Daniel Dar

2.0k total citations · 1 hit paper
19 papers, 1.0k citations indexed

About

Daniel Dar is a scholar working on Molecular Biology, Genetics and Ecology. According to data from OpenAlex, Daniel Dar has authored 19 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 10 papers in Genetics and 6 papers in Ecology. Recurrent topics in Daniel Dar's work include RNA and protein synthesis mechanisms (10 papers), Bacterial Genetics and Biotechnology (9 papers) and Genomics and Phylogenetic Studies (4 papers). Daniel Dar is often cited by papers focused on RNA and protein synthesis mechanisms (10 papers), Bacterial Genetics and Biotechnology (9 papers) and Genomics and Phylogenetic Studies (4 papers). Daniel Dar collaborates with scholars based in Israel, United States and France. Daniel Dar's co-authors include Rotem Sorek, Pascale Cossart, Dianne K. Newman, J. R. Mellin, Mikael Koutero, Long Cai, Noam Stern‐Ginossar, Marie‐Anne Nahori, Daniela Prasse and Ruth A. Schmitz and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Daniel Dar

19 papers receiving 1.0k citations

Hit Papers

Spatial transcriptomics of planktonic and sessile bacteri... 2021 2026 2022 2024 2021 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Dar Israel 15 797 353 264 91 86 19 1.0k
Yun Luo United States 14 680 0.9× 333 0.9× 210 0.8× 114 1.3× 73 0.8× 24 949
Errett C. Hobbs United States 9 718 0.9× 546 1.5× 359 1.4× 131 1.4× 77 0.9× 13 1.1k
Daniel P. Haeusser United States 11 692 0.9× 579 1.6× 368 1.4× 93 1.0× 76 0.9× 16 979
Godefroid Charbon Denmark 18 753 0.9× 580 1.6× 226 0.9× 92 1.0× 57 0.7× 32 966
Paola Bisicchia Ireland 11 546 0.7× 496 1.4× 281 1.1× 89 1.0× 57 0.7× 11 829
Desirée C. Yang United States 7 391 0.5× 331 0.9× 180 0.7× 85 0.9× 91 1.1× 8 701
Alexander J. Meeske United States 15 957 1.2× 580 1.6× 451 1.7× 132 1.5× 117 1.4× 22 1.3k
Anna‐Barbara Hachmann United States 8 660 0.8× 415 1.2× 259 1.0× 104 1.1× 57 0.7× 10 897
Brian K. Janes United States 17 653 0.8× 437 1.2× 236 0.9× 137 1.5× 85 1.0× 24 913
María Antonia Sánchez-Romero Spain 15 570 0.7× 350 1.0× 257 1.0× 118 1.3× 138 1.6× 35 979

Countries citing papers authored by Daniel Dar

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Dar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Dar

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

All Works

19 of 19 papers shown
1.
Moffitt, Jeffrey R., Mingyao Li, Qing Nie, et al.. (2025). What is the main bottleneck in deriving biological understanding from spatial transcriptomic profiling?. Cell Systems. 16(2). 101200–101200. 1 indexed citations
2.
Theis, Fabian J., Daniel Dar, Sanja Vicković, et al.. (2023). What do you most hope spatial molecular profiling will help us understand? Part 1. Cell Systems. 14(6). 423–427. 3 indexed citations
3.
Dar, Daniel, et al.. (2021). Spatial transcriptomics of planktonic and sessile bacterial populations at single-cell resolution. Science. 373(6556). 184 indexed citations breakdown →
4.
Dar, Daniel, et al.. (2021). Spatial transcriptomics of planktonic and sessile bacterial populations at single-cell resolution. Zenodo (CERN European Organization for Nuclear Research). 4 indexed citations
5.
Dar, Daniel, Linda S. Thomashow, David M. Weller, & Dianne K. Newman. (2020). Global landscape of phenazine biosynthesis and biodegradation reveals species-specific colonization patterns in agricultural soils and crop microbiomes. eLife. 9. 46 indexed citations
6.
Thomason, Maureen K., Maya Voichek, Daniel Dar, et al.. (2019). A rhlI 5′ UTR-Derived sRNA Regulates RhlR-Dependent Quorum Sensing in Pseudomonas aeruginosa. mBio. 10(5). 40 indexed citations
7.
Duval, Mélodie, Daniel Dar, Filipe Carvalho, et al.. (2018). HflXr, a homolog of a ribosome-splitting factor, mediates antibiotic resistance. Proceedings of the National Academy of Sciences. 115(52). 13359–13364. 41 indexed citations
8.
Dar, Daniel & Rotem Sorek. (2018). Extensive reshaping of bacterial operons by programmed mRNA decay. PLoS Genetics. 14(4). e1007354–e1007354. 51 indexed citations
9.
Dar, Daniel & Rotem Sorek. (2018). High-resolution RNA 3′-ends mapping of bacterial Rho-dependent transcripts. Nucleic Acids Research. 46(13). 6797–6805. 74 indexed citations
10.
Averbuch, Diana, Rifaat Safadi, Daniel Dar, et al.. (2018). Successful Brincidofovir Treatment of Metagenomics-detected Adenovirus Infection in a Severely Ill Signal Transducer and Activator of Transcription-1-deficient Patient. The Pediatric Infectious Disease Journal. 38(3). 297–299. 6 indexed citations
11.
Dar, Daniel & Rotem Sorek. (2018). Bacterial Noncoding RNAs Excised from within Protein-Coding Transcripts. mBio. 9(5). 41 indexed citations
12.
Dar, Daniel & Rotem Sorek. (2017). Regulation of antibiotic-resistance by non-coding RNAs in bacteria. Current Opinion in Microbiology. 36. 111–117. 31 indexed citations
13.
Dar, Daniel, J. R. Mellin, Mikael Koutero, et al.. (2016). Term-seq reveals abundant ribo-regulation of antibiotics resistance in bacteria. Science. 352(6282). aad9822–aad9822. 245 indexed citations
14.
Dar, Daniel, Daniela Prasse, Ruth A. Schmitz, & Rotem Sorek. (2016). Widespread formation of alternative 3′ UTR isoforms via transcription termination in archaea. Nature Microbiology. 1(10). 16143–16143. 50 indexed citations
15.
Cohen, Ofir, Shany Doron, Omri Wurtzel, et al.. (2016). Comparative transcriptomics across the prokaryotic tree of life. Nucleic Acids Research. 44(W1). W46–W53. 31 indexed citations
16.
Millman, Adi, et al.. (2016). Computational prediction of regulatory, premature transcription termination in bacteria. Nucleic Acids Research. 45(2). 886–893. 29 indexed citations
17.
Mellin, J. R., Mikael Koutero, Daniel Dar, et al.. (2014). Sequestration of a two-component response regulator by a riboswitch-regulated noncoding RNA. Science. 345(6199). 940–943. 122 indexed citations
18.
Salomon, Dor, Eran Bosis, Daniel Dar, Iftach Nachman, & Guido Sessa. (2012). Expression of Pseudomonas syringae type III effectors in yeast under stress conditions reveals that HopX1 attenuates activation of the high osmolarity glycerol MAP kinase pathway. Microbiology. 158(11). 2859–2869. 15 indexed citations
19.
Salomon, Dor, et al.. (2010). Expression of Xanthomonas campestris pv. vesicatoria Type III Effectors in Yeast Affects Cell Growth and Viability. Molecular Plant-Microbe Interactions. 24(3). 305–314. 33 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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