Ros Whittall

3.1k total citations · 1 hit paper
28 papers, 1.5k citations indexed

About

Ros Whittall is a scholar working on Surgery, Cancer Research and Pathology and Forensic Medicine. According to data from OpenAlex, Ros Whittall has authored 28 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Surgery, 7 papers in Cancer Research and 6 papers in Pathology and Forensic Medicine. Recurrent topics in Ros Whittall's work include Lipoproteins and Cardiovascular Health (24 papers), Cancer, Lipids, and Metabolism (6 papers) and Genetic factors in colorectal cancer (6 papers). Ros Whittall is often cited by papers focused on Lipoproteins and Cardiovascular Health (24 papers), Cancer, Lipids, and Metabolism (6 papers) and Genetic factors in colorectal cancer (6 papers). Ros Whittall collaborates with scholars based in United Kingdom, Brazil and Türkiye. Ros Whittall's co-authors include Steve E. Humphries, Marta Futema, H. A. W. Neil, Jackie A. Cooper, Nicholas Lench, S. E. A. Leigh, Fredrik Karpe, KaWah Li, Olivier Descamps and Alison Taylor and has published in prestigious journals such as The Lancet, American Journal of Clinical Nutrition and The American Journal of Cardiology.

In The Last Decade

Ros Whittall

28 papers receiving 1.5k citations

Hit Papers

Use of low-density lipoprotein cholesterol gene score to ... 2013 2026 2017 2021 2013 100 200 300 400

Peers

Ros Whittall
Clare Neuwirth United Kingdom
Barbara Sjouke Netherlands
Roeland Huijgen Netherlands
Marta Futema United Kingdom
Sigrid W. Fouchier Netherlands
Patrick M. Moriarty United States
Randall B. Graham United States
Ros Whittall
Citations per year, relative to Ros Whittall Ros Whittall (= 1×) peers Isabelle L. Ruel

Countries citing papers authored by Ros Whittall

Since Specialization
Citations

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

Fields of papers citing papers by Ros Whittall

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ros Whittall

This figure shows the co-authorship network connecting the top 25 collaborators of Ros Whittall. A scholar is included among the top collaborators of Ros Whittall 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 Ros Whittall. Ros Whittall 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.
Whittall, Ros, et al.. (2019). Genetics of LDLR Gene in Pakistani Hypercholesterolemia Families. 8(4). 143–146. 1 indexed citations
2.
Whittall, Ros, et al.. (2017). Analysis of mutations causing familial hypercholesterolaemia in black South African patients of different ancestr. South African Medical Journal. 107(2). 145–145. 3 indexed citations
3.
Durst, Ronen, Shoshi Shpitzen, Daniel Schurr, et al.. (2016). Molecular genetics of familial hypercholesterolemia in Israel–revisited. Atherosclerosis. 257. 55–63. 17 indexed citations
4.
Sharifi, Mahtab, Małgorzata Waluś‐Miarka, Barbara Idzior−Waluś, et al.. (2015). The genetic spectrum of familial hypercholesterolemia in south-eastern Poland. Metabolism. 65(3). 48–53. 26 indexed citations
5.
Futema, Marta, Vincent Plagnol, KaWah Li, et al.. (2014). Whole exome sequencing of familial hypercholesterolaemia patients negative for LDLR/APOB/PCSK9 mutations. Journal of Medical Genetics. 51(8). 537–544. 89 indexed citations
6.
Talmud, Philippa J., Sonia Shah, Ros Whittall, et al.. (2013). Use of low-density lipoprotein cholesterol gene score to distinguish patients with polygenic and monogenic familial hypercholesterolaemia: a case-control study. The Lancet. 381(9874). 1293–1301. 411 indexed citations breakdown →
7.
Ahmed, Waqas, Ros Whittall, Moeen Riaz, et al.. (2013). The genetic spectrum of familial hypercholesterolemia in Pakistan. Clinica Chimica Acta. 421. 219–225. 15 indexed citations
8.
Futema, Marta, Ros Whittall, Jackie A. Cooper, et al.. (2013). Analysis of the frequency and spectrum of mutations recognised to cause familial hypercholesterolaemia in routine clinical practice in a UK specialist hospital lipid clinic. Atherosclerosis. 229(1). 161–168. 77 indexed citations
9.
Whittall, Ros, Mariléia Scartezini, KaWah Li, et al.. (2009). Development of a high-resolution melting method for mutation detection in familial hypercholesterolaemia patients. Annals of Clinical Biochemistry International Journal of Laboratory Medicine. 47(1). 44–55. 37 indexed citations
10.
Taylor, Alison, Kavisha Patel, Ros Whittall, et al.. (2009). Mutation detection rate and spectrum in familial hypercholesterolaemia patients in the UK pilot cascade project. Clinical Genetics. 77(6). 572–580. 148 indexed citations
11.
12.
Taylor, Alison, et al.. (2007). Multiplex ARMS analysis to detect 13 common mutations in familial hypercholesterolaemia. Clinical Genetics. 71(6). 561–568. 25 indexed citations
13.
Scartezini, Mariléia, Christina Hubbart, Ros Whittall, et al.. (2007). The PCSK9 gene R46L variant is associated with lower plasma lipid levels and cardiovascular risk in healthy U.K. men. Clinical Science. 113(11). 435–441. 77 indexed citations
14.
Whittall, Ros, et al.. (2006). The A370T Variant (StuI Polymorphism) in the LDL Receptor Gene is not Associated with Plasma Lipid Levels or Cardiovascular Risk in UK Men. Annals of Human Genetics. 70(6). 697–704. 6 indexed citations
15.
Sozen, Mert, Ros Whittall, Cihan Öner, et al.. (2005). The molecular basis of familial hypercholesterolaemia in Turkish patients. Atherosclerosis. 180(1). 63–71. 34 indexed citations
16.
Theobald, Hannah, Phil Chowienczyk, Ros Whittall, Steve E. Humphries, & T. A. B. Sanders. (2004). LDL cholesterol–raising effect of low-dose docosahexaenoic acid in middle-aged men and women. American Journal of Clinical Nutrition. 79(4). 558–563. 76 indexed citations
17.
Elrayess, Mohamed A., Karen E. Webb, Geoff Bellingan, et al.. (2004). R643G polymorphism in PECAM-1 influences transendothelial migration of monocytes and is associated with progression of CHD and CHD events. Atherosclerosis. 177(1). 127–135. 34 indexed citations
18.
Stephens, Jeffrey W., Mert Sozen, Ros Whittall, et al.. (2004). Three Novel Mutations in the Apolipoprotein E Gene in a Sample of Individuals with Type 2 Diabetes Mellitus. Clinical Chemistry. 51(1). 119–124. 6 indexed citations
19.
Whittall, Ros, et al.. (2002). The intron 14 2140+5G>A variant in the low density lipoprotein receptor gene has no effect on plasma cholesterol levels: Table 1. Journal of Medical Genetics. 39(9). e57–e57. 8 indexed citations
20.
Wilson, Darren, Lema Haddad, Karen E. Heath, et al.. (1998). A World Wide Web Site for Low-Density Lipoprotein Receptor Gene Mutations in Familial Hypercholesterolemia: Sequence-Based, Tabular, and Direct Submission Data Handling. The American Journal of Cardiology. 81(12). 1509–1511. 41 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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