Ann Hochschild

7.1k total citations · 1 hit paper
90 papers, 5.6k citations indexed

About

Ann Hochschild is a scholar working on Molecular Biology, Genetics and Ecology. According to data from OpenAlex, Ann Hochschild has authored 90 papers receiving a total of 5.6k indexed citations (citations by other indexed papers that have themselves been cited), including 87 papers in Molecular Biology, 67 papers in Genetics and 44 papers in Ecology. Recurrent topics in Ann Hochschild's work include Bacterial Genetics and Biotechnology (67 papers), RNA and protein synthesis mechanisms (61 papers) and Bacteriophages and microbial interactions (44 papers). Ann Hochschild is often cited by papers focused on Bacterial Genetics and Biotechnology (67 papers), RNA and protein synthesis mechanisms (61 papers) and Bacteriophages and microbial interactions (44 papers). Ann Hochschild collaborates with scholars based in United States, United Kingdom and Australia. Ann Hochschild's co-authors include Mark Ptashne, Simon L. Dove, Bryce E. Nickels, Poulami Samai, Luciano A. Marraffini, Wenyan Jiang, David Bikard, Feng Zhang, J. Keith Joung and Nina Irwin and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Ann Hochschild

89 papers receiving 5.5k citations

Hit Papers

Programmable repression and activation of bacterial gene ... 2013 2026 2017 2021 2013 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ann Hochschild United States 42 5.0k 2.9k 1.6k 298 270 90 5.6k
Shoshy Altuvia Israel 32 3.5k 0.7× 2.4k 0.8× 1.5k 1.0× 311 1.0× 497 1.8× 50 4.6k
Agamemnon J. Carpousis France 39 4.8k 1.0× 3.2k 1.1× 1.7k 1.1× 173 0.6× 158 0.6× 65 5.2k
Ding Jun Jin United States 32 2.6k 0.5× 1.9k 0.7× 860 0.5× 279 0.9× 262 1.0× 69 3.5k
Jan‐Willem De Gier Sweden 38 3.3k 0.7× 2.0k 0.7× 883 0.6× 201 0.7× 382 1.4× 68 4.2k
Henri Buc France 36 4.0k 0.8× 2.2k 0.8× 708 0.5× 503 1.7× 266 1.0× 79 4.9k
Reid C. Johnson United States 49 5.9k 1.2× 3.4k 1.2× 1.6k 1.1× 139 0.5× 435 1.6× 122 7.0k
Sergei Borukhov United States 31 3.6k 0.7× 2.0k 0.7× 1.0k 0.6× 172 0.6× 111 0.4× 59 4.0k
Hiroji Aiba Japan 38 3.8k 0.8× 2.8k 1.0× 1.3k 0.8× 144 0.5× 318 1.2× 60 4.5k
Ross Dalbey United States 52 6.2k 1.2× 3.7k 1.3× 1.3k 0.8× 299 1.0× 480 1.8× 119 7.5k
Diane K. Hawley United States 20 3.9k 0.8× 2.1k 0.7× 780 0.5× 146 0.5× 158 0.6× 27 4.6k

Countries citing papers authored by Ann Hochschild

Since Specialization
Citations

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

Fields of papers citing papers by Ann Hochschild

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ann Hochschild

This figure shows the co-authorship network connecting the top 25 collaborators of Ann Hochschild. A scholar is included among the top collaborators of Ann Hochschild 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 Ann Hochschild. Ann Hochschild 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.
Paulo, João A., et al.. (2024). Systematic analysis of nonprogrammed frameshift suppression in E. coli via translational tiling proteomics. Proceedings of the National Academy of Sciences. 121(6). e2317453121–e2317453121.
2.
McDonough, EmilyKate, Eleanor Fleming, Giselle McCallum, et al.. (2023). Measuring prion propagation in single bacteria elucidates a mechanism of loss. Proceedings of the National Academy of Sciences. 120(39). e2221539120–e2221539120. 4 indexed citations
3.
Huang, Linfeng, Padraig Deighan, Jingmin Jin, et al.. (2020). Tombusvirus p19 Captures RNase III-Cleaved Double-Stranded RNAs Formed by Overlapping Sense and Antisense Transcripts in Escherichia coli. mBio. 11(3). 5 indexed citations
4.
Yuan, Andy H. & Ann Hochschild. (2017). A bacterial global regulator forms a prion. Science. 355(6321). 198–201. 113 indexed citations
5.
Heller, Danielle M., et al.. (2017). CbtA toxin of Escherichia coli inhibits cell division and cell elongation via direct and independent interactions with FtsZ and MreB. PLoS Genetics. 13(9). e1007007–e1007007. 35 indexed citations
6.
Bikard, David, Wenyan Jiang, Poulami Samai, et al.. (2013). Programmable repression and activation of bacterial gene expression using an engineered CRISPR-Cas system. Nucleic Acids Research. 41(15). 7429–7437. 866 indexed citations breakdown →
7.
Deighan, Padraig, et al.. (2011). Initial transcribed region sequences influence the composition and functional properties of the bacterial elongation complex. Genes & Development. 25(1). 77–88. 34 indexed citations
8.
Stayrook, Steven E., et al.. (2008). Crystal structure of the λ repressor and a model for pairwise cooperative operator binding. Nature. 452(7190). 1022–1025. 82 indexed citations
9.
Hochschild, Ann, et al.. (2007). A σ‐core interaction of the RNA polymerase holoenzyme that enhances promoter escape. The EMBO Journal. 26(6). 1579–1590. 27 indexed citations
10.
Pinkett, Heather W., Keith E. Shearwin, Steven E. Stayrook, et al.. (2006). The Structural Basis of Cooperative Regulation at an Alternate Genetic Switch. Molecular Cell. 21(5). 605–615. 27 indexed citations
11.
Nickels, Bryce E., et al.. (2006). RNA-Mediated Destabilization of the σ70 Region 4/β Flap Interaction Facilitates Engagement of RNA Polymerase by the Q Antiterminator. Molecular Cell. 24(3). 457–468. 25 indexed citations
12.
Nickels, Bryce E., Vladimir Mekler, Leonid Minakhin, et al.. (2005). The interaction between σ 70 and the β-flap of Escherichia coli RNA polymerase inhibits extension of nascent RNA during early elongation. Proceedings of the National Academy of Sciences. 102(12). 4488–4493. 72 indexed citations
13.
Gregory, Brian D., Padraig Deighan, & Ann Hochschild. (2005). An Artificial Activator that Contacts a Normally Occluded Surface of the RNA Polymerase Holoenzyme. Journal of Molecular Biology. 353(3). 497–506. 5 indexed citations
14.
Nickels, Bryce E., et al.. (2004). The σ70 subunit of RNA polymerase mediates a promoter-proximal pause at the lac promoter. Nature Structural & Molecular Biology. 11(6). 544–550. 72 indexed citations
15.
Hochschild, Ann. (2002). The λ Switch: cI Closes the Gap in Autoregulation. Current Biology. 12(3). R87–R89. 15 indexed citations
16.
Nickels, Bryce E., et al.. (2002). The σ70 Subunit of RNA Polymerase Is Contacted by the λQ Antiterminator during Early Elongation. Molecular Cell. 10(3). 611–622. 52 indexed citations
18.
Dove, Simon L., J. Keith Joung, & Ann Hochschild. (1997). Activation of prokaryotic transcription through arbitrary protein–protein contacts. Nature. 386(6625). 627–630. 232 indexed citations
19.
Ptashne, Mark, et al.. (1997). The activation defect of a λcI positive control mutant. Journal of Molecular Biology. 265(3). 261–265. 9 indexed citations
20.
Hochschild, Ann. (1990). 3 Protein-Protein Interactions and DNA Loop Formation. Cold Spring Harbor Monograph Archive. 20. 107–138. 14 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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