Glenn J. Markov

719 total citations
11 papers, 493 citations indexed

About

Glenn J. Markov is a scholar working on Molecular Biology, Genetics and Physiology. According to data from OpenAlex, Glenn J. Markov has authored 11 papers receiving a total of 493 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 4 papers in Genetics and 2 papers in Physiology. Recurrent topics in Glenn J. Markov's work include Adipose Tissue and Metabolism (2 papers), Genomics and Rare Diseases (2 papers) and Pluripotent Stem Cells Research (2 papers). Glenn J. Markov is often cited by papers focused on Adipose Tissue and Metabolism (2 papers), Genomics and Rare Diseases (2 papers) and Pluripotent Stem Cells Research (2 papers). Glenn J. Markov collaborates with scholars based in United States, Sweden and India. Glenn J. Markov's co-authors include Thach Mai, Helen M. Blau, Matthew J. Huentelman, Kenro Kusumi, Walter L. Eckalbar, Jason J. Corneveaux, April N. Allen, Yu Xin Wang, Sudhir Kumar and Nora Yucel and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and Nature Cell Biology.

In The Last Decade

Glenn J. Markov

11 papers receiving 485 citations

Peers

Glenn J. Markov

GENET

PHYSI

BIOMA

Ahmed Elewa United States

Michael Phelps United States

Anne Czechanski United States

Juan Carlos Izpisua Belmonte United States

Marina Feigenson United States

Artur Jaroszewicz United States

Andriy S. Yatsenko Germany

Hervé Faralli Canada

Diana M. Ho United States

Alejandro Leal Costa Rica

Ahmed Elewa United States

Glenn J. Markov

457 ×1.3

65 ×0.5

GENET

21 ×0.4

PHYSI

51 ×1.2

40 ×1.0

BIOMA

Citations per year, relative to Glenn J. Markov Glenn J. Markov (= 1×) peers Ahmed Elewa

Countries citing papers authored by Glenn J. Markov

Since Specialization

Citations

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

Fields of papers citing papers by Glenn J. Markov

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Glenn J. Markov. 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 Glenn J. Markov. The network helps show where Glenn J. Markov may publish in the future.

Co-authorship network of co-authors of Glenn J. Markov

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

All Works

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11 of 11 papers shown

Wang, Yu Xin, Adelaida R. Palla, Andrew Tri Van Ho, et al.. (2025). Multiomic profiling reveals that prostaglandin E2 reverses aged muscle stem cell dysfunction, leading to increased regeneration and strength. Cell stem cell. 32(7). 1154–1169.e9. 1 indexed citations

Markov, Glenn J., Thach Mai, Surag Nair, et al.. (2021). AP-1 is a temporally regulated dual gatekeeper of reprogramming to pluripotency. Proceedings of the National Academy of Sciences. 118(23). 24 indexed citations

Yucel, Nora, Yu Xin Wang, Thach Mai, et al.. (2019). Glucose Metabolism Drives Histone Acetylation Landscape Transitions that Dictate Muscle Stem Cell Function. Cell Reports. 27(13). 3939–3955.e6. 114 indexed citations

Mai, Thach, Glenn J. Markov, Jennifer J. Brady, et al.. (2018). NKX3-1 is required for induced pluripotent stem cell reprogramming and can replace OCT4 in mouse and human iPSC induction. Nature Cell Biology. 20(8). 900–908. 38 indexed citations

Gierman, Hinco J., Kristen Fortney, Jared C. Roach, et al.. (2014). Whole-Genome Sequencing of the World’s Oldest People. PLoS ONE. 9(11). e112430–e112430. 36 indexed citations

Hutchins, Elizabeth, Glenn J. Markov, Walter L. Eckalbar, et al.. (2014). Transcriptomic Analysis of Tail Regeneration in the Lizard Anolis carolinensis Reveals Activation of Conserved Vertebrate Developmental and Repair Mechanisms. PLoS ONE. 9(8). e105004–e105004. 107 indexed citations

Eckalbar, Walter L., Elizabeth Hutchins, Glenn J. Markov, et al.. (2013). Genome reannotation of the lizard Anolis carolinensis based on 14 adult and embryonic deep transcriptomes. BMC Genomics. 14(1). 49–49. 45 indexed citations

Dudley, Joel T., Yuseob Kim, Li Liu, et al.. (2012). Human genomic disease variants: A neutral evolutionary explanation. Genome Research. 22(8). 1383–1394. 33 indexed citations

Eckalbar, Walter L., Carlos R. Infante, Ruth M. Elsey, et al.. (2011). Somitogenesis in the anole lizard and alligator reveals evolutionary convergence and divergence in the amniote segmentation clock. Developmental Biology. 363(1). 308–319. 45 indexed citations

10.

Markov, Glenn J., Rajani M. George, Michael J. Ammar, et al.. (2010). Developmental gene activation in tail regeneration in the lizard, Anolis carolinensis. Developmental Biology. 344(1). 519–520. 2 indexed citations

11.

Kumar, Sudhir, et al.. (2009). Positional conservation and amino acids shape the correct diagnosis and population frequencies of benign and damaging personal amino acid mutations. Genome Research. 19(9). 1562–1569. 48 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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