Ray M. Marín

1.6k total citations · 1 hit paper
11 papers, 1.0k citations indexed

About

Ray M. Marín is a scholar working on Molecular Biology, Cancer Research and Plant Science. According to data from OpenAlex, Ray M. Marín has authored 11 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 5 papers in Cancer Research and 3 papers in Plant Science. Recurrent topics in Ray M. Marín's work include RNA modifications and cancer (4 papers), MicroRNA in disease regulation (4 papers) and Cancer-related molecular mechanisms research (3 papers). Ray M. Marín is often cited by papers focused on RNA modifications and cancer (4 papers), MicroRNA in disease regulation (4 papers) and Cancer-related molecular mechanisms research (3 papers). Ray M. Marín collaborates with scholars based in Switzerland, United States and Germany. Ray M. Marín's co-authors include Henrik Kaessmann, Jiří Vaníček, Ioannis Sarropoulos, Margarida Cardoso-Moreira, Angélica Liechti, Diego Cortez, Frank Grützner, Paul D. Waters, Deborah Toledo‐Flores and Richard A. Houghten and has published in prestigious journals such as Nature, Nucleic Acids Research and PLoS ONE.

In The Last Decade

Ray M. Marín

11 papers receiving 1.0k citations

Hit Papers

Origins and functional evolution of Y chromosomes across ... 2014 2026 2018 2022 2014 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ray M. Marín Switzerland 11 606 380 299 248 112 11 1.0k
Xionglei He China 19 1.3k 2.2× 507 1.3× 330 1.1× 270 1.1× 120 1.1× 51 1.8k
Arnaud Kerhornou United Kingdom 8 848 1.4× 398 1.0× 171 0.6× 295 1.2× 49 0.4× 9 1.4k
Olga Botvinnik United States 7 1.1k 1.7× 196 0.5× 103 0.3× 262 1.1× 21 0.2× 10 1.4k
Andreas Kähäri United Kingdom 6 832 1.4× 393 1.0× 181 0.6× 216 0.9× 22 0.2× 6 1.3k
Sasha F. Levy United States 22 1.4k 2.3× 795 2.1× 195 0.7× 172 0.7× 26 0.2× 34 1.8k
Cristina Marino‐Buslje Argentina 22 901 1.5× 127 0.3× 38 0.1× 181 0.7× 99 0.9× 60 1.2k
Joseph C. Reese United States 32 2.7k 4.5× 574 1.5× 107 0.4× 306 1.2× 57 0.5× 64 3.2k
Amir Mitchell United States 14 775 1.3× 287 0.8× 40 0.1× 198 0.8× 35 0.3× 20 1.1k
István Ladunga United States 18 1.2k 2.0× 189 0.5× 74 0.2× 440 1.8× 13 0.1× 30 1.7k
Matthieu Muffato United Kingdom 13 808 1.3× 370 1.0× 82 0.3× 309 1.2× 11 0.1× 15 1.2k

Countries citing papers authored by Ray M. Marín

Since Specialization
Citations

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

Fields of papers citing papers by Ray M. Marín

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ray M. Marín

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

All Works

11 of 11 papers shown
1.
Sarropoulos, Ioannis, Ray M. Marín, Margarida Cardoso-Moreira, & Henrik Kaessmann. (2019). Developmental dynamics of lncRNAs across mammalian organs and species. Nature. 571(7766). 510–514. 207 indexed citations
2.
Marín, Ray M., Diego Cortez, Francesco Lamanna, et al.. (2017). Convergent origination of aDrosophila-like dosage compensation mechanism in a reptile lineage. Genome Research. 27(12). 1974–1987. 65 indexed citations
3.
Paredes, Juan C., Jeremy K. Herren, Fanny Schüpfer, et al.. (2015). Genome Sequence of the Drosophila melanogaster Male-Killing Spiroplasma Strain MSRO Endosymbiont. mBio. 6(2). 64 indexed citations
4.
Šulc, M., Ray M. Marín, Harlan Robins, & Jiří Vaníček. (2015). PACCMIT/PACCMIT-CDS: identifying microRNA targets in 3′ UTRs and coding sequences. Nucleic Acids Research. 43(W1). W474–W479. 19 indexed citations
5.
Cortez, Diego, Ray M. Marín, Deborah Toledo‐Flores, et al.. (2014). Origins and functional evolution of Y chromosomes across mammals. Nature. 508(7497). 488–493. 365 indexed citations breakdown →
6.
Marín, Ray M., M. Šulc, & Jiří Vaníček. (2013). Searching the coding region for microRNA targets. RNA. 19(4). 467–474. 29 indexed citations
8.
Marín, Ray M. & Jiří Vaníček. (2012). Optimal Use of Conservation and Accessibility Filters in MicroRNA Target Prediction. PLoS ONE. 7(2). e32208–e32208. 18 indexed citations
9.
Marín, Ray M. & Jiří Vaníček. (2010). Efficient use of accessibility in microRNA target prediction. Nucleic Acids Research. 39(1). 19–29. 100 indexed citations
10.
Medina‐Franco, José L., Karina Martínez‐Mayorga, Andreas Bender, et al.. (2009). Characterization of Activity Landscapes Using 2D and 3D Similarity Methods: Consensus Activity Cliffs. Journal of Chemical Information and Modeling. 49(2). 477–491. 119 indexed citations
11.
Marín, Ray M., et al.. (2008). Graph Theoretical Similarity Approach To Compare Molecular Electrostatic Potentials. Journal of Chemical Information and Modeling. 48(1). 109–118. 26 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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