Mark Zervas

2.2k total citations
23 papers, 1.4k citations indexed

About

Mark Zervas is a scholar working on Molecular Biology, Developmental Neuroscience and Cellular and Molecular Neuroscience. According to data from OpenAlex, Mark Zervas has authored 23 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 8 papers in Developmental Neuroscience and 5 papers in Cellular and Molecular Neuroscience. Recurrent topics in Mark Zervas's work include Developmental Biology and Gene Regulation (8 papers), Neurogenesis and neuroplasticity mechanisms (8 papers) and Pluripotent Stem Cells Research (5 papers). Mark Zervas is often cited by papers focused on Developmental Biology and Gene Regulation (8 papers), Neurogenesis and neuroplasticity mechanisms (8 papers) and Pluripotent Stem Cells Research (5 papers). Mark Zervas collaborates with scholars based in United States and Germany. Mark Zervas's co-authors include Steven U. Walkley, Alexandra L. Joyner, Kostantin Dobrenis, Mary Anna Thrall, Sohyun Ahn, Sandrine Millet, Nellwyn Hagan, Sandra Blaess, Ashly Brown and Lindsay N. Hayes and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Neuron and PLoS ONE.

In The Last Decade

Mark Zervas

23 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark Zervas United States 16 757 543 326 311 249 23 1.4k
Maria I. Givogri United States 27 995 1.3× 892 1.6× 430 1.3× 226 0.7× 477 1.9× 51 2.0k
Hong Hua Li United States 15 781 1.0× 540 1.0× 254 0.8× 99 0.3× 138 0.6× 16 1.6k
Michael Tanowitz United States 22 1.3k 1.7× 132 0.2× 243 0.7× 583 1.9× 59 0.2× 29 1.7k
Stuart J. Rabin United States 19 972 1.3× 165 0.3× 187 0.6× 831 2.7× 320 1.3× 25 1.7k
Friso R. Postma Netherlands 17 1.8k 2.4× 283 0.5× 492 1.5× 336 1.1× 51 0.2× 19 2.1k
Shibi Likhite United States 15 928 1.2× 290 0.5× 52 0.2× 306 1.0× 157 0.6× 36 1.9k
Bénédicte C. Charrin France 3 1.3k 1.8× 124 0.2× 372 1.1× 1.1k 3.4× 107 0.4× 3 1.7k
Marka van Blitterswijk United States 24 1.3k 1.8× 414 0.8× 147 0.5× 525 1.7× 30 0.1× 47 2.8k
Seung Chun United States 11 1.1k 1.5× 286 0.5× 35 0.1× 329 1.1× 93 0.4× 11 2.0k
Sibylle Jablonka Germany 28 2.2k 2.9× 125 0.2× 236 0.7× 568 1.8× 125 0.5× 69 3.0k

Countries citing papers authored by Mark Zervas

Since Specialization
Citations

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

Fields of papers citing papers by Mark Zervas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Zervas

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

All Works

20 of 20 papers shown
1.
Hagan, Nellwyn, et al.. (2017). The Temporal Contribution of the Gbx2 Lineage to Cerebellar Neurons. Frontiers in Neuroanatomy. 11. 50–50. 5 indexed citations
2.
3.
Brown, Ashly, et al.. (2013). Dynamic temporal requirement ofWnt1in midbrain dopamine neuron development. Development. 140(6). 1342–1352. 38 indexed citations
4.
Normand, Elizabeth A., Shane R. Crandall, Catherine A. Thorn, et al.. (2013). Temporal and Mosaic Tsc1 Deletion in the Developing Thalamus Disrupts Thalamocortical Circuitry, Neural Function, and Behavior. Neuron. 78(5). 895–909. 46 indexed citations
5.
Machan, Jason T., et al.. (2012). Genetic dissection of midbrain dopamine neuron development in vivo. Developmental Biology. 372(2). 249–262. 15 indexed citations
6.
Brown, Ashly, Jason T. Machan, Lindsay N. Hayes, & Mark Zervas. (2011). Molecular organization and timing of Wnt1 expression define cohorts of midbrain dopamine neuron progenitors in vivo. The Journal of Comparative Neurology. 519(15). 2978–3000. 27 indexed citations
7.
Zervas, Mark, et al.. (2011). The Lineage Contribution and Role of Gbx2 in Spinal Cord Development. PLoS ONE. 6(6). e20940–e20940. 16 indexed citations
8.
Hayes, Lindsay N., Zhiwei Zhang, Paul R. Albert, Mark Zervas, & Sohyun Ahn. (2011). Timing ofSonic hedgehogandGli1expression segregates midbrain dopamine neurons. The Journal of Comparative Neurology. 519(15). 3001–3018. 52 indexed citations
9.
Hagan, Nellwyn & Mark Zervas. (2011). Wnt1 expression temporally allocates upper rhombic lip progenitors and defines their terminal cell fate in the cerebellum. Molecular and Cellular Neuroscience. 49(2). 217–229. 22 indexed citations
10.
Zervas, Mark, et al.. (2010). Tamoxifen dose response and conditional cell marking: Is there control?. Molecular and Cellular Neuroscience. 45(2). 132–138. 14 indexed citations
11.
Koveal, Dorothy, et al.. (2009). Comparative analysis of conditional reporter alleles in the developing embryo and embryonic nervous system. Gene Expression Patterns. 9(7). 475–489. 13 indexed citations
12.
Brown, Ashly, et al.. (2009). A Practical Approach to Genetic Inducible Fate Mapping: A Visual Guide to Mark and Track Cells <em>In Vivo</em>. Journal of Visualized Experiments. 13 indexed citations
13.
Brown, Ashly, et al.. (2009). A Practical Approach to Genetic Inducible Fate Mapping: A Visual Guide to Mark and Track Cells <em>In Vivo</em>. Journal of Visualized Experiments. 1 indexed citations
14.
Joyner, Alexandra L. & Mark Zervas. (2006). Genetic inducible fate mapping in mouse: Establishing genetic lineages and defining genetic neuroanatomy in the nervous system. Developmental Dynamics. 235(9). 2376–2385. 138 indexed citations
15.
Zervas, Mark, Thoralf Opitz, Winfried Edelmann, et al.. (2005). Impaired hippocampal long-term potentiation in microtubule-associated protein 1B-deficient mice. Journal of Neuroscience Research. 82(1). 83–92. 24 indexed citations
16.
Zervas, Mark, Sandra Blaess, & Alexandra L. Joyner. (2005). Classical Embryological Studies and Modern Genetic Analysis of Midbrain and Cerebellum Development. Current topics in developmental biology. 69. 101–138. 67 indexed citations
17.
Zervas, Mark, Sandrine Millet, Sohyun Ahn, & Alexandra L. Joyner. (2004). Cell Behaviors and Genetic Lineages of the Mesencephalon and Rhombomere 1. Neuron. 43(3). 345–357. 211 indexed citations
18.
Zervas, Mark, et al.. (2001). Critical role for glycosphingolipids in Niemann-Pick disease type C. Current Biology. 11(16). 1283–1287. 271 indexed citations
19.
Zervas, Mark, Kostantin Dobrenis, & Steven U. Walkley. (2001). Neurons in Niemann-Pick Disease Type C Accumulate Gangliosides as Well as Unesterified Cholesterol and Undergo Dendritic and Axonal Alterations. Journal of Neuropathology & Experimental Neurology. 60(1). 49–64. 229 indexed citations
20.
Walkley, Steven U., Donald S. Siegel, Kostantin Dobrenis, & Mark Zervas. (1998). GM2 Ganglioside as a Regulator of Pyramidal Neuron Dendritogenesisa. Annals of the New York Academy of Sciences. 845(1). 188–199. 28 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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