José M. Sempere

1.2k total citations
42 papers, 549 citations indexed

About

José M. Sempere is a scholar working on Molecular Biology, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, José M. Sempere has authored 42 papers receiving a total of 549 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 17 papers in Computational Theory and Mathematics and 13 papers in Artificial Intelligence. Recurrent topics in José M. Sempere's work include DNA and Biological Computing (17 papers), semigroups and automata theory (9 papers) and Cellular Automata and Applications (7 papers). José M. Sempere is often cited by papers focused on DNA and Biological Computing (17 papers), semigroups and automata theory (9 papers) and Cellular Automata and Applications (7 papers). José M. Sempere collaborates with scholars based in Spain, Romania and Italy. José M. Sempere's co-authors include Carlos Lloréns, Andrés Moyá, Ricardo Futami, Amparo Latorre, L. Covelli, Alfonso Muñoz-Pomer Fuentes, G. P. Bernet, Laura Domínguez‐Escribá, Daniel Tamarit and José Aguilar-Rodríguez and has published in prestigious journals such as Nucleic Acids Research, Clinical Infectious Diseases and Antimicrobial Agents and Chemotherapy.

In The Last Decade

José M. Sempere

35 papers receiving 534 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
José M. Sempere Spain 10 292 216 83 76 66 42 549
J. Peterson United States 3 688 2.4× 185 0.9× 207 2.5× 13 0.2× 152 2.3× 3 914
Justin Schonfeld Canada 11 135 0.5× 147 0.7× 80 1.0× 16 0.2× 71 1.1× 41 581
Marek Kokot Poland 6 442 1.5× 163 0.8× 140 1.7× 9 0.1× 113 1.7× 12 620
Ekaterina M. Panina Russia 7 424 1.5× 66 0.3× 55 0.7× 98 1.3× 210 3.2× 10 769
Nela Zavaljevski United States 15 397 1.4× 80 0.4× 32 0.4× 19 0.3× 71 1.1× 31 623
Guangrong Li China 26 481 1.6× 1.7k 7.7× 66 0.8× 15 0.2× 330 5.0× 142 2.2k
F. Rodolphe France 17 384 1.3× 348 1.6× 104 1.3× 22 0.3× 174 2.6× 32 793
Prabina Kumar Meher India 17 671 2.3× 384 1.8× 15 0.2× 36 0.5× 189 2.9× 57 1.1k
Vico Pascual Spain 10 118 0.4× 58 0.3× 73 0.9× 24 0.3× 13 0.2× 25 548
Sara Brunetti Italy 10 182 0.6× 72 0.3× 13 0.2× 41 0.5× 33 0.5× 38 522

Countries citing papers authored by José M. Sempere

Since Specialization
Citations

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

Fields of papers citing papers by José M. Sempere

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by José M. Sempere. 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 José M. Sempere. The network helps show where José M. Sempere may publish in the future.

Co-authorship network of co-authors of José M. Sempere

This figure shows the co-authorship network connecting the top 25 collaborators of José M. Sempere. A scholar is included among the top collaborators of José M. Sempere 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 José M. Sempere. José M. Sempere 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.
Sicilia, María Luisa Machado, et al.. (2025). Inteligencia artificial generativa: los modelos fundacionales. Procesamiento del lenguaje natural y modelos de lenguaje grandes. Revista Clínica Española. 226(1). 502413–502413.
2.
Rodríguez‐González, Alejandro, et al.. (2025). Machine learning y deep learning en medicina interna: desmitificando conceptos. Revista Clínica Española. 226(1). 502412–502412.
3.
Galán, Juan Carlos, et al.. (2024). Membrane computing simulation of sexually transmitted bacterial infections in hotspots of individuals with various risk behaviors. Microbiology Spectrum. 12(2). e0272823–e0272823. 1 indexed citations
4.
Hafez, Ahmed Ibrahem, Beatriz Soriano, Ricardo Futami, et al.. (2023). Client Applications and Server-Side Docker for Management of RNASeq and/or VariantSeq Workflows and Pipelines of the GPRO Suite. Genes. 14(2). 267–267. 2 indexed citations
5.
Sempere, José M., Juan Carlos Galán, Andrés Moyá, et al.. (2022). Simulating the efficacy of vaccines on the epidemiological dynamics of SARS-CoV-2 in a membrane computing model. PubMed. 3. uqac018–uqac018. 2 indexed citations
6.
Sempere, José M., Juan Carlos Galán, Andrés Moyá, et al.. (2021). Simulating the impact of non-pharmaceutical interventions limiting transmission in COVID-19 epidemics using a membrane computing model. PubMed. 2. uqab011–uqab011. 4 indexed citations
7.
Sempere, José M., et al.. (2020). A two authorities electronic vote scheme. Computers & Security. 97. 101940–101940. 4 indexed citations
8.
Sempere, José M.. (2019). Modeling of Decision Trees Through P Systems. New Generation Computing. 37(3). 325–337. 7 indexed citations
9.
Sempere, José M.. (2018). On the application of Watson-Crick finite automata for the resolution of bioinformatic problems.. 29–30. 4 indexed citations
10.
Rozenberg, Grzegorz, Arto Salomaa, José M. Sempere, & Claudio Zandron. (2015). Membrane Computing. Lecture notes in computer science. 1 indexed citations
11.
Sempere, José M., et al.. (2012). Accepting Networks of Genetic Processors are computationally complete. Theoretical Computer Science. 456. 18–29. 6 indexed citations
12.
Lloréns, Carlos, Ricardo Futami, L. Covelli, et al.. (2010). The Gypsy Database (GyDB) of mobile genetic elements: release 2.0. Nucleic Acids Research. 39(Database). D70–D74. 267 indexed citations
13.
Mitrana, Víctor & José M. Sempere. (2009). Accepting Evolutionary P Systems. 552–555.
14.
Sempere, José M.. (2008). Exploring regular reversibility in Watson-Crick finite automata. 1 indexed citations
15.
López, Mariola, Carlos Toro, Victoria Jiménez, et al.. (2006). Influence of Human T Cell Lymphotropic Virus Type 2 Coinfection on Virological and Immunological Parameters in HIV Type 1–Infected Patients. Clinical Infectious Diseases. 44(1). 105–110. 16 indexed citations
16.
Calles, Belén, et al.. (2004). Detection of Functional Motifs in Biosequences: A Grammatical Inference Approach.. 33(1). 72–75. 1 indexed citations
17.
Sempere, José M.. (2004). A Representation Theorem for Languages Accepted by Watson-Crick Finite Automata.. Bulletin of the European Association for Theoretical Computer Science. 83. 187–191. 9 indexed citations
18.
Sempere, José M., et al.. (2004). Inference of Reversible Tree Languages. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 34(4). 1658–1665. 10 indexed citations
19.
Zabay, J M, et al.. (1995). Serum β2-Microglobulin and Prediction of Progression to AIDS in HIV-Infected Injection Drug Users. Journal of Acquired Immune Deficiency Syndromes & Human Retrovirology. 8(3). 266–272. 9 indexed citations
20.
Sempere, José M. & Pedro García. (1993). A new regular language learning algorithm from lexicographically ordered complete samples. 1 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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