Michael A. Nolan

2.1k total citations · 1 hit paper
18 papers, 1.3k citations indexed

About

Michael A. Nolan is a scholar working on Cognitive Neuroscience, Epidemiology and Nutrition and Dietetics. According to data from OpenAlex, Michael A. Nolan has authored 18 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Cognitive Neuroscience, 4 papers in Epidemiology and 4 papers in Nutrition and Dietetics. Recurrent topics in Michael A. Nolan's work include Sperm and Testicular Function (3 papers), EEG and Brain-Computer Interfaces (3 papers) and Trace Elements in Health (2 papers). Michael A. Nolan is often cited by papers focused on Sperm and Testicular Function (3 papers), EEG and Brain-Computer Interfaces (3 papers) and Trace Elements in Health (2 papers). Michael A. Nolan collaborates with scholars based in United States, Australia and Canada. Michael A. Nolan's co-authors include G. Stanley McKnight, Kimberly A. Burton, W. Mark Brown, Donner F. Babcock, Gunther Wennemuth, Mercedes Lobera, Scott Davis, Holly Ponichtera, Anthony Letai and Sara Schad and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Scientific Reports.

In The Last Decade

Michael A. Nolan

17 papers receiving 1.3k citations

Hit 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.

Class IIa HDAC inhibition reduces breast tumours and metastases through anti-tumour macrophages

2017 432 citations Jennifer L. Guerriero, Alaba Sotayo et al. Nature profile →

Peers

Michael A. Nolan

IMMUN

PHEOH

Aliesha González‐Arenas Mexico

Alina Isakova United States

Valgerður Steinthórsdóttir Iceland

Niles Fox United States

Michele Salemi Italy

Thierry Coppola France

Jingwen Yin China

Yuyu Niu China

Yihe Wang China

Han S. Lee United States

Aliesha González‐Arenas Mexico

Michael A. Nolan

505 ×1.3

189 ×0.5

IMMUN

158 ×0.5

61 ×0.2

56 ×0.2

PHEOH

Citations per year, relative to Michael A. Nolan Michael A. Nolan (= 1×) peers Aliesha González‐Arenas

Countries citing papers authored by Michael A. Nolan

Since Specialization

Citations

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

Fields of papers citing papers by Michael A. Nolan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael A. Nolan

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

All Works

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18 of 18 papers shown

Monteleone, Mercedes, Hiroto Kambara, Alina Starchenko, et al.. (2023). Quantifying Cell Death Induced by the NLRC4 Inflammasome. Methods in molecular biology. 2696. 199–210. 1 indexed citations

Rao, Hrishikesh M., Tanya Talkar, Gregory Ciccarelli, et al.. (2020). Sensorimotor conflict tests in an immersive virtual environment reveal subclinical impairments in mild traumatic brain injury. Scientific Reports. 10(1). 9 indexed citations

Ciccarelli, Gregory, Michael A. Nolan, Hrishikesh M. Rao, et al.. (2020). Human balance models optimized using a large-scale, parallel architecture with applications to mild traumatic brain injury. 9. 1–8. 2 indexed citations

Ciccarelli, Gregory, Michael A. Nolan, Paul Calamia, et al.. (2019). Comparison of Two-Talker Attention Decoding from EEG with Nonlinear Neural Networks and Linear Methods. Scientific Reports. 9(1). 11538–11538. 92 indexed citations

Nolan, Michael A., et al.. (2019). ECG Feature Processing Performance Acceleration on SLURM Compute Systems. 7. 1–4.

Guerriero, Jennifer L., Alaba Sotayo, Holly Ponichtera, et al.. (2017). Class IIa HDAC inhibition reduces breast tumours and metastases through anti-tumour macrophages. Nature. 543(7645). 428–432. 432 indexed citations breakdown →

Quatieri, Thomas F., James R. Williamson, Christopher J. Smalt, et al.. (2016). Using EEG to Discriminate Cognitive Workload and Performance Based on Neural Activation and Connectivity. 7 indexed citations

Skepner, Jill, Radha Ramesh, Xiaoyan A. Qu, et al.. (2015). In vivo regulation of gene expression and T helper type 17 differentiation by RORγt inverse agonists. Immunology. 145(3). 347–356. 14 indexed citations

Dort, Christa J. Van, Daniel P. Zachs, Jonathan D. Kenny, et al.. (2014). Optogenetic activation of cholinergic neurons in the PPT or LDT induces REM sleep. Proceedings of the National Academy of Sciences. 112(2). 584–589. 208 indexed citations

10.

Sundrud, Mark S. & Michael A. Nolan. (2010). Synergistic and combinatorial control of T cell activation and differentiation by transcription factors. Current Opinion in Immunology. 22(3). 286–292. 26 indexed citations

11.

Roberts, Kenneth P., et al.. (2007). Structure and function of epididymal protein cysteine-rich secretory protein-1. Asian Journal of Andrology. 9(4). 508–514. 51 indexed citations

12.

Burton, Kimberly A., Deborah A. McDermott, David Wilkes, et al.. (2006). Haploinsufficiency at the Protein Kinase A RIα Gene Locus Leads to Fertility Defects in Male Mice and Men. Molecular Endocrinology. 20(10). 2504–2513. 50 indexed citations

13.

Nolan, Michael A., Leeying Wu, Hyun J. Bang, et al.. (2006). Identification of Rat Cysteine-Rich Secretory Protein 4 (Crisp4) as the Ortholog to Human CRISP1 and Mouse Crisp4. Biology of Reproduction. 74(5). 984–991. 52 indexed citations

14.

Roberts, Kenneth P., Kathy M. Ensrud, Joseph L. Wooters, et al.. (2006). Epididymal secreted protein Crisp-1 and sperm function. Molecular and Cellular Endocrinology. 250(1-2). 122–127. 59 indexed citations

15.

Nolan, Michael A., Donner F. Babcock, Gunther Wennemuth, et al.. (2004). Sperm-specific protein kinase A catalytic subunit Cα ₂ orchestrates cAMP signaling for male fertility. Proceedings of the National Academy of Sciences. 101(37). 13483–13488. 210 indexed citations

16.

Newhall, Kathryn J., David E. Cummings, Michael A. Nolan, & G. Stanley McKnight. (2004). Deletion of the RIIβ-Subunit of Protein Kinase A Decreases Body Weight and Increases Energy Expenditure in the Obese, Leptin-Deficient ob/ob Mouse. Molecular Endocrinology. 19(4). 982–991. 23 indexed citations

17.

Nolan, Michael A., et al.. (2004). The Role of Uncoupling Protein 1 in the Metabolism and Adiposity of RIIβ-Protein Kinase A-Deficient Mice. Molecular Endocrinology. 18(9). 2302–2311. 31 indexed citations

18.

Hansen, Karl R., Stephanie M. Krasnow, Michael A. Nolan, et al.. (2003). Activation of the Sympathetic Nervous System by Galanin-Like Peptide—A Possible Link between Leptin and Metabolism. Endocrinology. 144(11). 4709–4717. 58 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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