Daniel Reker

56 papers and 2.5k indexed citations i.

About

Daniel Reker is a scholar working on Molecular Biology, Computational Theory and Mathematics and Pharmacology. According to data from OpenAlex, Daniel Reker has authored 56 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Molecular Biology, 32 papers in Computational Theory and Mathematics and 15 papers in Pharmacology. Recurrent topics in Daniel Reker’s work include Computational Drug Discovery Methods (32 papers), Microbial Natural Products and Biosynthesis (14 papers) and Machine Learning in Materials Science (10 papers). Daniel Reker is often cited by papers focused on Computational Drug Discovery Methods (32 papers), Microbial Natural Products and Biosynthesis (14 papers) and Machine Learning in Materials Science (10 papers). Daniel Reker collaborates with scholars based in Switzerland, United States and Germany. Daniel Reker's co-authors include Gisbert Schneider, Petra Schneider, Tiago Rodrigues, Michael Reutlinger, Gonçalo J. L. Bernardes, J.B. Brown, Giovanni Traverso, Jens Kunze, Emily Hoyt and Anna Maria Perna and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Angewandte Chemie International Edition and Nature Nanotechnology.

In The Last Decade

Co-authorship network of co-authors of Daniel Reker i

Fields of papers citing papers by Daniel Reker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Daniel Reker

Since Specialization
Citations

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

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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