Michael D. R. Croning

1.7k citations
8 papers · 1.2k indexed · 1 hit paper · h-index 8
Topics
Neuroscience and Neuropharmacology Research (3 papers)Computational Drug Discovery Methods (3 papers)Machine Learning in Bioinformatics (2 papers)

In The Last Decade

Michael D. R. Croning

8 papers receiving 1.2k citations

Hit Papers

Evaluation of methods for the prediction of membrane span...20012026200920172001250500750

Peers

Michael D. R. Croning
Comparison fields: 5 of 98
  • Molecular Biology 777
  • Plant Science 176
  • Cellular and Molecular Neuroscience 154
  • Ecology 99
  • Genetics 93
Replace Christine Kaufmann with:
Christine Kaufmann Germany
Tobias Maier Spain
Xiaotong Luo China
Cristina Chiva Spain
Chenxi Jia China
István Ladunga United States
Mutsumi Sugita Japan
David R. Quilici United States
José C. Novello Brazil
Vitor Oliveira Brazil
Michael D. R. Croning relative to Christine Kaufmann Germany Christine Kaufmann's profile →
Citations per field
00.5×5.8×
Christine Kaufmann · 1×
Citations per year

Countries citing papers authored by Michael D. R. Croning

Since Specialization
Citations

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

Fields of papers citing papers by Michael D. R. Croning

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael D. R. Croning. 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 Michael D. R. Croning. The network helps show where Michael D. R. Croning may publish in the future.

Co-authorship network of co-authors of Michael D. R. Croning

This figure shows the co-authorship network connecting the top 25 collaborators of Michael D. R. Croning. A scholar is included among the top collaborators of Michael D. R. Croning 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 Michael D. R. Croning. Michael D. R. Croning 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 33
2 28
3 42
4 55
5
Evaluation of methods for the prediction of membrane spanning regionsbreakdown →
946
6 20
7 41
8 20

About Michael D. R. Croning

Michael D. R. Croning is a scholar working on Physiology, Cellular and Molecular Neuroscience and Computational Theory and Mathematics, having authored 8 papers that have together received 1.2k indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (3 papers), Computational Drug Discovery Methods (3 papers) and Machine Learning in Bioinformatics (2 papers). The work is most often cited by research in Molecular Biology (777 citations), Cellular and Molecular Neuroscience (154 citations) and Microbiology (47 citations). Michael D. R. Croning has collaborated with scholars based in United Kingdom, United States and Netherlands. Frequent co-authors include Steffen Möller, Rolf Apweiler, Gabriel G. Haddad, Jaak Vilo, Teresa K. Attwood, Anna Gaulton, Man‐Lung Fung, A. David Smith, Nigel R. Newberry and Tyra Zetterström. Their work appears in journals such as Nucleic Acids Research, Bioinformatics and British Journal of Pharmacology.

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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