Jem J. Rowland

4.6k total citations · 1 hit paper
30 papers, 3.2k citations indexed

About

Jem J. Rowland is a scholar working on Molecular Biology, Analytical Chemistry and Biophysics. According to data from OpenAlex, Jem J. Rowland has authored 30 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 14 papers in Analytical Chemistry and 6 papers in Biophysics. Recurrent topics in Jem J. Rowland's work include Spectroscopy and Chemometric Analyses (14 papers), Spectroscopy Techniques in Biomedical and Chemical Research (5 papers) and Microbial Metabolic Engineering and Bioproduction (5 papers). Jem J. Rowland is often cited by papers focused on Spectroscopy and Chemometric Analyses (14 papers), Spectroscopy Techniques in Biomedical and Chemical Research (5 papers) and Microbial Metabolic Engineering and Bioproduction (5 papers). Jem J. Rowland collaborates with scholars based in United Kingdom, France and Netherlands. Jem J. Rowland's co-authors include Douglas B. Kell, David Broadhurst, Royston Goodacre, Stephen G. Oliver, A. R. Jones, Andrew M. Woodward, Hazel M. Davey, Michael K. Winson, Léonie M. Raamsdonk and Andrew Hayes and has published in prestigious journals such as Science, Nature Biotechnology and Analytical Chemistry.

In The Last Decade

Jem J. Rowland

30 papers receiving 3.1k citations

Hit Papers

1 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.

A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations

2001 769 citations Léonie M. Raamsdonk, Bas Teusink et al. Nature Biotechnology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jem J. Rowland United Kingdom	22	1.8k	741	569	443	395	30	3.2k
William S. Rayens United States	19	901 0.5×	1.2k 1.6×	689 1.2×	372 0.8×	230 0.6×	38	3.2k
M. Daszykowski Poland	29	905 0.5×	1.3k 1.7×	507 0.9×	284 0.6×	613 1.6×	79	3.1k
Ewa Szymańska Poland	25	1.1k 0.6×	824 1.1×	480 0.8×	327 0.7×	288 0.7×	101	2.8k
Lionel Blanchet Netherlands	26	975 0.5×	1.0k 1.4×	687 1.2×	402 0.9×	360 0.9×	46	2.6k
Fredrik Lindgren Sweden	20	749 0.4×	1.3k 1.7×	449 0.8×	367 0.8×	315 0.8×	42	2.9k
Курт Вармуза Austria	26	782 0.4×	1.1k 1.5×	1.1k 2.0×	298 0.7×	671 1.7×	112	4.0k
Gavin R. Lloyd United Kingdom	23	715 0.4×	1.1k 1.4×	640 1.1×	873 2.0×	204 0.5×	81	3.1k
Sijmen de Jong Netherlands	21	665 0.4×	2.2k 3.0×	713 1.3×	667 1.5×	345 0.9×	31	4.3k
Cyril Ruckebusch France	29	662 0.4×	1.5k 2.0×	656 1.2×	822 1.9×	336 0.9×	139	3.4k
Alexey L. Pomerantsev Russia	30	823 0.5×	1.9k 2.5×	959 1.7×	571 1.3×	244 0.6×	102	3.4k

Countries citing papers authored by Jem J. Rowland

Since Specialization

Citations

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

Fields of papers citing papers by Jem J. Rowland

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jem J. Rowland. 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 Jem J. Rowland. The network helps show where Jem J. Rowland may publish in the future.

Co-authorship network of co-authors of Jem J. Rowland

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

All Works

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20 of 20 papers shown

Bilsland, Elizabeth, Andrew C. Sparkes, Kevin Williams, et al.. (2013). Yeast-based automated high-throughput screens to identify anti-parasitic lead compounds. Open Biology. 3(2). 120158–120158. 27 indexed citations

Sparkes, Andrew C., Wayne Aubrey, Emma Byrne, et al.. (2010). Towards Robot Scientists for autonomous scientific discovery. PubMed. 2(1). 1–1. 101 indexed citations

Gay, Alan, Howard Thomas, María Roca, et al.. (2008). Nondestructive analysis of senescence in mesophyll cells by spectral resolution of protein synthesis‐dependent pigment metabolism. New Phytologist. 179(3). 663–674. 10 indexed citations

Pritchard, Leighton, et al.. (2005). A general model of error-prone PCR. Journal of Theoretical Biology. 234(4). 497–509. 36 indexed citations

Woodward, Andrew M., Jem J. Rowland, & Douglas B. Kell. (2004). Fast automatic registration of images using the phase of a complex wavelet transform: application to proteome gels. The Analyst. 129(6). 542–542. 18 indexed citations

Winson, Michael K., et al.. (2004). Single-nucleotide polymorphism detection using nanomolar nucleotides and single-molecule fluorescence. Analytical Biochemistry. 327(1). 35–44. 24 indexed citations

Davey, Hazel M., et al.. (2004). Discrimination of Modes of Action of Antifungal Substances by Use of Metabolic Footprinting. Applied and Environmental Microbiology. 70(10). 6157–6165. 64 indexed citations

Davey, Hazel M., David Broadhurst, Jim K. Heald, et al.. (2003). High-throughput classification of yeast mutants for functional genomics using metabolic footprinting. Nature Biotechnology. 21(6). 692–696. 414 indexed citations

Broadhurst, David, Janet A. Taylor, Naheed Kaderbhai, et al.. (2002). Monitoring of complex industrial bioprocesses for metabolite concentrations using modern spectroscopies and machine learning: Application to gibberellic acid production. Biotechnology and Bioengineering. 78(5). 527–538. 64 indexed citations

10.

Vaidyanathan, Seetharaman, Jem J. Rowland, Douglas B. Kell, & Royston Goodacre. (2001). Discrimination of Aerobic Endospore-forming Bacteria via Electrospray-Ionization Mass Spectrometry of Whole Cell Suspensions. Analytical Chemistry. 73(17). 4134–4144. 66 indexed citations

11.

Raamsdonk, Léonie M., Bas Teusink, David Broadhurst, et al.. (2001). A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations. Nature Biotechnology. 19(1). 45–50. 769 indexed citations breakdown →

12.

Woodward, Andrew M., Naheed Kaderbhai, Mustak A. Kaderbhai, et al.. (2001). Histometrics: Improvement of the dynamic range of fluorescently stained proteins resolved in electrophoretic gels using hyperspectral imaging. PROTEOMICS. 1(11). 1351–1358. 6 indexed citations

13.

Gilbert, Richard J., Jem J. Rowland, & Douglas B. Kell. (2000). Genomic computing: explanatory modelling for functional genomics. Genetic and Evolutionary Computation Conference. 551–557. 13 indexed citations

14.

Shaw, Adrian D., Naheed Kaderbhai, A. R. Jones, et al.. (1999). Noninvasive, On-Line Monitoring of the Biotransformation by Yeast of Glucose to Ethanol Using Dispersive Raman Spectroscopy and Chemometrics. Applied Spectroscopy. 53(11). 1419–1428. 62 indexed citations

15.

Taylor, Janet A., Royston Goodacre, William G. Wade, Jem J. Rowland, & Douglas B. Kell. (1998). The deconvolution of pyrolysis mass spectra using genetic programming: application to the identification of someEubacteriumspecies. FEMS Microbiology Letters. 160(2). 237–246. 26 indexed citations

16.

Jones, A. R., Danielle I. Young, Janet A. Taylor, Douglas B. Kell, & Jem J. Rowland. (1998). Quantification of microbial productivity via multi-angle light scattering and supervised learning. Biotechnology and Bioengineering. 59(2). 131–143. 11 indexed citations

17.

Shaw, Adrian D., Giovanna Vlahov, A. R. Jones, et al.. (1997). Discrimination of the variety and region of origin of extra virgin olive oils using 13C NMR and multivariate calibration with variable reduction. Analytica Chimica Acta. 348(1-3). 357–374. 80 indexed citations

18.

Winson, Michael K., Royston Goodacre, Éadaoin M. Timmins, et al.. (1997). Diffuse reflectance absorbance spectroscopy taking in chemometrics (DRASTIC). A hyperspectral FT-IR-based approach to rapid screening for metabolite overproduction. Analytica Chimica Acta. 348(1-3). 273–282. 62 indexed citations

19.

Broadhurst, David, Royston Goodacre, A. R. Jones, Jem J. Rowland, & Douglas B. Kell. (1997). Genetic algorithms as a method for variable selection in multiple linear regression and partial least squares regression, with applications to pyrolysis mass spectrometry. Analytica Chimica Acta. 348(1-3). 71–86. 231 indexed citations

20.

Goodacre, Royston, Éadaoin M. Timmins, Paul J. Rooney, Jem J. Rowland, & Douglas B. Kell. (1996). Rapid identification of Streptococcus and Enterococcus species using diffuse reflectance-absorbance Fourier transform infrared spectroscopy and artificial neural networks. FEMS Microbiology Letters. 140(2-3). 233–239. 143 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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