Robi Tăcutu

3.3k total citations · 1 hit paper
34 papers, 2.1k citations indexed

About

Robi Tăcutu is a scholar working on Molecular Biology, Aging and Physiology. According to data from OpenAlex, Robi Tăcutu has authored 34 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 22 papers in Aging and 9 papers in Physiology. Recurrent topics in Robi Tăcutu's work include Genetics, Aging, and Longevity in Model Organisms (22 papers), Bioinformatics and Genomic Networks (8 papers) and Single-cell and spatial transcriptomics (4 papers). Robi Tăcutu is often cited by papers focused on Genetics, Aging, and Longevity in Model Organisms (22 papers), Bioinformatics and Genomic Networks (8 papers) and Single-cell and spatial transcriptomics (4 papers). Robi Tăcutu collaborates with scholars based in Israel, Romania and United Kingdom. Robi Tăcutu's co-authors include Vadim E. Fraifeld, Arie Budovsky, João Pedro de Magalhães, Thomas Craig, Gilad Lehmann, Daniel Thornton, Hagai Yanai, Emily Johnson, Jingwei Wang and Daniel Wuttke and has published in prestigious journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Robi Tăcutu

33 papers receiving 2.1k citations

Hit Papers

Human Ageing Genomic Reso... 2017 2026 2020 2023 2017 100 200 300 400

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Robi Tăcutu 1.1k 759 472 212 203 34 2.1k
Arie Budovsky 1.4k 1.2× 904 1.2× 592 1.3× 234 1.1× 231 1.1× 51 2.9k
Daryl P. Shanley 1.0k 0.9× 559 0.7× 497 1.1× 195 0.9× 194 1.0× 62 2.5k
Vadim E. Fraifeld 1.7k 1.5× 1.0k 1.3× 787 1.7× 268 1.3× 251 1.2× 84 3.4k
Thomas Craig 831 0.7× 450 0.6× 228 0.5× 162 0.8× 192 0.9× 13 1.5k
Sun Hee Yim 1.4k 1.2× 328 0.4× 383 0.8× 198 0.9× 119 0.6× 39 2.6k
Steven Buck 1.0k 0.9× 816 1.1× 314 0.7× 445 2.1× 373 1.8× 83 2.9k
Mark B. Roth 2.0k 1.8× 581 0.8× 501 1.1× 252 1.2× 291 1.4× 47 3.7k
Bertrand Ducos 1.4k 1.3× 900 1.2× 797 1.7× 338 1.6× 80 0.4× 46 3.0k
Travis J. Maures 1.5k 1.3× 652 0.9× 292 0.6× 369 1.7× 70 0.3× 22 2.3k
Robert S. Garofalo 2.0k 1.8× 1.2k 1.5× 908 1.9× 420 2.0× 273 1.3× 33 4.2k

Countries citing papers authored by Robi Tăcutu

Since Specialization
Citations

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

Fields of papers citing papers by Robi Tăcutu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Robi Tăcutu

This figure shows the co-authorship network connecting the top 25 collaborators of Robi Tăcutu. A scholar is included among the top collaborators of Robi Tăcutu 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 Robi Tăcutu. Robi Tăcutu 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.
2.
Toren, Dmitri, et al.. (2021). Systems biology analysis of lung fibrosis-related genes in the bleomycin mouse model. Scientific Reports. 11(1). 19269–19269. 8 indexed citations
3.
Toren, Dmitri, Eitan Rubin, Anna V. Kudryavtseva, et al.. (2020). Gray whale transcriptome reveals longevity adaptations associated with DNA repair and ubiquitination. Aging Cell. 19(7). e13158–e13158. 29 indexed citations
4.
Toren, Dmitri, et al.. (2020). SynergyAge, a curated database for synergistic and antagonistic interactions of longevity-associated genes. Scientific Data. 7(1). 366–366. 14 indexed citations
5.
Tăcutu, Robi, et al.. (2020). MetaboAge DB: a repository of known ageing-related changes in the human metabolome. Biogerontology. 21(6). 763–771. 16 indexed citations
6.
Avelar, Roberto A., Javier Gómez Ortega, Robi Tăcutu, et al.. (2020). A multidimensional systems biology analysis of cellular senescence in aging and disease. Genome biology. 21(1). 91–91. 232 indexed citations
7.
Yanai, Hagai, et al.. (2017). Wide‐scale comparative analysis of longevity genes and interventions. Aging Cell. 16(6). 1267–1275. 30 indexed citations
8.
Wan, Cen, Robi Tăcutu, Diogo Barardo, et al.. (2016). Systematic analysis of the gerontome reveals links between aging and age-related diseases. Human Molecular Genetics. 25(21). ddw307–ddw307. 64 indexed citations
9.
Tăcutu, Robi, et al.. (2015). A network pharmacology approach reveals new candidate caloric restriction mimetics in C. elegans. Aging Cell. 15(2). 256–266. 71 indexed citations
10.
Toren, Dmitri, et al.. (2015). MitoAge: a database for comparative analysis of mitochondrial DNA, with a special focus on animal longevity. Nucleic Acids Research. 44(D1). D1262–D1265. 21 indexed citations
11.
Wood, Shona H., Sipko van Dam, Thomas Craig, et al.. (2015). Transcriptome analysis in calorie-restricted rats implicates epigenetic and post-translational mechanisms in neuroprotection and aging. Genome biology. 16(1). 285–285. 45 indexed citations
12.
Craig, Thomas, Robi Tăcutu, Daniel Wuttke, et al.. (2014). The Digital Ageing Atlas: integrating the diversity of age-related changes into a unified resource. Nucleic Acids Research. 43(D1). D873–D878. 61 indexed citations
13.
Budovsky, Arie, Thomas Craig, Jingwei Wang, et al.. (2013). LongevityMap: a database of human genetic variants associated with longevity. Trends in Genetics. 29(10). 559–560. 71 indexed citations
14.
Tăcutu, Robi, Thomas Craig, Arie Budovsky, et al.. (2012). Human Ageing Genomic Resources: Integrated databases and tools for the biology and genetics of ageing. Nucleic Acids Research. 41(D1). D1027–D1033. 400 indexed citations
15.
Tăcutu, Robi, Arie Budovsky, João Pedro de Magalhães, et al.. (2012). Prediction of C. elegans Longevity Genes by Human and Worm Longevity Networks. PLoS ONE. 7(10). e48282–e48282. 36 indexed citations
16.
Tăcutu, Robi, Arie Budovsky, & Hagai Yanai. (2011). Immunoregulatory network and cancer-associated genes: molecular links and relevance to aging. SHILAP Revista de lepidopterología. 10 indexed citations
17.
Moskalev, Alexey, Zeljka Smit‐McBride, Mikhail Shaposhnikov, et al.. (2011). Gadd45 proteins: Relevance to aging, longevity and age-related pathologies. Ageing Research Reviews. 11(1). 51–66. 124 indexed citations
18.
Tăcutu, Robi, Arie Budovsky, & Vadim E. Fraifeld. (2010). The NetAge database: a compendium of networks for longevity, age-related diseases and associated processes. Biogerontology. 11(4). 513–522. 61 indexed citations
19.
Budovsky, Arie, Robi Tăcutu, Hagai Yanai, et al.. (2008). Common gene signature of cancer and longevity. Mechanisms of Ageing and Development. 130(1-2). 33–39. 43 indexed citations
20.
Wolfson, Marina, Arie Budovsky, Robi Tăcutu, & Vadim E. Fraifeld. (2008). The signaling hubs at the crossroad of longevity and age-related disease networks. The International Journal of Biochemistry & Cell Biology. 41(3). 516–520. 78 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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