Judith A. Kassis

5.0k total citations
59 papers, 3.9k citations indexed

About

Judith A. Kassis is a scholar working on Molecular Biology, Plant Science and Genetics. According to data from OpenAlex, Judith A. Kassis has authored 59 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Molecular Biology, 17 papers in Plant Science and 13 papers in Genetics. Recurrent topics in Judith A. Kassis's work include Genomics and Chromatin Dynamics (37 papers), Epigenetics and DNA Methylation (25 papers) and Cancer-related gene regulation (14 papers). Judith A. Kassis is often cited by papers focused on Genomics and Chromatin Dynamics (37 papers), Epigenetics and DNA Methylation (25 papers) and Cancer-related gene regulation (14 papers). Judith A. Kassis collaborates with scholars based in United States, Germany and Russia. Judith A. Kassis's co-authors include J. Lesley Brown, Jürg Müller, Patrick H. O’Farrell, Mary Whiteley, Ward F. Odenwald, Cornelia Fritsch, Stephen DiNardo, Liangjun Wang, Ru Cao and Richard S. Jones and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Judith A. Kassis

58 papers receiving 3.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Judith A. Kassis United States 32 3.5k 813 805 253 248 59 3.9k
James A. Kennison United States 26 3.3k 0.9× 778 1.0× 634 0.8× 193 0.8× 184 0.7× 45 3.6k
Pamela Geyer United States 38 3.7k 1.0× 1.5k 1.8× 810 1.0× 221 0.9× 179 0.7× 75 4.1k
Dale Dorsett United States 41 4.5k 1.3× 1.2k 1.5× 865 1.1× 146 0.6× 220 0.9× 79 4.9k
Asato Kuroiwa Japan 28 1.6k 0.4× 778 1.0× 1.2k 1.5× 225 0.9× 250 1.0× 82 2.8k
Dena M. Johnson-Schlitz United States 15 2.3k 0.7× 1.1k 1.4× 565 0.7× 416 1.6× 170 0.7× 21 2.8k
James B. Jaynes United States 33 3.3k 0.9× 575 0.7× 745 0.9× 697 2.8× 258 1.0× 53 3.8k
Allen Laughon United States 24 2.9k 0.8× 393 0.5× 699 0.9× 338 1.3× 160 0.6× 33 3.2k
Renate Renkawitz‐Pohl Germany 33 2.9k 0.8× 614 0.8× 964 1.2× 372 1.5× 307 1.2× 85 3.7k
Pavel Georgiev Russia 41 4.2k 1.2× 2.1k 2.5× 620 0.8× 223 0.9× 147 0.6× 275 4.7k
Hugh W. Brock Canada 42 4.9k 1.4× 981 1.2× 764 0.9× 383 1.5× 335 1.4× 86 5.6k

Countries citing papers authored by Judith A. Kassis

Since Specialization
Citations

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

Fields of papers citing papers by Judith A. Kassis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Judith A. Kassis. 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 Judith A. Kassis. The network helps show where Judith A. Kassis may publish in the future.

Co-authorship network of co-authors of Judith A. Kassis

This figure shows the co-authorship network connecting the top 25 collaborators of Judith A. Kassis. A scholar is included among the top collaborators of Judith A. Kassis 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 Judith A. Kassis. Judith A. Kassis 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.
Brown, J. Lesley, Liangliang Zhang, Pedro P. Rocha, Judith A. Kassis, & Ming-an Sun. (2024). Polycomb protein binding and looping in the ON transcriptional state. Science Advances. 10(17). eadn1837–eadn1837. 3 indexed citations
2.
Erokhin, Maksim, J. Lesley Brown, Nadezhda E. Vorobyeva, et al.. (2023). Crol contributes to PRE-mediated repression and Polycomb group proteins recruitment inDrosophila. Nucleic Acids Research. 51(12). 6087–6100. 6 indexed citations
3.
Brown, J. Lesley, et al.. (2023). Context-dependent role of Pho binding sites in Polycomb complex recruitment in Drosophila. Genetics. 224(4). 2 indexed citations
4.
Cheng, Yuzhong, et al.. (2023). The activity of engrailed imaginal disc enhancers is modulated epigenetically by chromatin and autoregulation. PLoS Genetics. 19(11). e1010826–e1010826. 3 indexed citations
5.
Mitra, Apratim, Beenish Rahat, Claudia Gebert, et al.. (2022). Decreasing Wapl dosage partially corrects embryonic growth and brain transcriptome phenotypes in Nipbl +/− embryos. Science Advances. 8(48). eadd4136–eadd4136. 4 indexed citations
6.
Kuroda, Mitzi I., et al.. (2020). Dynamic Competition of Polycomb and Trithorax in Transcriptional Programming. Annual Review of Biochemistry. 89(1). 235–253. 74 indexed citations
7.
De, Sandip, Apratim Mitra, Yuzhong Cheng, Karl Pfeifer, & Judith A. Kassis. (2016). Formation of a Polycomb-Domain in the Absence of Strong Polycomb Response Elements. PLoS Genetics. 12(7). e1006200–e1006200. 32 indexed citations
8.
Cheng, Yuzhong, et al.. (2014). Co-regulation of invected and engrailed by a complex array of regulatory sequences in Drosophila. Developmental Biology. 395(1). 131–143. 27 indexed citations
9.
Dorsett, Dale & Judith A. Kassis. (2014). Checks and Balances between Cohesin and Polycomb in Gene Silencing and Transcription. Current Biology. 24(11). R535–R539. 13 indexed citations
10.
Kassis, Judith A. & J. Lesley Brown. (2013). Polycomb Group Response Elements in Drosophila and Vertebrates. Advances in genetics. 81. 83–118. 164 indexed citations
11.
Langlais, Kristofor K., J. Lesley Brown, & Judith A. Kassis. (2012). Polycomb Group Proteins Bind an engrailed PRE in Both the “ON” and “OFF” Transcriptional States of engrailed. PLoS ONE. 7(11). e48765–e48765. 25 indexed citations
12.
Cheng, Yuzhong, et al.. (2012). P-Element Homing Is Facilitated by engrailed Polycomb-Group Response Elements in Drosophila melanogaster. PLoS ONE. 7(1). e30437–e30437. 11 indexed citations
13.
Kwon, Deborah Y., et al.. (2008). The role of Polycomb-group response elements in regulation of engrailed transcription in Drosophila. Development. 135(4). 669–676. 46 indexed citations
14.
Müller, Jürg & Judith A. Kassis. (2006). Polycomb response elements and targeting of Polycomb group proteins in Drosophila. Current Opinion in Genetics & Development. 16(5). 476–484. 207 indexed citations
15.
Brown, J. Lesley, et al.. (1998). The Drosophila Polycomb Group Gene pleiohomeotic Encodes a DNA Binding Protein with Homology to the Transcription Factor YY1. Molecular Cell. 1(7). 1057–1064. 343 indexed citations
16.
17.
Kassis, Judith A., et al.. (1991). A fragment of engrailed regulatory DNA can mediate transvection of the white gene in Drosophila.. Genetics. 128(4). 751–761. 95 indexed citations
18.
Kassis, Judith A., et al.. (1990). A synthetic homeodomain binding site acts as a cell type specific, promoter specific enhancer in Drosophila embryos.. The EMBO Journal. 9(8). 2573–2578. 46 indexed citations
19.
DiNardo, Stephen, et al.. (1988). Two-tiered regulation of spatially patterned engrailed gene expression during Drosophila embryogenesis. Nature. 332(6165). 604–609. 356 indexed citations
20.
Kassis, Judith A., Mei Lie Wong, & Patrick H. O’Farrell. (1985). Electron Microscopic Heteroduplex Mapping Identifies Regions of the engrailed Locus That Are Conserved between Drosophila melanogaster and Drosophila virilis. Molecular and Cellular Biology. 5(12). 3600–3609. 7 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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