Daniel S. Kessler

5.8k total citations · 1 hit paper
49 papers, 5.0k citations indexed

About

Daniel S. Kessler is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Daniel S. Kessler has authored 49 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Molecular Biology, 12 papers in Immunology and 11 papers in Oncology. Recurrent topics in Daniel S. Kessler's work include Developmental Biology and Gene Regulation (21 papers), Pluripotent Stem Cells Research (11 papers) and Cytokine Signaling Pathways and Interactions (10 papers). Daniel S. Kessler is often cited by papers focused on Developmental Biology and Gene Regulation (21 papers), Pluripotent Stem Cells Research (11 papers) and Cytokine Signaling Pathways and Interactions (10 papers). Daniel S. Kessler collaborates with scholars based in United States, Germany and South Korea. Daniel S. Kessler's co-authors include David T. Levy, James Darnell, Richard Pine, Douglas A. Melton, J E Darnell, Susan A. Veals, Xin‐Yuan Fu, Thomas Decker, Nancy C. Reich and Patricia A. Labosky and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Daniel S. Kessler

49 papers receiving 4.8k citations

Hit Papers

Interferon-induced nuclear factors that bind a shared pro... 1988 2026 2000 2013 1988 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel S. Kessler United States 34 3.0k 2.1k 1.8k 525 515 49 5.0k
Rikiro Fukunaga Japan 32 3.3k 1.1× 1.7k 0.8× 1.3k 0.8× 440 0.8× 831 1.6× 71 5.7k
Erika A Bach United States 29 2.0k 0.7× 2.9k 1.4× 2.0k 1.2× 386 0.7× 333 0.6× 48 5.1k
Elizabeth J. Taparowsky United States 39 3.3k 1.1× 1.7k 0.8× 1.4k 0.8× 592 1.1× 658 1.3× 74 5.6k
Kei-ichi Nakayama Japan 28 4.9k 1.6× 2.2k 1.0× 2.6k 1.5× 723 1.4× 532 1.0× 39 7.5k
Issay Kitabayashi Japan 41 4.4k 1.5× 1.2k 0.6× 1.1k 0.7× 531 1.0× 557 1.1× 121 6.1k
Michel Streuli United States 45 5.5k 1.9× 3.2k 1.5× 1.2k 0.7× 414 0.8× 483 0.9× 60 8.1k
James Hagman United States 40 3.0k 1.0× 3.3k 1.6× 909 0.5× 537 1.0× 507 1.0× 81 6.3k
David L. Wiest United States 42 2.3k 0.8× 3.4k 1.6× 1.1k 0.6× 396 0.8× 302 0.6× 124 5.3k
Atsuo Kawahara Japan 34 3.3k 1.1× 1.9k 0.9× 1.3k 0.7× 492 0.9× 459 0.9× 79 5.3k
Elaine Spooncer United Kingdom 33 2.4k 0.8× 1.3k 0.6× 789 0.5× 304 0.6× 543 1.1× 77 4.7k

Countries citing papers authored by Daniel S. Kessler

Since Specialization
Citations

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

Fields of papers citing papers by Daniel S. Kessler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel S. Kessler

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel S. Kessler. A scholar is included among the top collaborators of Daniel S. Kessler 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 S. Kessler. Daniel S. Kessler 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.
Waschbüsch, Dieter, Helen Michels, Edith Ossendorf, et al.. (2014). LRRK2 Transport Is Regulated by Its Novel Interacting Partner Rab32. PLoS ONE. 9(10). e111632–e111632. 75 indexed citations
2.
Zhang, Yan, et al.. (2012). Transcriptional integration of Wnt and Nodal pathways in establishment of the Spemann organizer. Developmental Biology. 368(2). 231–241. 21 indexed citations
3.
Kessler, Daniel S., Dominik Heider, Jessica Morgner, et al.. (2012). The Action of Small GTPases Rab11 and Rab25 in Vesicle Trafficking During Cell Migration. Cellular Physiology and Biochemistry. 29(5-6). 647–656. 36 indexed citations
4.
Kessler, Daniel S., et al.. (2010). Foxd3 is an essential Nodal-dependent regulator of zebrafish dorsal mesoderm development. Developmental Biology. 342(1). 39–50. 13 indexed citations
5.
Blythe, Shelby A., et al.. (2009). Chromatin immunoprecipitation in early Xenopus laevis embryos. Developmental Dynamics. 238(6). 1422–1432. 74 indexed citations
6.
Barnekow, Angelika, et al.. (2009). Chapter 5 Rab Proteins and Their Interaction Partners. International review of cell and molecular biology. 274. 235–274. 19 indexed citations
7.
8.
Stayrook, Steven E., et al.. (2007). Prevalence of the EH1 Groucho interaction motif in the metazoan Fox family of transcriptional regulators. BMC Genomics. 8(1). 201–201. 33 indexed citations
9.
Kessler, Daniel S., et al.. (2006). FoxD3 and Grg4 Physically Interact to Repress Transcription and Induce Mesoderm in Xenopus. Journal of Biological Chemistry. 282(4). 2548–2557. 56 indexed citations
11.
O’Hara, F. Patrick, et al.. (2005). Zebrafish Lmx1b.1 and Lmx1b.2 are required for maintenance of the isthmic organizer. Development. 132(14). 3163–3173. 38 indexed citations
12.
Yao, Jie & Daniel S. Kessler. (2003). Mesoderm Induction in Xenopus: Oocyte Expression System and Animal Cap Assay. Humana Press eBooks. 137. 169–178. 4 indexed citations
13.
Engleka, Mark J., et al.. (2001). VegT Activation of Sox17 at the Midblastula Transition Alters the Response to Nodal Signals in the Vegetal Endoderm Domain. Developmental Biology. 237(1). 159–172. 43 indexed citations
14.
Engleka, Mark J. & Daniel S. Kessler. (2001). Siamois cooperates with TGFbeta signals to induce the complete function of the Spemann-Mangold organizer. The International Journal of Developmental Biology. 45(1). 241–250. 19 indexed citations
15.
Yao, Jie & Daniel S. Kessler. (2001). Goosecoid promotes head organizer activity by direct repression of Xwnt8 in Spemann’s organizer. Development. 128(15). 2975–2987. 63 indexed citations
16.
Wall, Nancy A., et al.. (2000). Mesendoderm Induction and Reversal of Left–Right Pattern by Mouse Gdf1, a Vg1-Related Gene. Developmental Biology. 227(2). 495–509. 60 indexed citations
17.
Conlon, Frank L. & Daniel S. Kessler. (2000). Hopping into the new millennium. Trends in Genetics. 16(12). 537–540. 1 indexed citations
18.
Huang, Weidong, Daniel S. Kessler, & Raymond L. Erikson. (1995). Biochemical and biological analysis of Mek1 phosphorylation site mutants.. Molecular Biology of the Cell. 6(3). 237–245. 102 indexed citations
19.
Pine, Richard, Thomas Decker, Daniel S. Kessler, David T. Levy, & James Darnell. (1990). Purification and Cloning of Interferon-Stimulated Gene Factor 2 (ISGF2): ISGF2 (IRF-1) Can Bind to the Promoters of Both Beta Interferon- and Interferon-Stimulated Genes but Is Not a Primary Transcriptional Activator of Either. Molecular and Cellular Biology. 10(6). 2448–2457. 111 indexed citations
20.
Levy, David T., Nancy C. Reich, Daniel S. Kessler, Richard Pine, & James Darnell. (1988). Transcriptional Regulation of Interferon-stimulated Genes: A DNA Response Element and Induced Proteins That Recognize It. Cold Spring Harbor Symposia on Quantitative Biology. 53(0). 799–802. 22 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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