Francisco Cedrón

661 total citations · 1 hit paper
18 papers, 384 citations indexed

About

Francisco Cedrón is a scholar working on Electrical and Electronic Engineering, Cognitive Neuroscience and Agronomy and Crop Science. According to data from OpenAlex, Francisco Cedrón has authored 18 papers receiving a total of 384 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Electrical and Electronic Engineering, 4 papers in Cognitive Neuroscience and 3 papers in Agronomy and Crop Science. Recurrent topics in Francisco Cedrón's work include Advanced Memory and Neural Computing (5 papers), Neural dynamics and brain function (3 papers) and Neural Networks and Applications (3 papers). Francisco Cedrón is often cited by papers focused on Advanced Memory and Neural Computing (5 papers), Neural dynamics and brain function (3 papers) and Neural Networks and Applications (3 papers). Francisco Cedrón collaborates with scholars based in Spain, France and Italy. Francisco Cedrón's co-authors include Alejandro Pazos, Carlos Fernández-Lozano, Adrián Carballal, José Liñares-Blanco, Víctor Maojo, Nereida Rodríguez-Fernández, Francisco J. Nóvoa, Ana B. Porto-Pazos, Enrique Fernández-Blanco and Óscar Ibáñez and has published in prestigious journals such as SHILAP Revista de lepidopterología, International Journal of Molecular Sciences and Applied Sciences.

In The Last Decade

Francisco Cedrón

16 papers receiving 369 citations

Hit Papers

align trajectories

What are hit papers?

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 review on machine learning approaches and trends in drug discovery

2021 264 citations José Liñares-Blanco, Nereida Rodríguez-Fernández et al. Computational and Structural Biotechnology Journal profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Francisco Cedrón Spain	5	190	146	53	52	35	18	384
Tomasz Arodź United States	12	220 1.2×	247 1.7×	72 1.4×	69 1.3×	32 0.9×	27	601
Jiajun Hong China	12	184 1.0×	614 4.2×	54 1.0×	48 0.9×	33 0.9×	21	902
Xiao Gan United States	6	193 1.0×	293 2.0×	33 0.6×	174 3.3×	30 0.9×	9	720
Sabina Podlewska Poland	14	205 1.1×	306 2.1×	27 0.5×	80 1.5×	13 0.4×	48	571
Shengyu Zhang China	11	75 0.4×	200 1.4×	126 2.4×	73 1.4×	20 0.6×	42	477
María Jimena Martínez Argentina	11	177 0.9×	145 1.0×	22 0.4×	87 1.7×	9 0.3×	22	350
Andreas Schüller Germany	17	206 1.1×	347 2.4×	18 0.3×	66 1.3×	9 0.3×	37	711
Sunyoung Kwon South Korea	11	155 0.8×	245 1.7×	31 0.6×	61 1.2×	12 0.3×	30	544
Jiří Filipovič Czechia	12	86 0.5×	285 2.0×	18 0.3×	68 1.3×	42 1.2×	40	539

Countries citing papers authored by Francisco Cedrón

Since Specialization

Citations

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

Fields of papers citing papers by Francisco Cedrón

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Francisco Cedrón

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

All Works

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18 of 18 papers shown

Porto-Pazos, Ana B., et al.. (2025). Alzheimer’s Disease: Exploring Pathophysiological Hypotheses and the Role of Machine Learning in Drug Discovery. International Journal of Molecular Sciences. 26(3). 1004–1004. 8 indexed citations

Cedrón, Francisco, et al.. (2024). Efficient Implementation of Multilayer Perceptrons: Reducing Execution Time and Memory Consumption. Applied Sciences. 14(17). 8020–8020.

Cedrón, Francisco, et al.. (2023). Artificial glial cells in artificial neuronal networks: a systematic review. Artificial Intelligence Review. 56(S2). 2651–2666. 4 indexed citations

Liñares-Blanco, José, Nereida Rodríguez-Fernández, Francisco Cedrón, et al.. (2021). A review on machine learning approaches and trends in drug discovery. Computational and Structural Biotechnology Journal. 19. 4538–4558. 264 indexed citations breakdown →

Carballal, Adrián, Francisco Cedrón, Iria Santos, Antonino Santos, & Juan Romero. (2021). Minimal neural network topology optimization for aesthetic classification. Neural Computing and Applications. 33(1). 107–119. 4 indexed citations

Porto-Pazos, Ana B., et al.. (2020). Probiotic: First Prescriptive Application of Probiotics in Spain. SHILAP Revista de lepidopterología. 34–34.

Fernández-Lozano, Carlos & Francisco Cedrón. (2020). Shiny Dashboard for Monitoring the COVID-19 Pandemic in Spain. MDPI (MDPI AG). 23–23. 3 indexed citations

Cedrón, Francisco, Adrián Carballal, Carlos Fernández-Lozano, Cristian R. Munteanu, & Alejandro Pazos. (2018). Infraestructure to support biomedical applications. 5507–5507. 1 indexed citations

Cedrón, Francisco, et al.. (2016). Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications. International Journal of Molecular Sciences. 17(8). 1313–1313. 64 indexed citations

10.

Porto-Pazos, Ana B., et al.. (2016). Parallel Computing for Brain Simulation. Current Topics in Medicinal Chemistry. 17(14). 1646–1668. 2 indexed citations

11.

Fernández-Lozano, Carlos, Francisco Cedrón, Daniel Rivero, et al.. (2016). Using genetic algorithms to improve support vector regression in the analysis of atomic spectra of lubricant oils. Engineering Computations. 33(4). 995–1005. 3 indexed citations

12.

Mesejo, Pablo, Óscar Ibáñez, Enrique Fernández-Blanco, et al.. (2015). Artificial Neuron–Glia Networks Learning Approach Based on Cooperative Coevolution. International Journal of Neural Systems. 25(4). 1550012–1550012. 21 indexed citations

13.

Porto-Pazos, Ana B., et al.. (2015). <strong>Computational Models of the Brain</strong>. e009–e009. 1 indexed citations

14.

Sau, Federico, et al.. (2012). MODELOS DE SIMULACIÓN DEL CULTIVO DE MAÍZ: FUNDAMENTOS Y APLICACIONES EN ESPAÑA. POLI-RED (Revistas Digitales Politécnicas) (La Universidad Politécnica de Madrid). 40(2). 117–138. 1 indexed citations

15.

Sau, Federico, et al.. (2010). Simulation models of the maize crop: basis and applications in Spain.. 40(2). 117–138. 1 indexed citations

16.

Cedrón, Francisco, et al.. (2006). PRODUCTIVIDAD DE LA ROTACIÓN ANUAL RAIGRÁS-MAÍZ EN GALICIA: EVALUACIÓN DURANTE CINCO AÑOS EN REGADÍO Y SECANO Y BAJO DOS SISTEMAS DE SIEMBRA. POLI-RED (Revistas Digitales Politécnicas) (La Universidad Politécnica de Madrid). 36(2). 193–216. 2 indexed citations

17.

Sau, Federico, et al.. (2001). Efecto de la fecha siembra en altramuz blanco y guisante proteaginoso. Agricultura: Revista agropecuaria y ganadera. 110–112. 1 indexed citations

18.

Sau, Federico, et al.. (1999). Intensificación de la producción forrajera en Galicia. Agricultura: Revista agropecuaria y ganadera. 384–386. 4 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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