Ian Dix

759 total citations
12 papers, 647 citations indexed

About

Ian Dix is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine and Genetics. According to data from OpenAlex, Ian Dix has authored 12 papers receiving a total of 647 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 4 papers in Cardiology and Cardiovascular Medicine and 3 papers in Genetics. Recurrent topics in Ian Dix's work include RNA Research and Splicing (9 papers), RNA and protein synthesis mechanisms (7 papers) and Fungal and yeast genetics research (5 papers). Ian Dix is often cited by papers focused on RNA Research and Splicing (9 papers), RNA and protein synthesis mechanisms (7 papers) and Fungal and yeast genetics research (5 papers). Ian Dix collaborates with scholars based in United Kingdom, Israel and France. Ian Dix's co-authors include Jean D. Beggs, CAROLINE S. RUSSELL, Martin Kupiec, Sigal Ben‐Yehuda, Keith N. Leppard, Raymond T. O’Keefe, Andrew J. Newman, Micheline Fromont‐Racine, Jean‐Christophe Rain and Laurence Decourty and has published in prestigious journals such as Journal of Virology, Genetics and Journal of General Virology.

In The Last Decade

Ian Dix

12 papers receiving 634 citations

Peers

Ian Dix

MB

GENET

CB

CCM

ONCOL

Ivo Fierro-Monti United States

Tatjana Naranda United States

Jaswant S. Bhorjee United States

Gary M. Studnicka United States

Olivia Novac Canada

K. Lakomek Germany

Martyn K. Darby United States

Zhihe Kuang Australia

Brigitte Wittmann‐Liebold Germany

Mincheng Zhang United States

Ivo Fierro-Monti United States

Ian Dix

478 ×0.8

MB

34 ×0.5

GENET

20 ×0.5

CB

50 ×1.9

CCM

22 ×0.9

ONCOL

Citations per year, relative to Ian Dix Ian Dix (= 1×) peers Ivo Fierro-Monti

Countries citing papers authored by Ian Dix

Since Specialization

Citations

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

Fields of papers citing papers by Ian Dix

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ian Dix

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

All Works

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12 of 12 papers shown

1.

RUSSELL, CAROLINE S., Sigal Ben‐Yehuda, Ian Dix, Martin Kupiec, & Jean D. Beggs. (2000). Functional analyses of interacting factors involved in both pre-mRNA splicing and cell cycle progression in Saccharomyces cerevisiae. RNA. 6(11). 1565–1572. 48 indexed citations

2.

Fromont‐Racine, Micheline, Andrew E. Mayes, Adeline Simon, et al.. (2000). Genome-Wide Protein Interaction Screens Reveal Functional Networks Involving Sm-Like Proteins. Yeast. 1(2). 95–110. 163 indexed citations

3.

Fromont‐Racine, Micheline, Andrew E. Mayes, Adeline Simon, et al.. (2000). Genome-Wide Protein Interaction Screens Reveal Functional Networks Involving Sm-Like Proteins. Yeast. 1(2). 95–110. 43 indexed citations

4.

Ben‐Yehuda, Sigal, et al.. (2000). Genetic and Physical Interactions Between Factors Involved in Both Cell Cycle Progression and Pre-mRNA Splicing in Saccharomyces cerevisiae. Genetics. 156(4). 1503–1517. 102 indexed citations

5.

Ben‐Yehuda, Sigal, CAROLINE S. RUSSELL, Ian Dix, Jean D. Beggs, & Martin Kupiec. (2000). Extensive Genetic Interactions Between PRP8 and PRP17/CDC40, Two Yeast Genes Involved in Pre-mRNA Splicing and Cell Cycle Progression. Genetics. 154(1). 61–71. 41 indexed citations

6.

Dix, Ian, et al.. (1999). The identification and characterization of a novel splicing protein, Isy1p, of Saccharomyces cerevisiae. RNA. 5(3). 360–368. 39 indexed citations

7.

Dix, Ian, CAROLINE S. RUSSELL, Raymond T. O’Keefe, Andrew J. Newman, & Jean D. Beggs. (1998). Protein–RNA interactions in the U5 snRNP of Saccharomyces cerevisiae. RNA. 4(10). 1239–1250. 32 indexed citations

8.

Dix, Ian, et al.. (1998). Identification and functional analysis of hPRP17, the human homologue of the PRP17/CDC40 yeast gene involved in splicing and cell cycle control. RNA. 4(10). 1304–1312. 41 indexed citations

9.

Dix, Ian, CAROLINE S. RUSSELL, Raymond T. O’Keefe, Andrew J. Newman, & Jean D. Beggs. (1998). Protein-RNA interactions in the U5 snRNP of Saccharomyces cerevisiae. RNA. 4(12). 1674–1686. 71 indexed citations

10.

Dix, Ian & Keith N. Leppard. (1995). Expression of adenovirus type 5 E4 Orf2 protein during lytic infection. Journal of General Virology. 76(4). 1051–1055. 17 indexed citations

11.

Dix, Ian & Keith N. Leppard. (1993). Regulated splicing of adenovirus type 5 E4 transcripts and regulated cytoplasmic accumulation of E4 mRNA. Journal of Virology. 67(6). 3226–3231. 44 indexed citations

12.

Dix, Ian & Keith N. Leppard. (1992). Open reading frames 1 and 2 of adenovirus region E4 are conserved between human serotypes 2 and 5. Journal of General Virology. 73(11). 2975–2976. 6 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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