Paul Scherer

595 total citations
8 papers, 237 citations indexed

About

Paul Scherer is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Cell Biology. According to data from OpenAlex, Paul Scherer has authored 8 papers receiving a total of 237 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 3 papers in Cellular and Molecular Neuroscience and 2 papers in Cell Biology. Recurrent topics in Paul Scherer's work include Neuropeptides and Animal Physiology (3 papers), Receptor Mechanisms and Signaling (2 papers) and Bioinformatics and Genomic Networks (2 papers). Paul Scherer is often cited by papers focused on Neuropeptides and Animal Physiology (3 papers), Receptor Mechanisms and Signaling (2 papers) and Bioinformatics and Genomic Networks (2 papers). Paul Scherer collaborates with scholars based in United States, United Kingdom and China. Paul Scherer's co-authors include Píetro Lió, Nikola Simidjievski, Mateja Jamnik, Cristian Bodnar, Solomon H. Snyder, Gregory B. Willer, Yuanquan Song, Jessica A. Panzer, Ronald G. Gregg and Rita J. Balice‐Gordon and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Bioinformatics and PLoS ONE.

In The Last Decade

Paul Scherer

8 papers receiving 236 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Paul Scherer United States	7	167	34	30	29	28	8	237
Manami Suzuki Japan	12	105 0.6×	23 0.7×	6 0.2×	10 0.3×	41 1.5×	40	420
Aarti Singh United Kingdom	8	225 1.3×	43 1.3×	13 0.4×	9 0.3×	13 0.5×	12	341
Saadia Ahmed United States	4	318 1.9×	38 1.1×	21 0.7×	3 0.1×	102 3.6×	7	476
William P. Bone United States	10	291 1.7×	33 1.0×	16 0.5×	21 0.7×	18 0.6×	13	484
Federico López United Kingdom	4	121 0.7×	17 0.5×	14 0.5×	8 0.3×	6 0.2×	7	195
Beatriz Puisac Spain	16	431 2.6×	79 2.3×	15 0.5×	8 0.3×	15 0.5×	45	568
Uday S. Evani United States	9	362 2.2×	53 1.6×	51 1.7×	19 0.7×	13 0.5×	10	493
Ruizhi Wang China	9	116 0.7×	74 2.2×	23 0.8×	25 0.9×	21 0.8×	23	333
Cavatina K. Truong United States	10	531 3.2×	23 0.7×	20 0.7×	8 0.3×	39 1.4×	10	659
Robert B. Bentham United Kingdom	7	245 1.5×	26 0.8×	28 0.9×	3 0.1×	29 1.0×	10	286

Countries citing papers authored by Paul Scherer

Since Specialization

Citations

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

Fields of papers citing papers by Paul Scherer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Paul Scherer

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

All Works

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8 of 8 papers shown

1.

Scherer, Paul, Maja Trębacz, Nikola Simidjievski, et al.. (2021). Unsupervised construction of computational graphs for gene expression data with explicit structural inductive biases. Bioinformatics. 38(5). 1320–1327. 2 indexed citations

2.

Simidjievski, Nikola, et al.. (2019). Variational Autoencoders for Cancer Data Integration: Design Principles and Computational Practice. Frontiers in Genetics. 10. 1205–1205. 82 indexed citations

3.

Vasavda, Chirag, et al.. (2017). Measuring G-protein-coupled Receptor Signaling via Radio-labeled GTP Binding. Journal of Visualized Experiments. 9 indexed citations

4.

Scherer, Paul, Neil M. Neumann, Chirag Vasavda, et al.. (2017). TRPV1 is a physiological regulator of μ-opioid receptors. Proceedings of the National Academy of Sciences. 114(51). 13561–13566. 30 indexed citations

5.

Vasavda, Chirag, et al.. (2017). Measuring G-protein-coupled Receptor Signaling via Radio-labeled GTP Binding. Journal of Visualized Experiments. 6 indexed citations

6.

Scherer, Paul, Yan Ding, Zhiqing Liu, et al.. (2016). Inositol hexakisphosphate (IP6) generated by IP5K mediates cullin-COP9 signalosome interactions and CRL function. Proceedings of the National Academy of Sciences. 113(13). 3503–3508. 30 indexed citations

7.

Song, Yuanquan, Jason R. Willer, Paul Scherer, et al.. (2010). Neural and Synaptic Defects in slytherin, a Zebrafish Model for Human Congenital Disorders of Glycosylation. PLoS ONE. 5(10). e13743–e13743. 28 indexed citations

8.

Song, Yuanquan, Mary Selak, Corey T. Watson, et al.. (2009). Mechanisms Underlying Metabolic and Neural Defects in Zebrafish and Human Multiple Acyl-CoA Dehydrogenase Deficiency (MADD). PLoS ONE. 4(12). e8329–e8329. 50 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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