Michael Vidne

463 total citations
12 papers, 272 citations indexed

About

Michael Vidne is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Cognitive Neuroscience. According to data from OpenAlex, Michael Vidne has authored 12 papers receiving a total of 272 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Pulmonary and Respiratory Medicine and 3 papers in Cognitive Neuroscience. Recurrent topics in Michael Vidne's work include Neural dynamics and brain function (3 papers), Computational Drug Discovery Methods (3 papers) and Lung Cancer Treatments and Mutations (3 papers). Michael Vidne is often cited by papers focused on Neural dynamics and brain function (3 papers), Computational Drug Discovery Methods (3 papers) and Lung Cancer Treatments and Mutations (3 papers). Michael Vidne collaborates with scholars based in United States, Netherlands and Poland. Michael Vidne's co-authors include Liam Paninski, Yashar Ahmadian, Kamiar Rahnama Rad, Joshua T Vogelstein, Shinsuke Koyama, Wei Wu, A. M. Litke, Jayant Kulkarni, Jonathan W. Pillow and Jonathon Shlens and has published in prestigious journals such as Journal of Clinical Oncology, Cancer Research and Scientific Reports.

In The Last Decade

Michael Vidne

12 papers receiving 268 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael Vidne United States 6 207 103 58 50 46 12 272
Pedro J. Gonçalves Germany 9 120 0.6× 63 0.6× 44 0.8× 107 2.1× 21 0.5× 15 290
Robert Clewley United States 10 334 1.6× 121 1.2× 26 0.4× 113 2.3× 148 3.2× 14 533
Vito Paolo Pastore Italy 11 165 0.8× 159 1.5× 67 1.2× 58 1.2× 14 0.3× 34 387
Jeremy Lewi United States 4 226 1.1× 110 1.1× 60 1.0× 35 0.7× 30 0.7× 6 281
Arno Onken United Kingdom 9 220 1.1× 95 0.9× 41 0.7× 84 1.7× 20 0.4× 19 317
M. P. Young United Kingdom 8 323 1.6× 81 0.8× 19 0.3× 62 1.2× 34 0.7× 11 439
Felipe Gerhard Switzerland 6 225 1.1× 132 1.3× 28 0.5× 34 0.7× 43 0.9× 9 283
Ryan C. Kelly United States 8 295 1.4× 185 1.8× 29 0.5× 49 1.0× 26 0.6× 13 385
Shannon R. Campbell United States 7 207 1.0× 55 0.5× 60 1.0× 19 0.4× 135 2.9× 18 327
Evan Archer United States 7 75 0.4× 29 0.3× 53 0.9× 23 0.5× 31 0.7× 9 161

Countries citing papers authored by Michael Vidne

Since Specialization
Citations

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

Fields of papers citing papers by Michael Vidne

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Vidne

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

All Works

12 of 12 papers shown
1.
Kato, Shumei, Robert Porter, Ryosuke Okamura, et al.. (2021). Functional measurement of mitogen-activated protein kinase pathway activation predicts responsiveness of RAS-mutant cancers to MEK inhibitors. European Journal of Cancer. 149. 184–192. 4 indexed citations
2.
Jankú, Filip, Eric J. Sherman, Rona Yaeger, et al.. (2021). Abstract CT212: Expanded phase 1/2a study of PLX8394, a novel next generation BRAF inhibitor in patients with advanced, unresectable solid tumors with alterations in BRAF. Cancer Research. 81(13_Supplement). CT212–CT212. 1 indexed citations
3.
Zimmerman, Lior, et al.. (2020). A Novel System for Functional Determination of Variants of Uncertain Significance using Deep Convolutional Neural Networks. Scientific Reports. 10(1). 4192–4192. 5 indexed citations
4.
5.
Kamal, Maud, Gabi Tarcic, Sylvain Dureau, et al.. (2018). Revisited analysis of a SHIVA01 trial cohort using functional mutational analyses successfully predicted treatment outcome. Molecular Oncology. 12(5). 594–601. 1 indexed citations
6.
Loree, Jonathan M., Vijaykumar Holla, Michael J. Overman, et al.. (2017). Not all RAS mutations created equal: Functional and clinical characterization of 80 different KRAS and NRAS mutations.. Journal of Clinical Oncology. 35(15_suppl). 3589–3589. 8 indexed citations
7.
Miron, Benjamin, Nir Peled, Gabi Tarcic, et al.. (2016). Functional profiling of oncogenic mutations in lung cancer patients (NCT02274025) - interim results. Annals of Oncology. 27. vi412–vi412. 1 indexed citations
8.
Tarcic, Gabi, Mohamed Kamal, Oded Edelheit, et al.. (2016). Functional mutational analysis to assess the oncogenic activity of variant of uncertain significance (VUS) detected in patients included in the SHIVA trial. European Journal of Cancer. 69. S6–S7. 2 indexed citations
9.
Paninski, Liam, Kamiar Rahnama Rad, & Michael Vidne. (2012). Robust particle filters via sequential pairwise reparameterized Gibbs sampling. 299. 1–6. 1 indexed citations
10.
Vidne, Michael, Yashar Ahmadian, Jonathon Shlens, et al.. (2011). Modeling the impact of common noise inputs on the network activity of retinal ganglion cells. Journal of Computational Neuroscience. 33(1). 97–121. 72 indexed citations
11.
Paninski, Liam, et al.. (2011). Inferring synaptic inputs given a noisy voltage trace via sequential Monte Carlo methods. Journal of Computational Neuroscience. 33(1). 1–19. 33 indexed citations
12.
Paninski, Liam, Yashar Ahmadian, Shinsuke Koyama, et al.. (2009). A new look at state-space models for neural data. Journal of Computational Neuroscience. 29(1-2). 107–126. 131 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Pedro J. Gonçalves Breakdown of academic impact, for papers by Robert Clewley Breakdown of academic impact, for papers by Vito Paolo Pastore Breakdown of academic impact, for papers by Jeremy Lewi Breakdown of academic impact, for papers by Arno Onken Breakdown of academic impact, for papers by M. P. Young Breakdown of academic impact, for papers by Felipe Gerhard Breakdown of academic impact, for papers by Ryan C. Kelly Breakdown of academic impact, for papers by Shannon R. Campbell Breakdown of academic impact, for papers by Evan Archer
Rankless by CCL
2026