David T. Mulder

1.2k total citations
16 papers, 482 citations indexed

About

David T. Mulder is a scholar working on Molecular Biology, Food Science and Oncology. According to data from OpenAlex, David T. Mulder has authored 16 papers receiving a total of 482 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 6 papers in Food Science and 5 papers in Oncology. Recurrent topics in David T. Mulder's work include Salmonella and Campylobacter epidemiology (6 papers), Genomics and Phylogenetic Studies (3 papers) and Bacterial Genetics and Biotechnology (3 papers). David T. Mulder is often cited by papers focused on Salmonella and Campylobacter epidemiology (6 papers), Genomics and Phylogenetic Studies (3 papers) and Bacterial Genetics and Biotechnology (3 papers). David T. Mulder collaborates with scholars based in Canada, United States and Australia. David T. Mulder's co-authors include Brian K. Coombes, Sarah A. Reid‐Yu, Ana Victoria C. Pilar, Marie A. Elliot, Chan Gao, Fransiskus Hindra, Charles Yin, Ana M. Tomljenovic-Berube, Matthew D. Whiteside and Fiona S. L. Brinkman and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Molecular Microbiology and Infection and Immunity.

In The Last Decade

David T. Mulder

16 papers receiving 477 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David T. Mulder Canada 10 187 183 164 85 84 16 482
Nadège Bossuet‐Greif France 10 127 0.7× 89 0.5× 367 2.2× 38 0.4× 102 1.2× 13 507
Emilee E. Shine United States 9 100 0.5× 66 0.4× 452 2.8× 103 1.2× 139 1.7× 12 593
Shu-Lin Liu China 15 89 0.5× 126 0.7× 426 2.6× 82 1.0× 65 0.8× 27 707
Tiphanie Faïs France 10 105 0.6× 78 0.4× 331 2.0× 26 0.3× 78 0.9× 11 477
Sophie Tronnet France 9 90 0.5× 81 0.4× 260 1.6× 28 0.3× 66 0.8× 11 358
Mara Giangrossi Italy 14 215 1.1× 67 0.4× 510 3.1× 169 2.0× 372 4.4× 21 778
Guohui Zhao China 14 73 0.4× 31 0.2× 383 2.3× 84 1.0× 95 1.1× 24 603
Christophe Garcie France 7 92 0.5× 61 0.3× 228 1.4× 18 0.2× 71 0.8× 7 314
Camille V. Chagneau France 10 87 0.5× 67 0.4× 198 1.2× 28 0.3× 40 0.5× 17 310
Samir El Qaidi United States 10 109 0.6× 68 0.4× 178 1.1× 69 0.8× 81 1.0× 20 318

Countries citing papers authored by David T. Mulder

Since Specialization
Citations

This map shows the geographic impact of David T. Mulder'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 David T. Mulder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David T. Mulder more than expected).

Fields of papers citing papers by David T. Mulder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David T. Mulder. 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 David T. Mulder. The network helps show where David T. Mulder may publish in the future.

Co-authorship network of co-authors of David T. Mulder

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

All Works

16 of 16 papers shown
1.
Cheng, Xuanjin, Laura Williamson, Martin Krzywinski, et al.. (2024). Enhancing clinical genomic accuracy with panelGC: a novel metric and tool for quantifying and monitoring GC biases in hybridization capture panel sequencing. Briefings in Bioinformatics. 25(5). 1 indexed citations
2.
McGuire, Anna, Melissa K. McConechy, Barbara Melosky, et al.. (2022). The Clinically Actionable Molecular Profile of Early versus Late-Stage Non-Small Cell Lung Cancer, an Individual Age and Sex Propensity-Matched Pair Analysis. Current Oncology. 29(4). 2630–2643. 7 indexed citations
3.
Chow, Signy, Olena Kis, David T. Mulder, et al.. (2022). Myeloma immunoglobulin rearrangement and translocation detection through targeted capture sequencing. Life Science Alliance. 6(1). e202201543–e202201543. 6 indexed citations
4.
Paul, Michael St., Samuel D. Saibil, Scott Lien, et al.. (2020). IL6 Induces an IL22+ CD8+ T-cell Subset with Potent Antitumor Function. Cancer Immunology Research. 8(3). 321–333. 28 indexed citations
5.
Mulder, David T., Etienne Mahé, Mark Dowar, et al.. (2018). CapTCR-seq: hybrid capture for T-cell receptor repertoire profiling. Blood Advances. 2(23). 3506–3514. 10 indexed citations
6.
Ilyas, Bushra, David T. Mulder, Dustin J. Little, et al.. (2018). Regulatory Evolution Drives Evasion of Host Inflammasomes by Salmonella Typhimurium. Cell Reports. 25(4). 825–832.e5. 22 indexed citations
7.
Kis, Olena, Signy Chow, Rayan Kaedbey, et al.. (2017). Targeted Sequencing of Circulating Cell-free DNA in Multiple Myeloma Allows Analysis of Somatic Mutations, Copy Number Aberrations, and Translocations. Clinical Lymphoma Myeloma & Leukemia. 17(1). e93–e94. 1 indexed citations
8.
Mulder, David T., Joseph B. McPhee, Sarah A. Reid‐Yu, et al.. (2014). Multiple histidines in the periplasmic domain of the Salmonella enterica sensor kinase SsrA enhance signaling in response to extracellular acidification. Molecular Microbiology. 95(4). 678–691. 23 indexed citations
9.
Pilar, Ana Victoria C., et al.. (2013). Active modification of host inflammation bySalmonella. Gut Microbes. 4(2). 140–145. 9 indexed citations
10.
Mulder, David T., et al.. (2013). The SseC translocon component in Salmonella enterica serovar Typhimurium is chaperoned by SscA. BMC Microbiology. 13(1). 221–221. 6 indexed citations
11.
Mulder, David T., et al.. (2012). Type VI Secretion System-Associated Gene Clusters Contribute to Pathogenesis of Salmonella enterica Serovar Typhimurium. Infection and Immunity. 80(6). 1996–2007. 80 indexed citations
12.
Pilar, Ana Victoria C., et al.. (2012). GogB Is an Anti-Inflammatory Effector that Limits Tissue Damage during Salmonella Infection through Interaction with Human FBXO22 and Skp1. PLoS Pathogens. 8(6). e1002773–e1002773. 76 indexed citations
13.
Gao, Chan, Fransiskus Hindra, David T. Mulder, Charles Yin, & Marie A. Elliot. (2012). Crp Is a Global Regulator of Antibiotic Production in Streptomyces. mBio. 3(6). 91 indexed citations
14.
Tomljenovic-Berube, Ana M., David T. Mulder, Matthew D. Whiteside, Fiona S. L. Brinkman, & Brian K. Coombes. (2010). Identification of the Regulatory Logic Controlling Salmonella Pathoadaptation by the SsrA-SsrB Two-Component System. PLoS Genetics. 6(3). e1000875–e1000875. 63 indexed citations
15.
Osborne, Suzanne E., Don Walthers, Ana M. Tomljenovic-Berube, et al.. (2009). Pathogenic adaptation of intracellular bacteria by rewiring a cis -regulatory input function. Proceedings of the National Academy of Sciences. 106(10). 3982–3987. 50 indexed citations
16.
Obertop, H., Jan van Lanschot, M. van Blankenstein, et al.. (1993). Neo-adjuvant chemotherapy in operable esophageal squamous cell cancer; an interim report of a randomized controlled trial. European Journal of Cancer. 29. S104–S104. 9 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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