Daniel Kahn

5.1k total citations
39 papers, 1.5k citations indexed

About

Daniel Kahn is a scholar working on Molecular Biology, Artificial Intelligence and Genetics. According to data from OpenAlex, Daniel Kahn has authored 39 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Molecular Biology, 5 papers in Artificial Intelligence and 5 papers in Genetics. Recurrent topics in Daniel Kahn's work include Microbial Metabolic Engineering and Bioproduction (11 papers), Genomics and Phylogenetic Studies (7 papers) and RNA and protein synthesis mechanisms (7 papers). Daniel Kahn is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (11 papers), Genomics and Phylogenetic Studies (7 papers) and RNA and protein synthesis mechanisms (7 papers). Daniel Kahn collaborates with scholars based in France, United States and Netherlands. Daniel Kahn's co-authors include Erik L. L. Sonnhammer, F. Corpet, Jérôme Gouzy, Laurent Duret, Jean-François Goût, Christopher K. Glass, Debra Archer, Mercedes Ricote, Robyn Cunard and Carolyn Kelly and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and The Journal of Immunology.

In The Last Decade

Daniel Kahn

36 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Kahn France 17 1.2k 250 215 99 89 39 1.5k
Pierre Vincens France 15 1.9k 1.6× 378 1.5× 171 0.8× 117 1.2× 114 1.3× 30 2.4k
Michele Magrane United Kingdom 14 1.7k 1.4× 192 0.8× 211 1.0× 71 0.7× 102 1.1× 21 2.2k
Randall F. Smith United States 14 1.0k 0.9× 290 1.2× 256 1.2× 31 0.3× 136 1.5× 23 1.8k
Andrew Yates United Kingdom 14 1.1k 0.9× 321 1.3× 317 1.5× 66 0.7× 74 0.8× 30 1.6k
Natalia Maltsev United States 18 1.7k 1.5× 157 0.6× 373 1.7× 51 0.5× 65 0.7× 47 2.0k
Daniel Barrell United Kingdom 12 1.6k 1.4× 255 1.0× 230 1.1× 40 0.4× 96 1.1× 14 2.1k
Michael F. Chou United States 14 1.3k 1.1× 169 0.7× 152 0.7× 41 0.4× 71 0.8× 21 1.7k
Evelyn Camon United Kingdom 16 1.5k 1.3× 211 0.8× 175 0.8× 49 0.5× 203 2.3× 19 2.0k
Andrew Hayes United Kingdom 28 2.0k 1.8× 257 1.0× 226 1.1× 99 1.0× 81 0.9× 56 2.5k
Petri Törönen Finland 19 1.5k 1.3× 543 2.2× 189 0.9× 63 0.6× 109 1.2× 40 2.3k

Countries citing papers authored by Daniel Kahn

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Kahn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Kahn

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Kahn. A scholar is included among the top collaborators of Daniel Kahn 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 Kahn. Daniel Kahn 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.
Schläpfer, Pascal, Peifen Zhang, Chuan Wang, et al.. (2017). Genome-Wide Prediction of Metabolic Enzymes, Pathways, and Gene Clusters in Plants. PLANT PHYSIOLOGY. 173(4). 2041–2059. 253 indexed citations
2.
Mièle, Vincent, Simon Penel, Vincent Daubin, et al.. (2012). High-quality sequence clustering guided by network topology and multiple alignment likelihood. Bioinformatics. 28(8). 1078–1085. 22 indexed citations
3.
Brilli, Matteo, et al.. (2012). On the identifiability of metabolic network models. Journal of Mathematical Biology. 67(6-7). 1795–1832. 26 indexed citations
4.
Baldazzi, Valentina, Delphine Ropers, Johannes Geiselmann, Daniel Kahn, & Hidde de Jong. (2011). Importance of metabolic coupling for the dynamics of gene expression following a diauxic shift in Escherichia coli. Journal of Theoretical Biology. 295. 100–115. 10 indexed citations
5.
Baldazzi, Valentina, Delphine Ropers, Yves Markowicz, et al.. (2010). The Carbon Assimilation Network in Escherichia coli Is Densely Connected and Largely Sign-Determined by Directions of Metabolic Fluxes. PLoS Computational Biology. 6(6). e1000812–e1000812. 49 indexed citations
6.
Goût, Jean-François, Daniel Kahn, & Laurent Duret. (2010). The Relationship among Gene Expression, the Evolution of Gene Dosage, and the Rate of Protein Evolution. PLoS Genetics. 6(5). e1000944–e1000944. 150 indexed citations
7.
Goût, Jean-François, Daniel Kahn, & Laurent Duret. (2010). Correction: The Relationship among Gene Expression, the Evolution of Gene Dosage, and the Rate of Protein Evolution. PLoS Genetics. 6(6). 19 indexed citations
8.
Goût, Jean-François, Laurent Duret, & Daniel Kahn. (2009). Differential Retention of Metabolic Genes Following Whole-Genome Duplication. Molecular Biology and Evolution. 26(5). 1067–1072. 29 indexed citations
9.
Handorf, Thomas, Nils Christian, Oliver Ebenhöh, & Daniel Kahn. (2007). An environmental perspective on metabolism. Journal of Theoretical Biology. 252(3). 530–537. 44 indexed citations
10.
Handorf, Thomas, Oliver Ebenhöh, Daniel Kahn, & R. Heinrich. (2006). Hierarchy of metabolic compounds based on their synthesising capacity. PubMed. 153(5). 359–359. 7 indexed citations
11.
Corpet, F., Jérôme Gouzy, & Daniel Kahn. (1999). Recent improvements of the ProDom database of protein domain families. Nucleic Acids Research. 27(1). 263–267. 140 indexed citations
12.
Gouzy, Jérôme, et al.. (1997). XDOM, a graphical tool to analyse domain arrangements in any set of protein sequences. Computer applications in the biosciences. 13(6). 601–608. 23 indexed citations
13.
Heeswijk, Wally C. van, et al.. (1996). An alternative PII protein in the regulation of glutamine synthetase in Escherichia coli. HAL (Le Centre pour la Communication Scientifique Directe). 6 indexed citations
14.
Gouzy, Jérôme, F. Corpet, & Daniel Kahn. (1996). Graphical interface for ProDom domain families. Trends in Biochemical Sciences. 21(12). 493–493. 11 indexed citations
15.
Sonnhammer, Erik L. L. & Daniel Kahn. (1994). Modular arrangement of proteins as inferred from analysis of homology. Protein Science. 3(3). 482–492. 183 indexed citations
16.
Heeswijk, Wally C. van, et al.. (1993). The genes of the glutamine synthetase adenylylation cascade are not regulated by nitrogen in Escherichia coli. HAL (Le Centre pour la Communication Scientifique Directe). 5 indexed citations
17.
Kahn, Daniel & Hans V. Westerhoff. (1993). The regulatory strength: How to be precise about regulation and homeostasis. Acta Biotheoretica. 41(1-2). 85–96. 35 indexed citations
18.
Ide, Charles F., et al.. (1987). Healing modes correlate with visuotectal pattern formation in regenerating embryonic Xenopus retina. Developmental Biology. 124(2). 316–330. 13 indexed citations
19.
Kahn, Daniel, et al.. (1985). Relationship between LP-residual spectral distances and phonetic judgments. The Journal of the Acoustical Society of America. 78(S1). S82–S82. 1 indexed citations
20.
Blanquet, Sylvain, Philippe Dessen, & Daniel Kahn. (1984). [11] Properties and specificity of methionyl-tRNAfMet formyltransferase from Escherichia coli. Methods in enzymology on CD-ROM/Methods in enzymology. 106. 141–152. 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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