Daniele Catanzaro

581 total citations
34 papers, 354 citations indexed

About

Daniele Catanzaro is a scholar working on Genetics, Molecular Biology and Plant Science. According to data from OpenAlex, Daniele Catanzaro has authored 34 papers receiving a total of 354 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Genetics, 20 papers in Molecular Biology and 9 papers in Plant Science. Recurrent topics in Daniele Catanzaro's work include Genomics and Phylogenetic Studies (13 papers), Genome Rearrangement Algorithms (12 papers) and Chromosomal and Genetic Variations (8 papers). Daniele Catanzaro is often cited by papers focused on Genomics and Phylogenetic Studies (13 papers), Genome Rearrangement Algorithms (12 papers) and Chromosomal and Genetic Variations (8 papers). Daniele Catanzaro collaborates with scholars based in Belgium, Italy and France. Daniele Catanzaro's co-authors include Martine Labbé, Raffaele Pesenti, Michel C. Milinkovitch, Laurent Gatto, Éric Gourdin, Luı́s Gouveia, Philippe Chévalier, Juan‐José Salazar‐González, Marco Di Summa and Roberto Aringhieri and has published in prestigious journals such as Bioinformatics, PLoS ONE and European Journal of Operational Research.

In The Last Decade

Daniele Catanzaro

32 papers receiving 342 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daniele Catanzaro Belgium 13 123 117 110 44 43 34 354
Marcelo Gonçalves Narciso Brazil 9 90 0.7× 14 0.1× 103 0.9× 73 1.7× 34 0.8× 17 301
Jarosław Byrka Poland 8 26 0.2× 39 0.3× 57 0.5× 9 0.2× 48 1.1× 28 423
Azam Sheikh Muhammad Sweden 9 24 0.2× 172 1.5× 91 0.8× 25 0.6× 69 1.6× 20 388
David Mester Israel 14 236 1.9× 166 1.4× 402 3.7× 304 6.9× 124 2.9× 18 862
Tom Payne United States 10 11 0.1× 148 1.3× 30 0.3× 65 1.5× 43 1.0× 17 406
Nathan P. Lawrence Canada 13 68 0.6× 160 1.4× 30 0.3× 21 0.5× 67 1.6× 24 506
José Ramón Quevedo Spain 13 54 0.4× 72 0.6× 21 0.2× 20 0.5× 304 7.1× 46 600
Jinyuan Chen United States 15 19 0.2× 77 0.7× 10 0.1× 51 1.2× 75 1.7× 61 611
Robert Entriken United States 12 257 2.1× 372 3.2× 20 0.2× 16 0.4× 15 0.3× 23 746

Countries citing papers authored by Daniele Catanzaro

Since Specialization
Citations

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

Fields of papers citing papers by Daniele Catanzaro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniele Catanzaro

This figure shows the co-authorship network connecting the top 25 collaborators of Daniele Catanzaro. A scholar is included among the top collaborators of Daniele Catanzaro 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 Daniele Catanzaro. Daniele Catanzaro is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Catanzaro, Daniele, et al.. (2025). Optimizing over path-length matrices of unrooted binary trees. Mathematical Programming. 215(1-2). 453–505. 1 indexed citations
2.
Catanzaro, Daniele, et al.. (2023). Job scheduling under Time-of-Use energy tariffs for sustainable manufacturing: a survey. European Journal of Operational Research. 308(3). 1091–1109. 18 indexed citations
3.
Catanzaro, Daniele, et al.. (2023). Deep Reinforcement Learning for inventory optimization with non-stationary uncertain demand. European Journal of Operational Research. 314(2). 433–445. 26 indexed citations
4.
Catanzaro, Daniele, et al.. (2023). An evolution strategy approach for the balanced minimum evolution problem. Bioinformatics. 39(11). 1 indexed citations
5.
Catanzaro, Daniele, et al.. (2015). Max point-tolerance graphs. Discrete Applied Mathematics. 216. 84–97. 16 indexed citations
6.
Catanzaro, Daniele, Stanley E. Shackney, Alejandro A. Schäffer, & Russell Schwartz. (2015). Classifying the Progression of Ductal Carcinoma from Single-Cell Sampled Data via Integer Linear Programming: A Case Study. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 13(4). 643–655. 7 indexed citations
7.
Catanzaro, Daniele, Luı́s Gouveia, & Martine Labbé. (2015). Improved integer linear programming formulations for the job Sequencing and tool Switching Problem. European Journal of Operational Research. 244(3). 766–777. 29 indexed citations
8.
Catanzaro, Daniele, Martine Labbé, & Bjarni V. Halldórsson. (2013). An Integer Programming Formulation of the Parsimonious Loss of Heterozygosity Problem. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 10(6). 1391–1402. 2 indexed citations
9.
Catanzaro, Daniele, R. Ravi, & Russell Schwartz. (2013). A mixed integer linear programming model to reconstruct phylogenies from single nucleotide polymorphism haplotypes under the maximum parsimony criterion. Algorithms for Molecular Biology. 8(1). 3–3. 3 indexed citations
10.
Catanzaro, Daniele, et al.. (2013). The balanced minimum evolution problem under uncertain data. Discrete Applied Mathematics. 161(13-14). 1789–1804. 3 indexed citations
11.
Catanzaro, Daniele, et al.. (2011). A Class Representative Model for Pure Parsimony Haplotyping under Uncertain Data. PLoS ONE. 6(3). e17937–e17937. 1 indexed citations
12.
Aringhieri, Roberto, Daniele Catanzaro, & Marco Di Summa. (2011). Optimal solutions for the balanced minimum evolution problem. Computers & Operations Research. 38(12). 1845–1854. 9 indexed citations
13.
Catanzaro, Daniele, et al.. (2011). Reduction approaches for robust shortest path problems. Computers & Operations Research. 38(11). 1610–1619. 25 indexed citations
14.
Catanzaro, Daniele, Martine Labbé, Raffaele Pesenti, & Juan‐José Salazar‐González. (2011). The Balanced Minimum Evolution Problem. INFORMS journal on computing. 24(2). 276–294. 19 indexed citations
15.
Catanzaro, Daniele, et al.. (2010). Computer-aided human leukocyte antigen association studies: A case study for psoriasis and severe alopecia areata. Human Immunology. 71(8). 783–788. 6 indexed citations
16.
Catanzaro, Daniele, et al.. (2010). A branch-and-cut algorithm for the partitioning-hub location-routing problem. Computers & Operations Research. 38(2). 539–549. 41 indexed citations
17.
Aringhieri, Roberto, Chiara Braghin, & Daniele Catanzaro. (2008). An Exact Approach for solving the Balanced Minimum Evolution Problem.. 48–51.
18.
Catanzaro, Daniele. (2008). The minimum evolution problem: Overview and classification. Networks. 53(2). 112–125. 19 indexed citations
19.
Catanzaro, Daniele, et al.. (2007). An ant colony optimization algorithm for phylogenetic estimation under the minimum evolution principle. BMC Evolutionary Biology. 7(1). 228–228. 3 indexed citations
20.
Catanzaro, Daniele, Raffaele Pesenti, & Michel C. Milinkovitch. (2006). A non-linear optimization procedure to estimate distances and instantaneous substitution rate matrices under the GTR model. Bioinformatics. 22(6). 708–715. 18 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.

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