Iván Dotú

1.7k total citations
33 papers, 1.0k citations indexed

About

Iván Dotú is a scholar working on Molecular Biology, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Iván Dotú has authored 33 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 6 papers in Artificial Intelligence and 4 papers in Computer Networks and Communications. Recurrent topics in Iván Dotú's work include RNA and protein synthesis mechanisms (17 papers), RNA modifications and cancer (16 papers) and RNA Research and Splicing (16 papers). Iván Dotú is often cited by papers focused on RNA and protein synthesis mechanisms (17 papers), RNA modifications and cancer (16 papers) and RNA Research and Splicing (16 papers). Iván Dotú collaborates with scholars based in United States, Spain and France. Iván Dotú's co-authors include Peter Clote, Jeffrey H. Chuang, Gábor Nagy, Susan L. Ackerman, Ryuta Ishimura, Pascal Van Hentenryck, Xiang‐Lei Yang, Paul Schimmel, Yasuharu Nishimura and Juan Antonio García-Martín and has published in prestigious journals such as Science, Nucleic Acids Research and Bioinformatics.

In The Last Decade

Iván Dotú

32 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Iván Dotú United States 16 878 75 68 65 61 33 1.0k
Derek Thirstrup United States 7 820 0.9× 173 2.3× 55 0.8× 71 1.1× 29 0.5× 11 1.4k
Charles Y. Lin United States 9 1.1k 1.2× 65 0.9× 107 1.6× 155 2.4× 18 0.3× 14 1.3k
Gabriel Musso United States 15 502 0.6× 66 0.9× 140 2.1× 57 0.9× 28 0.5× 28 660
Shibiao Wan United States 21 885 1.0× 34 0.5× 29 0.4× 53 0.8× 27 0.4× 54 1.1k
Vincent Gardeux Switzerland 17 768 0.9× 25 0.3× 164 2.4× 130 2.0× 18 0.3× 43 1.2k
Jeong‐Rae Kim South Korea 15 622 0.7× 112 1.5× 84 1.2× 48 0.7× 17 0.3× 37 820
Leslie R. Grate United States 15 1.2k 1.3× 61 0.8× 55 0.8× 102 1.6× 13 0.2× 20 1.4k
Patrick Erñst United States 16 760 0.9× 28 0.4× 85 1.3× 46 0.7× 52 0.9× 47 1.1k
Albert Xu United States 8 802 0.9× 34 0.5× 147 2.2× 70 1.1× 25 0.4× 18 928
Hong Jin China 21 857 1.0× 27 0.4× 163 2.4× 138 2.1× 46 0.8× 40 1.2k

Countries citing papers authored by Iván Dotú

Since Specialization
Citations

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

Fields of papers citing papers by Iván Dotú

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Iván Dotú

This figure shows the co-authorship network connecting the top 25 collaborators of Iván Dotú. A scholar is included among the top collaborators of Iván Dotú 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 Iván Dotú. Iván Dotú 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.
Minuesa, Gerard, et al.. (2021). MoiRNAiFold: a novel tool for complex in silico RNA design. Nucleic Acids Research. 49(9). 4934–4943. 18 indexed citations
2.
Dotú, Iván, et al.. (2018). SARNAclust: Semi-automatic detection of RNA protein binding motifs from immunoprecipitation data. PLoS Computational Biology. 14(3). e1006078–e1006078. 4 indexed citations
3.
Pagès, Amadís, et al.. (2017). The discovery potential of RNA processing profiles. Nucleic Acids Research. 46(3). e15–e15. 10 indexed citations
4.
Ishimura, Ryuta, Gábor Nagy, Iván Dotú, Jeffrey H. Chuang, & Susan L. Ackerman. (2016). Activation of GCN2 kinase by ribosome stalling links translation elongation with translation initiation. eLife. 5. 161 indexed citations
5.
Fernández-Chamorro, Javier, Gloria Lozano, Juan Antonio García-Martín, et al.. (2016). Designing synthetic RNAs to determine the relevance of structural motifs in picornavirus IRES elements. Scientific Reports. 6(1). 24243–24243. 8 indexed citations
6.
García-Martín, Juan Antonio, et al.. (2016). RNAdualPF: software to compute the dual partition function with sample applications in molecular evolution theory. BMC Bioinformatics. 17(1). 424–424. 9 indexed citations
7.
Cilla, Rodrigo, et al.. (2015). Segmentation and Tracking of Adherens Junctions in 3D for the Analysis of Epithelial Tissue Morphogenesis. PLoS Computational Biology. 11(4). e1004124–e1004124. 18 indexed citations
8.
Ishimura, Ryuta, Gábor Nagy, Iván Dotú, et al.. (2014). Ribosome stalling induced by mutation of a CNS-specific tRNA causes neurodegeneration. Science. 345(6195). 455–459. 328 indexed citations
9.
Dotú, Iván, et al.. (2014). Energy Parameters and Novel Algorithms for an Extended Nearest Neighbor Energy Model of RNA. PLoS ONE. 9(2). e85412–e85412. 3 indexed citations
10.
García-Martín, Juan Antonio, Peter Clote, & Iván Dotú. (2013). RNAiFold: a web server for RNA inverse folding and molecular design. Nucleic Acids Research. 41(W1). W465–W470. 15 indexed citations
11.
Dotú, Iván, Gloria Lozano, Peter Clote, & Encarnación Martı́nez-Salas. (2013). Using RNA inverse folding to identify IRES-like structural subdomains. RNA Biology. 10(12). 1842–1852. 18 indexed citations
12.
Senter, Evan, et al.. (2012). Using the Fast Fourier Transform to Accelerate the Computational Search for RNA Conformational Switches. PLoS ONE. 7(12). e50506–e50506. 13 indexed citations
13.
Zarringhalam, Kourosh, Michelle M. Meyer, Iván Dotú, Jeffrey H. Chuang, & Peter Clote. (2012). Integrating Chemical Footprinting Data into RNA Secondary Structure Prediction. PLoS ONE. 7(10). e45160–e45160. 74 indexed citations
14.
Dotú, Iván, Manuel Cebrián, Pascal Van Hentenryck, & Peter Clote. (2011). On Lattice Protein Structure Prediction Revisited. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 8(6). 1620–1632. 41 indexed citations
15.
Dotú, Iván, Miguel Á. Patricio, Antonio Berlanga, Jesús Garcı́a, & José M. Molina. (2010). Boosting video tracking performance by means of Tabu Search in intelligent visual surveillance systems. Journal of Heuristics. 17(4). 415–440. 7 indexed citations
16.
Dotú, Iván, et al.. (2009). RNA STRUCTURAL SEGMENTATION. WORLD SCIENTIFIC eBooks. 57–68. 4 indexed citations
17.
Cebrián, Manuel, Iván Dotú, Pascal Van Hentenryck, & Peter Clote. (2008). Protein structure prediction on the face centered cubic lattice by local search. National Conference on Artificial Intelligence. 241–246. 23 indexed citations
18.
Dotú, Iván, et al.. (2007). Scheduling social tournaments locally. AI Communications. 20(3). 151–162. 1 indexed citations
19.
Dotú, Iván & Pascal Van Hentenryck. (2005). A simple Hybrid Evolutionary Algorithm for Finding Golomb Rulers. 3. 2018–2023. 15 indexed citations
20.
Ansótegui, Carlos, Álvaro del Val, Iván Dotú, Cèsar Fernández, & Felip Manyà. (2004). Modeling choices in quasigroup completion: SAT vs. CSP. National Conference on Artificial Intelligence. 137–142. 16 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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