L. Chen and Andreas Wilm. Their work appears in journals such as Bioinformatics, Nature Communications, Nucleic Acids Research, Genome Research and Information Sciences.
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.