Julián Perera

1.6k total citations
38 papers, 1.3k citations indexed

About

Julián Perera is a scholar working on Molecular Biology, Pharmacology and Genetics. According to data from OpenAlex, Julián Perera has authored 38 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Molecular Biology, 10 papers in Pharmacology and 8 papers in Genetics. Recurrent topics in Julián Perera's work include Steroid Chemistry and Biochemistry (11 papers), Pharmacogenetics and Drug Metabolism (10 papers) and Microbial Metabolic Engineering and Bioproduction (10 papers). Julián Perera is often cited by papers focused on Steroid Chemistry and Biochemistry (11 papers), Pharmacogenetics and Drug Metabolism (10 papers) and Microbial Metabolic Engineering and Bioproduction (10 papers). Julián Perera collaborates with scholars based in Spain, United States and Germany. Julián Perera's co-authors include Juana María Navarro Lloréns, Victoria Mascaraque, Oliver Drzyzga, Sergio Alonso, Georg Fuchs, Wolfgang Eisenreich, Wael Ismail, Robin Teufel, Wolfgang Haehnel and José L. Garcı́a and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and PLoS ONE.

In The Last Decade

Julián Perera

35 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Julián Perera Spain 19 1000 205 195 187 164 38 1.3k
Elı́as R. Olivera Spain 24 1.3k 1.3× 511 2.5× 99 0.5× 173 0.9× 283 1.7× 44 2.0k
Martina Jahn Germany 25 1.7k 1.7× 194 0.9× 39 0.2× 123 0.7× 219 1.3× 47 2.2k
Haisheng Wang China 17 351 0.4× 221 1.1× 80 0.4× 89 0.5× 137 0.8× 57 1.0k
Tewes Tralau Germany 21 499 0.5× 167 0.8× 50 0.3× 103 0.6× 149 0.9× 55 1.2k
Keiji Yano Japan 22 929 0.9× 471 2.3× 45 0.2× 205 1.1× 108 0.7× 90 1.5k
Susana Genti‐Raimondi Argentina 21 491 0.5× 97 0.5× 101 0.5× 123 0.7× 87 0.5× 55 929
Mojtaba Tabatabaei Yazdi Iran 19 548 0.5× 33 0.2× 232 1.2× 194 1.0× 36 0.2× 49 1.1k
Hiroshi Ikenaga Japan 25 1.1k 1.1× 59 0.3× 72 0.4× 268 1.4× 80 0.5× 50 1.5k
Michel Chartrain United States 23 1.3k 1.3× 118 0.6× 116 0.6× 41 0.2× 119 0.7× 64 1.8k
José M. Sala‐Trepat France 16 791 0.8× 263 1.3× 34 0.2× 81 0.4× 213 1.3× 22 1.2k

Countries citing papers authored by Julián Perera

Since Specialization
Citations

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

Fields of papers citing papers by Julián Perera

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Julián Perera

This figure shows the co-authorship network connecting the top 25 collaborators of Julián Perera. A scholar is included among the top collaborators of Julián Perera 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 Julián Perera. Julián Perera 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.
Quijano, Elias, Julián Perera, Hanna K. Mandl, et al.. (2023). DNA recognition and induced genome modification by a hydroxymethyl-γ tail-clamp peptide nucleic acid. Cell Reports Physical Science. 4(10). 101635–101635. 5 indexed citations
2.
Quijano, Elias, et al.. (2022). Antispacer peptide nucleic acids for sequence-specific CRISPR-Cas9 modulation. Nucleic Acids Research. 50(10). e59–e59. 11 indexed citations
3.
Alonso, Sergio, et al.. (2019). New insights into the genome of Rhodococcus ruber strain Chol-4. BMC Genomics. 20(1). 332–332. 29 indexed citations
4.
Perera, Julián, et al.. (2019). Metabolic engineering of Rhodococcus ruber Chol-4: A cell factory for testosterone production. PLoS ONE. 14(7). e0220492–e0220492. 15 indexed citations
5.
Perera, Julián, et al.. (2018). Shape selective bifacial recognition of double helical DNA. Communications Chemistry. 1(1). 37 indexed citations
6.
Perera, Julián, Kirti Bhatt, Chakicherla Gayathri, et al.. (2018). Design of Bivalent Nucleic Acid Ligands for Recognition of RNA-Repeated Expansion Associated with Huntington’s Disease. Biochemistry. 57(14). 2094–2108. 28 indexed citations
7.
Perera, Julián, et al.. (2017). Analysis of Intermediates of Steroid Transformations in Resting Cells by Thin-Layer Chromatography (TLC). Methods in molecular biology. 1645. 347–360. 3 indexed citations
8.
Perera, Julián, et al.. (2017). Functional differentiation of 3-ketosteroid Δ1-dehydrogenase isozymes in Rhodococcus ruber strain Chol-4. Microbial Cell Factories. 16(1). 42–42. 31 indexed citations
9.
Perera, Julián, et al.. (2013). Cholesterol to cholestenone oxidation by ChoG, the main extracellular cholesterol oxidase of Rhodococcus ruber strain Chol-4. The Journal of Steroid Biochemistry and Molecular Biology. 139. 33–44. 18 indexed citations
10.
Mascaraque, Victoria, et al.. (2010). ChoG is the main inducible extracellular cholesterol oxidase of Rhodococcus sp. strain CECT3014. Microbiological Research. 166(5). 403–418. 35 indexed citations
11.
Drzyzga, Oliver, et al.. (2009). Gordonia cholesterolivorans sp. nov., a cholesterol-degrading actinomycete isolated from sewage sludge. INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY. 59(5). 1011–1015. 34 indexed citations
12.
Lloréns, Juana María Navarro, et al.. (2009). Morphological, Physiological, and Molecular Characterization of a Newly Isolated Steroid-Degrading Actinomycete, Identified as Rhodococcus ruber Strain Chol-4. Current Microbiology. 59(5). 548–553. 32 indexed citations
13.
14.
Bartolomé‐Martín, David, Esteban Martínez‐García, Victoria Mascaraque, et al.. (2004). Characterization of a second functional gene cluster for the catabolism of phenylacetic acid in Pseudomonas sp. strain Y2. Gene. 341. 167–179. 21 indexed citations
15.
Alonso, Sergio, David Bartolomé‐Martín, Marta del Álamo, et al.. (2003). Genetic characterization of the styrene lower catabolic pathway of Pseudomonas sp. strain Y2. Gene. 319. 71–83. 22 indexed citations
16.
Alonso, Sergio, et al.. (2003). Design of catabolic cassettes for styrene biodegradation. Antonie van Leeuwenhoek. 84(1). 17–24. 5 indexed citations
17.
Aparicio, Tomás, et al.. (2000). pT3.2I, the Smallest Plasmid of Thiobacillus T3.2. Plasmid. 44(1). 1–11. 4 indexed citations
18.
Silóniz, Marı́a-Isabel de, et al.. (1993). Characterization of a new metal-mobilizing Thiobacillus isolate. Archives of Microbiology. 159(3). 237–243. 10 indexed citations
19.
Almendral, José M., et al.. (1988). Complexity of the Early Genetic Response to Growth Factors in Mouse Fibroblasts. Molecular and Cellular Biology. 8(5). 2140–2148. 157 indexed citations
20.
Franco, Luís, et al.. (1979). Histone H4 from the fruit fly Ceratitis capitata. Purification and characterization. Insect Biochemistry. 9(1). 39–42. 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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