Joshua Lynch

1.7k total citations
21 papers, 822 citations indexed

About

Joshua Lynch is a scholar working on Molecular Biology, Materials Chemistry and Cognitive Neuroscience. According to data from OpenAlex, Joshua Lynch has authored 21 papers receiving a total of 822 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 5 papers in Materials Chemistry and 4 papers in Cognitive Neuroscience. Recurrent topics in Joshua Lynch's work include Machine Learning in Materials Science (3 papers), Electron and X-Ray Spectroscopy Techniques (3 papers) and Functional Brain Connectivity Studies (3 papers). Joshua Lynch is often cited by papers focused on Machine Learning in Materials Science (3 papers), Electron and X-Ray Spectroscopy Techniques (3 papers) and Functional Brain Connectivity Studies (3 papers). Joshua Lynch collaborates with scholars based in United States, United Kingdom and New Zealand. Joshua Lynch's co-authors include Ran Blekhman, Dan Knights, Timothy K. Starr, Michael B. Burns, Tariq Ezaz, Tony Gamble, David Zarkower, Daniel P. Scantlebury, Molly Przeworski and Alain Froment and has published in prestigious journals such as Geochimica et Cosmochimica Acta, Molecular Biology and Evolution and PLoS Genetics.

In The Last Decade

Joshua Lynch

20 papers receiving 813 citations

Peers

Joshua Lynch

GENET

EEBS

Shuyun Li China

Benjamin Evans United States

Katarzyna B. Hooks France

Paul Williams United States

Panayiota Kotsakiozi United States

André Luis Costa‐da‐Silva Brazil

Katelyn Michelini United States

Sarah Marsh United States

Sway P. Chen United States

Yanming Zhang China

Shuyun Li China

Joshua Lynch

275 ×0.7

180 ×0.8

GENET

87 ×0.7

60 ×0.6

140 ×1.6

EEBS

Citations per year, relative to Joshua Lynch Joshua Lynch (= 1×) peers Shuyun Li

Countries citing papers authored by Joshua Lynch

Since Specialization

Citations

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

Fields of papers citing papers by Joshua Lynch

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joshua Lynch

This figure shows the co-authorship network connecting the top 25 collaborators of Joshua Lynch. A scholar is included among the top collaborators of Joshua Lynch 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 Joshua Lynch. Joshua Lynch 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

Kwon, Gihan, Kim Kisslinger, Sooyeon Hwang, et al.. (2023). Multielectrode electrochemical cell for in situ structural characterization of amorphous thin-film catalysts using high-energy X-ray scattering. Journal of Applied Crystallography. 56(5). 1392–1402. 1 indexed citations

Maffettone, Phillip M., Daniel Allan, Stuart I. Campbell, et al.. (2023). Self-driving multimodal studies at user facilities. Acta Crystallographica Section A Foundations and Advances. 79(a1). a325–a325. 1 indexed citations

Cohen, Stephanie E. & Joshua Lynch. (2023). COVID-19-Induced Phlegmasia Cerulea Dolens. Cureus. 15(1). e33644–e33644. 1 indexed citations

Zhao, Chonghang, Marcus M. Noack, Jiun-Han Chen, et al.. (2022). Machine-learning for designing nanoarchitectured materials by dealloying. Communications Materials. 3(1). 9 indexed citations

Morris, T. W., et al.. (2022). On-the-fly optimization of synchrotron beamlines using machine learning. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 22–22. 1 indexed citations

Nash, Boaz, Maksim Rakitin, Joshua Lynch, et al.. (2022). Combining diagnostics, modeling, and control systems for automated alignment of the TES beamline. Journal of Physics Conference Series. 2380(1). 12103–12103. 6 indexed citations

Maffettone, Phillip M., et al.. (2021). Gaming the beamlines—employing reinforcement learning to maximize scientific outcomes at large-scale user facilities. Machine Learning Science and Technology. 2(2). 25025–25025. 10 indexed citations

Olds, Daniel, Daniel Allan, Thomas A Caswell, et al.. (2021). Optimizing High- Throughput Capabilities by Leveraging Reinforcement Learning Methods with the Bluesky Suite. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 585. 36–42. 2 indexed citations

Youens‐Clark, Ken, Alise J. Ponsero, Elisha M. Wood‐Charlson, et al.. (2019). iMicrobe: Tools and data-driven discovery platform for the microbiome sciences. GigaScience. 8(7). 18 indexed citations

10.

Lynch, Joshua, Karen Tang, Sambhawa Priya, et al.. (2017). HOMINID: a framework for identifying associations between host genetic variation and microbiome composition. GigaScience. 6(12). 1–7. 18 indexed citations

11.

Nicholas, Sarah, Melinda L. Erickson, Laurel G. Woodruff, et al.. (2017). Solid-phase arsenic speciation in aquifer sediments: A micro-X-ray absorption spectroscopy approach for quantifying trace-level speciation. Geochimica et Cosmochimica Acta. 211. 228–255. 30 indexed citations

12.

Morton, Elise R., Joshua Lynch, Alain Froment, et al.. (2015). Variation in Rural African Gut Microbiota Is Strongly Correlated with Colonization by Entamoeba and Subsistence. PLoS Genetics. 11(11). e1005658–e1005658. 168 indexed citations

13.

Gamble, Tony, et al.. (2015). Restriction Site-Associated DNA Sequencing (RAD-seq) Reveals an Extraordinary Number of Transitions among Gecko Sex-Determining Systems. Molecular Biology and Evolution. 32(5). 1296–1309. 196 indexed citations

14.

Burns, Michael B., Joshua Lynch, Timothy K. Starr, Dan Knights, & Ran Blekhman. (2015). Virulence genes are a signature of the microbiome in the colorectal tumor microenvironment. Genome Medicine. 7(1). 55–55. 182 indexed citations

15.

Lynch, Joshua, et al.. (2011). Expression of key retinoic acid modulating genes suggests active regulation during development and regeneration of the amphibian limb. Developmental Dynamics. 240(5). 1259–1270. 31 indexed citations

16.

Christova, Peka, Scott M. Lewis, Trenton A. Jerde, Joshua Lynch, & Apostolos P. Georgopoulos. (2011). True associations between resting fMRI time series based on innovations. Journal of Neural Engineering. 8(4). 46025–46025. 36 indexed citations

17.

Georgopoulos, Apostolos P., Heng‐Ru May Tan, Scott M. Lewis, et al.. (2010). The synchronous neural interactions test as a functional neuromarker for post-traumatic stress disorder (PTSD): a robust classification method based on the bootstrap. Journal of Neural Engineering. 7(1). 16011–16011. 65 indexed citations

18.

Lynch, Joshua, et al.. (2010). Analysis of the expression of retinoic acid metabolising genes during Xenopus laevis organogenesis. Gene Expression Patterns. 11(1-2). 112–117. 14 indexed citations

19.

Tan, Heng‐Ru May, Arthur C. Leuthold, David N. Lee, Joshua Lynch, & Apostolos P. Georgopoulos. (2009). Neural mechanisms of movement speed and tau as revealed by magnetoencephalography. Experimental Brain Research. 195(4). 541–552. 16 indexed citations

20.

Jerde, Trenton A., Scott M. Lewis, Ute Goerke, et al.. (2008). Ultra-high field parallel imaging of the superior parietal lobule during mental maze solving. Experimental Brain Research. 187(4). 551–561. 15 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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