Albert Ribes‐Zamora

453 total citations
10 papers, 349 citations indexed

About

Albert Ribes‐Zamora is a scholar working on Molecular Biology, Physiology and Oncology. According to data from OpenAlex, Albert Ribes‐Zamora has authored 10 papers receiving a total of 349 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 3 papers in Physiology and 1 paper in Oncology. Recurrent topics in Albert Ribes‐Zamora's work include DNA Repair Mechanisms (8 papers), Telomeres, Telomerase, and Senescence (3 papers) and Genomics and Chromatin Dynamics (2 papers). Albert Ribes‐Zamora is often cited by papers focused on DNA Repair Mechanisms (8 papers), Telomeres, Telomerase, and Senescence (3 papers) and Genomics and Chromatin Dynamics (2 papers). Albert Ribes‐Zamora collaborates with scholars based in United States and Singapore. Albert Ribes‐Zamora's co-authors include Alison A. Bertuch, Ivana Mihalek, Olivier Lichtarge, Christopher L. Williams, Madhuri Hegde, Stacey L. Berg, Susan M. Blaney, Debananda Pati, Svasti Haricharan and M. Eileen Dolan and has published in prestigious journals such as Bioinformatics, PLoS ONE and Scientific Reports.

In The Last Decade

Albert Ribes‐Zamora

10 papers receiving 341 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Albert Ribes‐Zamora United States 8 297 148 70 32 28 10 349
Yi Gong United States 9 453 1.5× 176 1.2× 160 2.3× 31 1.0× 20 0.7× 16 539
Penelope A. Mason United Kingdom 8 391 1.3× 103 0.7× 27 0.4× 30 0.9× 21 0.8× 11 437
Sophie Gilbert Canada 6 180 0.6× 128 0.9× 85 1.2× 15 0.5× 19 0.7× 9 308
Corey Winston Jones-Weinert United States 7 371 1.2× 73 0.5× 58 0.8× 27 0.8× 11 0.4× 8 435
Haihe Ruan China 7 286 1.0× 144 1.0× 32 0.5× 39 1.2× 63 2.3× 8 366
Charlotte Hodson Australia 10 442 1.5× 104 0.7× 69 1.0× 13 0.4× 43 1.5× 10 474
Katja Kratz Switzerland 7 410 1.4× 78 0.5× 60 0.9× 29 0.9× 43 1.5× 8 460
Joshua A. M. Allen Australia 6 337 1.1× 240 1.6× 28 0.4× 23 0.7× 8 0.3× 8 379
Sophie Rozenzhak United States 6 251 0.8× 77 0.5× 23 0.3× 23 0.7× 21 0.8× 7 296
Laure Lemmens Switzerland 5 292 1.0× 105 0.7× 41 0.6× 49 1.5× 34 1.2× 6 347

Countries citing papers authored by Albert Ribes‐Zamora

Since Specialization
Citations

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

Fields of papers citing papers by Albert Ribes‐Zamora

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Albert Ribes‐Zamora. 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 Albert Ribes‐Zamora. The network helps show where Albert Ribes‐Zamora may publish in the future.

Co-authorship network of co-authors of Albert Ribes‐Zamora

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

All Works

10 of 10 papers shown
2.
Follis, Jack L., et al.. (2016). The ATM- and ATR-related SCD domain is over-represented in proteins involved in nervous system development. Scientific Reports. 6(1). 19050–19050. 7 indexed citations
3.
Follis, Jack L., et al.. (2014). Using a PyMOL Activity to Reinforce the Connection between Genotype and Phenotype in an Undergraduate Genetics Laboratory. PLoS ONE. 9(12). e114257–e114257. 7 indexed citations
4.
Ribes‐Zamora, Albert, et al.. (2014). SCDFinder, a Web-based tool for the identification of putative novel ATM and ATR targets. Bioinformatics. 30(23). 3394–3395. 2 indexed citations
5.
Ribes‐Zamora, Albert, et al.. (2013). TRF2 Interaction with Ku Heterotetramerization Interface Gives Insight into c-NHEJ Prevention at Human Telomeres. Cell Reports. 5(1). 194–206. 56 indexed citations
6.
Cheung, Hannah, F Anthony San Lucas, Stephanie C. Hicks, et al.. (2012). An S/T-Q cluster domain census unveils new putative targets under Tel1/Mec1 control. BMC Genomics. 13(1). 664–664. 15 indexed citations
7.
Ribes‐Zamora, Albert, et al.. (2011). Ku Must Load Directly onto the Chromosome End in Order to Mediate Its Telomeric Functions. PLoS Genetics. 7(8). e1002233–e1002233. 33 indexed citations
8.
Ribes‐Zamora, Albert, et al.. (2011). Three novel truncating TINF2 mutations causing severe dyskeratosis congenita in early childhood. Clinical Genetics. 81(5). 470–478. 65 indexed citations
9.
Horton, Terzah M., Debananda Pati, Linna Zhang, et al.. (2009). Poly(ADP-ribose) polymerase inhibitor ABT-888 potentiates the cytotoxic activity of temozolomide in leukemia cells: influence of mismatch repair status and O 6-methylguanine-DNA methyltransferase activity. Molecular Cancer Therapeutics. 8(8). 2232–2242. 67 indexed citations
10.
Ribes‐Zamora, Albert, Ivana Mihalek, Olivier Lichtarge, & Alison A. Bertuch. (2007). Distinct faces of the Ku heterodimer mediate DNA repair and telomeric functions. Nature Structural & Molecular Biology. 14(4). 301–307. 84 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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