Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
A Tutorial for Competent Memetic Algorithms: Model, Taxonomy, and Design Issues
2005520 citationsNatalio Krasnogor, James E. Smithprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Natalio Krasnogor
Since
Specialization
Citations
This map shows the geographic impact of Natalio Krasnogor'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 Natalio Krasnogor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Natalio Krasnogor more than expected).
Fields of papers citing papers by Natalio Krasnogor
This network shows the impact of papers produced by Natalio Krasnogor. 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 Natalio Krasnogor. The network helps show where Natalio Krasnogor may publish in the future.
Co-authorship network of co-authors of Natalio Krasnogor
This figure shows the co-authorship network connecting the top 25 collaborators of Natalio Krasnogor.
A scholar is included among the top collaborators of Natalio Krasnogor 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 Natalio Krasnogor. Natalio Krasnogor is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Costanza, Jole, Vincenzo Cutello, Luca Zammataro, et al.. (2011). Effective calibration of artificial gene regulatory networks.. 39–46.1 indexed citations
12.
Antczak, Maciej, et al.. (2011). DomAns - pattern based method for protein domain boundaries prediction and analysis. Foundations of Computing and Decision Sciences. 35–56.2 indexed citations
13.
Glaab, Enrico, Jonathan M. Garibaldi, & Natalio Krasnogor. (2010). Learning pathway-based decision rules to classify microarray cancer samples. Open Repository and Bibliography (University of Luxembourg). 123–134.5 indexed citations
14.
Krasnogor, Natalio, Giuseppe Nicosia, Mario Pavone, & David A. Pelta. (2008). Nature Inspired Cooperative Strategies for Optimization (NICSO 2007) (Studies in Computational Intelligence) (Studies in Computational Intelligence) XXXX. Springer eBooks.10 indexed citations
15.
Pelta, David A., Juan R. González, & Natalio Krasnogor. (2005). Protein Structure Comparison through Fuzzy Contact Maps and the Universal Similarity Metric. European Society for Fuzzy Logic and Technology Conference. 1124–1129.9 indexed citations
16.
Krasnogor, Natalio, et al.. (2005). An Appealing Computational Mechanism Drawn from Bacterial Quorum Sensing.. Bulletin of the European Association for Theoretical Computer Science. 85. 135–148.13 indexed citations
17.
Hart, William E., et al.. (2002). Alignment of protein structures with a memetic evolutionary algorithm. UWE Research Repository (UWE Bristol). 1027–1034.23 indexed citations
18.
Krasnogor, Natalio & James E. Smith. (2001). Emergence of profitable search strategies based on a simple inheritance mechanism. UWE Research Repository (UWE Bristol). 432–439.60 indexed citations
19.
Krasnogor, Natalio & James E. Smith. (2000). A Memetic Algorithm with self-adaptive local search: TSP as a case study. UWE Research Repository (UWE Bristol). 987–994.105 indexed citations
20.
Krasnogor, Natalio, William E. Hart, James E. Smith, & David A. Pelta. (1999). Protein structure prediction with evolutionary algorithms. UWE Research Repository (UWE Bristol). 1596–1601.74 indexed citations
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.