Ioannis Filippis
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- Protein Structure and Dynamics 7
- Bioinformatics and Genomic Networks 3
- RNA and protein synthesis mechanisms 3
- Genomics and Phylogenetic Studies 3
- Machine Learning in Bioinformatics 2
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- Computational Drug Discovery Methods 3
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- Enzyme Structure and Function 2
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- Mass Spectrometry Techniques and Applications 2
- Co-authors
- Michael J.E. SternbergLawrence A. KelleyChristopher M. YatesMichael LappéJosé M. DuarteHenning StehrJoe G. GreenerNataša Pržulj
- Journals
- The Plant Journal (2 papers)BMC Bioinformatics (2 papers)Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences (1 paper)
- Partner nations
- United KingdomGermanyUnited States
In The Last Decade
Ioannis Filippis
12 papers receiving 371 citations
Peers
Comparison fields: 5 of 72
- Molecular Biology 313
- Computational Theory and Mathematics 46
- Genetics 68
- Materials Chemistry 59
- Plant Science 44
Countries citing papers authored by Ioannis Filippis
This map shows the geographic impact of Ioannis Filippis'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 Ioannis Filippis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ioannis Filippis more than expected).
Fields of papers citing papers by Ioannis Filippis
This network shows the impact of papers produced by Ioannis Filippis. 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 Ioannis Filippis. The network helps show where Ioannis Filippis may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ioannis Filippis, 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 | 2017 | 35 | |
| 2 | 2016 | 17 | |
| 3 | 2015 | 9 | |
| 4 | 2014 | 175 | |
| 5 | 2013 | 16 | |
| 6 | 2012 | 5 | |
| 7 | 2010 | 40 | |
| 8 | 2009 | 4 | |
| 9 | 2009 | 28 | |
| 10 | 2009 | 31 | |
| 11 | 2008 | 9 | |
| 12 | 2008 | 12 |
About Ioannis Filippis
Ioannis Filippis is a scholar working on Computational Theory and Mathematics, Biophysics and Molecular Biology, having authored 12 papers that have together received 381 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (7 papers), Computational Drug Discovery Methods (3 papers), Bioinformatics and Genomic Networks (3 papers), RNA and protein synthesis mechanisms (3 papers), Genomics and Phylogenetic Studies (3 papers), Machine Learning in Bioinformatics (2 papers), Enzyme Structure and Function (2 papers) and Mass Spectrometry Techniques and Applications (2 papers). The work is most often cited by research in Molecular Biology (313 citations), Computational Theory and Mathematics (46 citations) and Genetics (68 citations). Ioannis Filippis has collaborated with scholars based in United Kingdom, Germany and United States. Frequent co-authors include Michael J.E. Sternberg, Lawrence A. Kelley, Christopher M. Yates, Michael Lappé, José M. Duarte, Henning Stehr, Joe G. Greener, Nataša Pržulj, Rosa López-Cobollo and Tijana Milenković. Their work appears in journals such as The Plant Journal, BMC Bioinformatics, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, Genome Medicine 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.