Olga Danilchanka

2.5k total citations · 1 hit paper
17 papers, 1.8k citations indexed

About

Olga Danilchanka is a scholar working on Infectious Diseases, Epidemiology and Molecular Biology. According to data from OpenAlex, Olga Danilchanka has authored 17 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Infectious Diseases, 9 papers in Epidemiology and 5 papers in Molecular Biology. Recurrent topics in Olga Danilchanka's work include Tuberculosis Research and Epidemiology (10 papers), Mycobacterium research and diagnosis (8 papers) and Antibiotic Resistance in Bacteria (5 papers). Olga Danilchanka is often cited by papers focused on Tuberculosis Research and Epidemiology (10 papers), Mycobacterium research and diagnosis (8 papers) and Antibiotic Resistance in Bacteria (5 papers). Olga Danilchanka collaborates with scholars based in United States, Germany and United Kingdom. Olga Danilchanka's co-authors include Michael Niederweis, John J. Mekalanos, Mikhail Pavlenok, Jason T. Huff, Harald Engelhardt, Christian Hoffmann, Alexander Speer, Masato Suzuki, James B. Eaglesham and B. Lowey and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Olga Danilchanka

17 papers receiving 1.8k citations

Hit Papers

align trajectories

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.

Bacterial cGAS-like enzymes synthesize diverse nucleotide signals

2019 249 citations Aaron T. Whiteley, James B. Eaglesham et al. Nature profile →

Peers

Olga Danilchanka

EPIDE

IMMUN

Sarah W. Satola United States

Georgiana E. Purdy United States

Brian Weinrick United States

Michael C. Chao United States

Andrea Marra United States

Joseph A. Mangan United Kingdom

Sharon L. Kendall United Kingdom

Corin Yeats United Kingdom

Abdallah M. Abdallah Netherlands

Claudia Sala Switzerland

Sarah W. Satola United States

Olga Danilchanka

686 ×0.8

973 ×1.2

735 ×1.2

EPIDE

339 ×0.9

IMMUN

552 ×1.6

Citations per year, relative to Olga Danilchanka Olga Danilchanka (= 1×) peers Sarah W. Satola

Countries citing papers authored by Olga Danilchanka

Since Specialization

Citations

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

Fields of papers citing papers by Olga Danilchanka

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Olga Danilchanka

This figure shows the co-authorship network connecting the top 25 collaborators of Olga Danilchanka. A scholar is included among the top collaborators of Olga Danilchanka 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 Olga Danilchanka. Olga Danilchanka is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

Pajuelo, David, Uday Tak, Lei Zhang, et al.. (2021). Toxin secretion and trafficking by Mycobacterium tuberculosis. Nature Communications. 12(1). 6592–6592. 39 indexed citations

Whiteley, Aaron T., James B. Eaglesham, Carina C. de Oliveira Mann, et al.. (2019). Bacterial cGAS-like enzymes synthesize diverse nucleotide signals. Nature. 567(7747). 194–199. 249 indexed citations breakdown →

Tak, Uday, J. Vlach, Acely Garza-Garcı́a, et al.. (2018). The tuberculosis necrotizing toxin is an NAD+ and NADP+ glycohydrolase with distinct enzymatic properties. Journal of Biological Chemistry. 294(9). 3024–3036. 24 indexed citations

Tordello, Elena Del, Olga Danilchanka, Andrew J. McCluskey, & John J. Mekalanos. (2016). Type VI secretion system sheaths as nanoparticles for antigen display. Proceedings of the National Academy of Sciences. 113(11). 3042–3047. 18 indexed citations

Speer, Alexander, Jim Sun, Olga Danilchanka, et al.. (2015). Surface hydrolysis of sphingomyelin by the outer membrane protein Rv0888 supports replication of Mycobacterium tuberculosis in macrophages. Molecular Microbiology. 97(5). 881–897. 52 indexed citations

Danilchanka, Olga, David Pires, Elsa Anes, & Michael Niederweis. (2015). The Mycobacterium tuberculosis Outer Membrane Channel Protein CpnT Confers Susceptibility to Toxic Molecules. Antimicrobial Agents and Chemotherapy. 59(4). 2328–2336. 35 indexed citations

Roux, Damien, Olga Danilchanka, Thomas Guillard, et al.. (2015). Fitness cost of antibiotic susceptibility during bacterial infection. Science Translational Medicine. 7(297). 297ra114–297ra114. 108 indexed citations

Suzuki, Masato, Olga Danilchanka, & John J. Mekalanos. (2014). Vibrio cholerae T3SS Effector VopE Modulates Mitochondrial Dynamics and Innate Immune Signaling by Targeting Miro GTPases. Cell Host & Microbe. 16(5). 581–591. 85 indexed citations

Danilchanka, Olga, Jim Sun, Mikhail Pavlenok, et al.. (2014). An outer membrane channel protein of Mycobacterium tuberculosis with exotoxin activity. Proceedings of the National Academy of Sciences. 111(18). 6750–6755. 99 indexed citations

10.

Skurnik, David, Damien Roux, Vincent Cattoir, et al.. (2013). Enhanced in vivo fitness of carbapenem-resistant oprD mutants of Pseudomonas aeruginosa revealed through high-throughput sequencing. Proceedings of the National Academy of Sciences. 110(51). 20747–20752. 100 indexed citations

11.

Jones, Christopher M., Zhaoyong Xi, Alexander Speer, et al.. (2013). Discovery of a Siderophore Export System Essential for Virulence of Mycobacterium tuberculosis. PLoS Pathogens. 9(1). e1003120–e1003120. 199 indexed citations

12.

Danilchanka, Olga & John J. Mekalanos. (2013). Cyclic Dinucleotides and the Innate Immune Response. Cell. 154(5). 962–970. 190 indexed citations

13.

Niederweis, Michael, Olga Danilchanka, Jason T. Huff, Christian Hoffmann, & Harald Engelhardt. (2010). Mycobacterial outer membranes: in search of proteins. Trends in Microbiology. 18(3). 109–116. 170 indexed citations

14.

Cook, Gregory M., Michael Berney, Susanne Gebhard, et al.. (2009). Physiology of Mycobacteria. Advances in microbial physiology. 55. 81–319. 143 indexed citations

15.

Siroy, Axel, Daniel Harder, Frank Wolschendorf, et al.. (2008). Rv1698 of Mycobacterium tuberculosis Represents a New Class of Channel-forming Outer Membrane Proteins. Journal of Biological Chemistry. 283(26). 17827–17837. 60 indexed citations

16.

Danilchanka, Olga, Mikhail Pavlenok, & Michael Niederweis. (2008). Role of Porins for Uptake of Antibiotics by Mycobacterium smegmatis. Antimicrobial Agents and Chemotherapy. 52(9). 3127–3134. 104 indexed citations

17.

Danilchanka, Olga, et al.. (2008). Identification of a Novel Multidrug Efflux Pump of Mycobacterium tuberculosis. Antimicrobial Agents and Chemotherapy. 52(7). 2503–2511. 113 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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