Carlos Cano

1.0k total citations
36 papers, 547 citations indexed

About

Carlos Cano is a scholar working on Molecular Biology, Oncology and Artificial Intelligence. According to data from OpenAlex, Carlos Cano has authored 36 papers receiving a total of 547 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 8 papers in Oncology and 6 papers in Artificial Intelligence. Recurrent topics in Carlos Cano's work include Bioinformatics and Genomic Networks (9 papers), Gene expression and cancer classification (7 papers) and Colorectal Cancer Surgical Treatments (4 papers). Carlos Cano is often cited by papers focused on Bioinformatics and Genomic Networks (9 papers), Gene expression and cancer classification (7 papers) and Colorectal Cancer Surgical Treatments (4 papers). Carlos Cano collaborates with scholars based in Spain, United States and Germany. Carlos Cano's co-authors include Armando Blanco, Víctor Martínez, Carmen Navarro, Waldo Fajardo, Marta Cuadros, Francisco J. López, P. Palma, Ángel Concha, Fernando García and Dennis P. Wall and has published in prestigious journals such as PLoS ONE, Expert Systems with Applications and Frontiers in Immunology.

In The Last Decade

Carlos Cano

33 papers receiving 531 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Carlos Cano Spain 12 359 171 103 82 55 36 547
Amanda C. Schierz United Kingdom 8 532 1.5× 141 0.8× 198 1.9× 56 0.7× 125 2.3× 11 739
Ammar Ammar Netherlands 7 357 1.0× 60 0.4× 52 0.5× 38 0.5× 92 1.7× 19 621
Vasileios Stathias United States 10 388 1.1× 200 1.2× 85 0.8× 31 0.4× 93 1.7× 21 644
Yuqi Wen China 15 432 1.2× 223 1.3× 47 0.5× 47 0.6× 60 1.1× 48 619
Olga Zolotareva Germany 13 416 1.2× 151 0.9× 89 0.9× 97 1.2× 105 1.9× 23 750
Coryandar Gilvary United States 5 264 0.7× 211 1.2× 92 0.9× 183 2.2× 81 1.5× 5 757
Xiaoyang Ruan United States 11 151 0.4× 49 0.3× 111 1.1× 60 0.7× 62 1.1× 20 399
Tor‐Kristian Jenssen Norway 10 1.0k 2.8× 69 0.4× 58 0.6× 169 2.1× 94 1.7× 10 1.2k
Jaegyoon Ahn South Korea 19 883 2.5× 285 1.7× 97 0.9× 99 1.2× 206 3.7× 52 1.2k
Yuansheng Liu China 11 425 1.2× 104 0.6× 38 0.4× 65 0.8× 64 1.2× 23 584

Countries citing papers authored by Carlos Cano

Since Specialization
Citations

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

Fields of papers citing papers by Carlos Cano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Carlos Cano

This figure shows the co-authorship network connecting the top 25 collaborators of Carlos Cano. A scholar is included among the top collaborators of Carlos Cano 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 Carlos Cano. Carlos Cano 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.
Soto, Mauricio, Carlos Cano, Justin Reese, et al.. (2025). Biasing second-order random walk sampling for heterogeneous graph embedding *. 1–8. 1 indexed citations
2.
Cuéllar, Manuel Pegalájar, Carlos Cano, L. G. B. Ruiz, & Lorenzo Servadei. (2023). Time series quantum classifiers with amplitude embedding. Quantum Machine Intelligence. 5(2). 5 indexed citations
3.
Vilchez, José R., Miguel Ángel López‐Nevot, Felipe García, et al.. (2023). Human adipose tissue as a major reservoir of cytomegalovirus-reactive T cells. Frontiers in Immunology. 14. 1303724–1303724.
4.
Cappelletti, Luca, Tommaso Fontana, Elena Casiraghi, et al.. (2023). GRAPE for fast and scalable graph processing and random-walk-based embedding. Nature Computational Science. 3(6). 552–568. 14 indexed citations
5.
Andrades, Álvaro, María Isabel Rodríguez, Carlos Cano, et al.. (2022). Multi-omic alterations of the SWI/SNF complex define a clinical subgroup in lung adenocarcinoma. Clinical Epigenetics. 14(1). 42–42. 4 indexed citations
6.
Ríos‐Arrabal, Sandra, et al.. (2021). Endothelin-1 as a Mediator of Heme Oxygenase-1-Induced Stemness in Colorectal Cancer: Influence of p53. Journal of Personalized Medicine. 11(6). 509–509. 9 indexed citations
7.
Martínez, Víctor, Carmen Navarro, Carlos Cano, Waldo Fajardo, & Armando Blanco. (2015). DrugNet: Network-based drug–disease prioritization by integrating heterogeneous data. Artificial Intelligence in Medicine. 63(1). 41–49. 161 indexed citations
8.
Cuadros, Marta, et al.. (2015). Predictive Biomarkers to Chemoradiation in Locally Advanced Rectal Cancer. BioMed Research International. 2015. 1–10. 41 indexed citations
9.
Navarro, Carmen, Francisco J. López, Carlos Cano, Fernando García-Alcalde, & Armando Blanco. (2014). CisMiner: Genome-Wide In-Silico Cis-Regulatory Module Prediction by Fuzzy Itemset Mining. PLoS ONE. 9(9). e108065–e108065. 9 indexed citations
10.
Palma, P., Marta Cuadros, Carmen Olmedo, et al.. (2013). Microarray Profiling of Mononuclear Peripheral Blood Cells Identifies Novel Candidate Genes Related to Chemoradiation Response in Rectal Cancer. PLoS ONE. 8(9). e74034–e74034. 10 indexed citations
11.
Cuadros, Marta, Carlos Cano, Francisco J. López, Rafael López Castro, & Ángel Concha. (2012). Expression Profiling of Breast Tumors Based on Human Epidermal Growth Factor Receptor 2 Status Defines Migration-Related Genes. Pathobiology. 80(1). 32–40. 6 indexed citations
12.
López, Francisco J., Marta Cuadros, Carlos Cano, Ángel Concha, & Armando Blanco. (2012). Biomedical application of fuzzy association rules for identifying breast cancer biomarkers. Medical & Biological Engineering & Computing. 50(9). 981–990. 25 indexed citations
13.
14.
Cuadros, Marta, et al.. (2011). HER2 status in breast cancer: experience of a Spanish National Reference Centre. Clinical & Translational Oncology. 13(5). 335–340. 7 indexed citations
15.
Bernal, Mónica, Fernando García-Alcalde, Ángel Concha, et al.. (2011). Genome-wide differential genetic profiling characterizes colorectal cancers with genetic instability and specific routes to HLA class I loss and immune escape. Cancer Immunology Immunotherapy. 61(6). 803–816. 24 indexed citations
16.
Cano, Carlos, et al.. (2009). Collaborative text-annotation resource for disease-centered relation extraction from biomedical text. Journal of Biomedical Informatics. 42(5). 967–977. 18 indexed citations
17.
García, Fernando, Francisco J. López, Carlos Cano, & Armando Blanco. (2009). FISim: A new similarity measure between transcription factor binding sites based on the fuzzy integral. BMC Bioinformatics. 10(1). 224–224. 13 indexed citations
18.
López, Francisco J., Armando Blanco, Fernando García, Carlos Cano, & Antonio Marín García. (2008). Fuzzy association rules for biological data analysis: A case study on yeast. BMC Bioinformatics. 9(1). 107–107. 23 indexed citations
19.
Esteban, Marcos Bruna, Rafael López‐Andújar, Eva Montalvá, et al.. (2008). Donantes de ayer y de hoy: ¿han cambiado las características de los donantes de hígado durante los últimos 15 años?. Cirugía Española. 83(4). 194–198. 2 indexed citations
20.
Zaragozá, Cristóbal, et al.. (2007). Resultados de la anopexia grapada de Longo en el tratamiento quirúrgico ambulatorio de las hemorroides de grados III-IV. Cirugía Española. 81(3). 130–133. 2 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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2026