Mitchell Guttman

54.1k total citations · 18 hit papers
65 papers, 23.3k citations indexed

About

Mitchell Guttman is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Mitchell Guttman has authored 65 papers receiving a total of 23.3k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Molecular Biology, 36 papers in Cancer Research and 7 papers in Genetics. Recurrent topics in Mitchell Guttman's work include RNA Research and Splicing (45 papers), Cancer-related molecular mechanisms research (33 papers) and RNA modifications and cancer (27 papers). Mitchell Guttman is often cited by papers focused on RNA Research and Splicing (45 papers), Cancer-related molecular mechanisms research (33 papers) and RNA modifications and cancer (27 papers). Mitchell Guttman collaborates with scholars based in United States, United Kingdom and Germany. Mitchell Guttman's co-authors include John L. Rinn, Eric S. Lander, Manuel Garber, Aviv Regev, Maite Huarte, J Engreitz, Ido Amit, Amy Chow, B Bernstein and Ahmad M. Khalil and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Mitchell Guttman

65 papers receiving 23.1k citations

Hit Papers

Chromatin signature reveals over a thousand highly conser... 2009 2026 2014 2020 2009 2009 2012 2010 2011 1000 2.0k 3.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals
    2009 3.3k citations Mitchell Guttman, Manuel Garber et al. profile →
  2. Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression
    2009 2.3k citations Ahmad M. Khalil, Mitchell Guttman et al. Proceedings of the National Academy of Sciences profile →
  3. Modular regulatory principles of large non-coding RNAs
    2012 1.8k citations Mitchell Guttman, John L. Rinn profile →
  4. A Large Intergenic Noncoding RNA Induced by p53 Mediates Global Gene Repression in the p53 Response
    2010 1.7k citations Maite Huarte, Mitchell Guttman et al. Cell profile →
  5. lincRNAs act in the circuitry controlling pluripotency and differentiation
    2011 1.5k citations Mitchell Guttman, Manuel Garber et al. profile →
  6. m6A RNA methylation promotes XIST-mediated transcriptional repression
    2016 1.3k citations Chun‐Kan Chen, Amy Chow et al. profile →
  7. Ab initio reconstruction of cell type–specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs
    2010 952 citations Mitchell Guttman, Manuel Garber et al. Nature Biotechnology profile →
  8. Local regulation of gene expression by lncRNA promoters, transcription and splicing
    2016 905 citations J Engreitz, Patrick McDonel et al. profile →
  9. Robust transcriptome-wide discovery of RNA-binding protein binding sites with enhanced CLIP (eCLIP)
    2016 863 citations Eric L. Van Nostrand, Gabriel A. Pratt et al. Nature Methods profile →
  10. The Xist lncRNA interacts directly with SHARP to silence transcription through HDAC3
    2015 837 citations Colleen A. McHugh, Chun‐Kan Chen et al. profile →
  11. Transcriptome-wide Mapping Reveals Widespread Dynamic-Regulated Pseudouridylation of ncRNA and mRNA
    2014 759 citations J Engreitz, Mitchell Guttman et al. Cell profile →
  12. Computational methods for transcriptome annotation and quantification using RNA-seq
    2011 751 citations Manuel Garber, Mitchell Guttman et al. Nature Methods profile →
  13. Ribosome Profiling Provides Evidence that Large Noncoding RNAs Do Not Encode Proteins
    2013 594 citations Mitchell Guttman, Pamela Russell et al. Cell profile →
  14. Higher-Order Inter-chromosomal Hubs Shape 3D Genome Organization in the Nucleus
    2018 568 citations Sofia A. Quinodoz, Noah Ollikainen et al. Cell profile →
  15. Long non-coding RNAs: spatial amplifiers that control nuclear structure and gene expression
    2016 446 citations J Engreitz, Noah Ollikainen et al. profile →
  16. The 4D nucleome project
    2017 439 citations Mitchell Guttman et al. profile →
  17. Integrated spatial genomics reveals global architecture of single nuclei
    2021 249 citations Noah Ollikainen, Mitchell Guttman et al. profile →
  18. RNA promotes the formation of spatial compartments in the nucleus
    2021 231 citations Sofia A. Quinodoz, Joanna W. Jachowicz et al. Cell profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mitchell Guttman United States 43 20.7k 14.6k 1.6k 1.2k 939 65 23.3k
Marcel E. Dinger Australia 52 17.4k 0.8× 14.2k 1.0× 1.4k 0.9× 793 0.7× 955 1.0× 144 20.6k
Manuel Garber United States 35 13.9k 0.7× 9.7k 0.7× 1.8k 1.1× 1.0k 0.8× 894 1.0× 58 17.0k
Tim R. Mercer Australia 40 12.8k 0.6× 10.0k 0.7× 952 0.6× 626 0.5× 709 0.8× 80 15.1k
Ryan A. Flynn United States 38 12.9k 0.6× 5.0k 0.3× 1.0k 0.6× 962 0.8× 415 0.4× 69 14.3k
Mihaela Zavolan Switzerland 63 16.5k 0.8× 9.1k 0.6× 929 0.6× 1.8k 1.5× 1.2k 1.3× 141 19.7k
Elisa Izaurralde Germany 89 22.9k 1.1× 5.8k 0.4× 1.4k 0.9× 1.8k 1.5× 860 0.9× 163 25.6k
Nicholas T. Ingolia United States 48 15.1k 0.7× 4.0k 0.3× 1.2k 0.8× 821 0.7× 1.1k 1.2× 89 18.1k
Richard W. Carthew United States 52 13.1k 0.6× 4.8k 0.3× 1.8k 1.2× 2.5k 2.1× 529 0.6× 105 17.0k
Igor Ulitsky Israel 48 9.5k 0.5× 6.6k 0.4× 587 0.4× 494 0.4× 406 0.4× 94 11.2k
Lee P. Lim United States 27 17.8k 0.9× 14.2k 1.0× 958 0.6× 2.6k 2.2× 567 0.6× 47 21.6k

Countries citing papers authored by Mitchell Guttman

Since Specialization
Citations

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

Fields of papers citing papers by Mitchell Guttman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mitchell Guttman

This figure shows the co-authorship network connecting the top 25 collaborators of Mitchell Guttman. A scholar is included among the top collaborators of Mitchell Guttman 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 Mitchell Guttman. Mitchell Guttman 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.
Guo, Jimmy K., Mario R. Blanco, Ward G. Walkup, et al.. (2024). Denaturing purifications demonstrate that PRC2 and other widely reported chromatin proteins do not appear to bind directly to RNA in vivo. Molecular Cell. 84(7). 1271–1289.e12. 44 indexed citations
2.
Perez, Andrew, et al.. (2024). ChIP-DIP maps binding of hundreds of proteins to DNA simultaneously and identifies diverse gene regulatory elements. Nature Genetics. 56(12). 2827–2841. 7 indexed citations
3.
Kitchen, Sheila A., Adrian Brückner, Mark S. Ladinsky, et al.. (2024). The genomic and cellular basis of biosynthetic innovation in rove beetles. Cell. 187(14). 3563–3584.e26. 6 indexed citations
4.
Quinodoz, Sofia A., Prashant Bhat, Peter Chovanec, et al.. (2022). SPRITE: a genome-wide method for mapping higher-order 3D interactions in the nucleus using combinatorial split-and-pool barcoding. Nature Protocols. 17(1). 36–75. 32 indexed citations
5.
Jachowicz, Joanna W., et al.. (2022). Xist spatially amplifies SHARP/SPEN recruitment to balance chromosome-wide silencing and specificity to the X chromosome. Nature Structural & Molecular Biology. 29(3). 239–249. 70 indexed citations
6.
Jachowicz, Joanna W., Noah Ollikainen, Matthew S. Curtis, et al.. (2021). Single-cell measurement of higher-order 3D genome organization with scSPRITE. Nature Biotechnology. 40(1). 64–73. 75 indexed citations
7.
Quinodoz, Sofia A., Joanna W. Jachowicz, Prashant Bhat, et al.. (2021). RNA promotes the formation of spatial compartments in the nucleus. Cell. 184(23). 5775–5790.e30. 231 indexed citations breakdown →
8.
Strehle, Mackenzie & Mitchell Guttman. (2020). Xist drives spatial compartmentalization of DNA and protein to orchestrate initiation and maintenance of X inactivation. Current Opinion in Cell Biology. 64. 139–147. 32 indexed citations
9.
Bemmel, Joke G. van, Rafael Galupa, Nicolas Servant, et al.. (2019). The bipartite TAD organization of the X-inactivation center ensures opposing developmental regulation of Tsix and Xist. Nature Genetics. 51(6). 1024–1034. 55 indexed citations
10.
Blanco, Mario R., Erik Aznauryan, Noah Ollikainen, et al.. (2016). Xist recruits the X chromosome to the nuclear lamina to enable chromosome-wide silencing. Science. 354(6311). 468–472. 193 indexed citations
11.
Nostrand, Eric L. Van, Gabriel A. Pratt, A.A. Shishkin, et al.. (2016). Robust transcriptome-wide discovery of RNA-binding protein binding sites with enhanced CLIP (eCLIP). Nature Methods. 13(6). 508–514. 863 indexed citations breakdown →
12.
McHugh, Colleen A., Chun‐Kan Chen, Amy Chow, et al.. (2015). The Xist lncRNA interacts directly with SHARP to silence transcription through HDAC3. RePEc: Research Papers in Economics. 3 indexed citations
13.
Paten, Benedict, Mark Diekhans, Brian Druker, et al.. (2015). The NIH BD2K center for big data in translational genomics. Journal of the American Medical Informatics Association. 22(6). 1143–1147. 24 indexed citations
14.
Quinodoz, Sofia A. & Mitchell Guttman. (2014). Long noncoding RNAs: an emerging link between gene regulation and nuclear organization. Trends in Cell Biology. 24(11). 651–663. 257 indexed citations
15.
Engreitz, J, Amy Pandya‐Jones, Patrick McDonel, et al.. (2013). The Xist lncRNA Exploits Three-Dimensional Genome Architecture to Spread Across the X Chromosome. Science. 341(6147). 1237973–1237973. 48 indexed citations
16.
Guttman, Mitchell, Pamela Russell, Nicholas T. Ingolia, Jonathan S. Weissman, & Eric S. Lander. (2013). Ribosome Profiling Provides Evidence that Large Noncoding RNAs Do Not Encode Proteins. Cell. 154(1). 240–251. 594 indexed citations breakdown →
17.
Robinson, James, Helga Thorvaldsdóttir, Wendy Winckler, et al.. (2011). Integrative Genomics Viewer. DSpace@MIT (Massachusetts Institute of Technology). 1 indexed citations
18.
Khalil, Ahmad M., Mitchell Guttman, Maite Huarte, et al.. (2009). Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression. Proceedings of the National Academy of Sciences. 106(28). 11667–11672. 2331 indexed citations breakdown →
19.
Ma, Changqing, Meraj Aziz, S. Rao, et al.. (2007). Genomic copy number alterations in non-small cell lung cancers identified using CBS and MSA. Journal of Clinical Oncology. 25(18_suppl). 7695–7695. 1 indexed citations
20.
Suyama, Kimita, Irina M. Shapiro, Mitchell Guttman, & Ronen Hazan. (2002). A signaling pathway leading to metastasis is controlled by N-cadherin and the FGF receptor. Cancer Cell. 2(4). 301–314. 404 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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