Frank Wessely

687 total citations
10 papers, 322 citations indexed

About

Frank Wessely is a scholar working on Molecular Biology, Genetics and Physiology. According to data from OpenAlex, Frank Wessely has authored 10 papers receiving a total of 322 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 5 papers in Genetics and 2 papers in Physiology. Recurrent topics in Frank Wessely's work include Epigenetics and DNA Methylation (3 papers), Microbial Metabolic Engineering and Bioproduction (3 papers) and Genetic Syndromes and Imprinting (2 papers). Frank Wessely is often cited by papers focused on Epigenetics and DNA Methylation (3 papers), Microbial Metabolic Engineering and Bioproduction (3 papers) and Genetic Syndromes and Imprinting (2 papers). Frank Wessely collaborates with scholars based in United Kingdom, Germany and Belgium. Frank Wessely's co-authors include Richard D. Emes, Stefan Schuster, Pu Li, M. Bartl, Christoph Kaleta, Reinhard Guthke, Richard N. Clayton, Kiren Yacqub‐Usman, William E. Farrell and Jane Vowles and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Analytical Chemistry.

In The Last Decade

Frank Wessely

10 papers receiving 320 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Frank Wessely United Kingdom	9	217	52	34	33	31	10	322
André Saraiva Leão Marcelo Antunes Brazil	9	140 0.6×	27 0.5×	21 0.6×	30 0.9×	8 0.3×	19	277
Angelien Heister Netherlands	10	227 1.0×	69 1.3×	15 0.4×	42 1.3×	15 0.5×	10	437
Guilian Fu China	9	263 1.2×	106 2.0×	19 0.6×	26 0.8×	16 0.5×	16	350
Giovanni A. Carosso United States	9	338 1.6×	92 1.8×	14 0.4×	55 1.7×	40 1.3×	11	470
Isabel Mayo Spain	12	213 1.0×	37 0.7×	10 0.3×	83 2.5×	36 1.2×	14	482
Martin A. Samuels United States	7	207 1.0×	56 1.1×	18 0.5×	27 0.8×	13 0.4×	9	307
Daniel R. Carvalho Brazil	11	164 0.8×	84 1.6×	8 0.2×	57 1.7×	30 1.0×	31	343
Masataka Kunii Japan	11	214 1.0×	91 1.8×	9 0.3×	36 1.1×	43 1.4×	16	380
Z Kostrouch Czechia	10	282 1.3×	57 1.1×	59 1.7×	42 1.3×	36 1.2×	17	427
R. A. Lazzarini United States	9	328 1.5×	53 1.0×	18 0.5×	136 4.1×	29 0.9×	11	514

Countries citing papers authored by Frank Wessely

Since Specialization

Citations

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

Fields of papers citing papers by Frank Wessely

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Frank Wessely

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

All Works

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10 of 10 papers shown

Booth, Heather, Frank Wessely, Natalie Connor‐Robson, et al.. (2019). RNA sequencing reveals MMP2 and TGFB1 downregulation in LRRK2 G2019S Parkinson's iPSC-derived astrocytes. Neurobiology of Disease. 129. 56–66. 54 indexed citations

Baud, Anna, Frank Wessely, Francesca Mazzacuva, et al.. (2017). Multiplex High-Throughput Targeted Proteomic Assay To Identify Induced Pluripotent Stem Cells. Analytical Chemistry. 89(4). 2440–2448. 11 indexed citations

Wessely, Frank, et al.. (2015). Optimal regulatory strategies for metabolic pathways in Escherichia coli depending on protein costs. Common Library Network (Der Gemeinsame Bibliotheksverbund). 2 indexed citations

Emes, Richard D., Frank Wessely, Paul R. Kemp, et al.. (2013). A Comparative Approach to Understanding Tissue-Specific Expression of Uncoupling Protein 1 Expression in Adipose Tissue. Frontiers in Genetics. 3. 304–304. 9 indexed citations

Wessely, Frank & Richard D. Emes. (2012). Identification of DNA methylation biomarkers from Infinium arrays. Frontiers in Genetics. 3. 161–161. 36 indexed citations

Fainberg, Hernan P., Jaume Bacardit, Dongfang Li, et al.. (2012). Reduced Neonatal Mortality in Meishan Piglets: A Role for Hepatic Fatty Acids?. PLoS ONE. 7(11). e49101–e49101. 14 indexed citations

Emes, Richard D., et al.. (2012). Quantitative, genome-wide analysis of the DNA methylome in sporadic pituitary adenomas. Endocrine Related Cancer. 19(6). 805–816. 55 indexed citations

Clifford, Harry, et al.. (2011). Comparison of Clustering Methods for Investigation of Genome-Wide Methylation Array Data. SHILAP Revista de lepidopterología. 2. 88–88. 23 indexed citations

Wessely, Frank, M. Bartl, Reinhard Guthke, et al.. (2011). Optimal regulatory strategies for metabolic pathways in Escherichia coli depending on protein costs. Molecular Systems Biology. 7(1). 515–515. 90 indexed citations

10.

Schuster, Stefan, Jan‐Ulrich Kreft, Naama Brenner, et al.. (2010). Cooperation and cheating in microbial exoenzyme production – Theoretical analysis for biotechnological applications. Biotechnology Journal. 5(7). 751–758. 28 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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