P. J. Hagerman

1.6k total citations
9 papers, 1.2k citations indexed

About

P. J. Hagerman is a scholar working on Genetics, Molecular Biology and Cognitive Neuroscience. According to data from OpenAlex, P. J. Hagerman has authored 9 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Genetics, 6 papers in Molecular Biology and 6 papers in Cognitive Neuroscience. Recurrent topics in P. J. Hagerman's work include Genetics and Neurodevelopmental Disorders (9 papers), Autism Spectrum Disorder Research (6 papers) and Genomic variations and chromosomal abnormalities (3 papers). P. J. Hagerman is often cited by papers focused on Genetics and Neurodevelopmental Disorders (9 papers), Autism Spectrum Disorder Research (6 papers) and Genomic variations and chromosomal abnormalities (3 papers). P. J. Hagerman collaborates with scholars based in United States, Netherlands and India. P. J. Hagerman's co-authors include Flora Tassone, Dolores Garcia-Arocena, Randi J. Hagerman, Rob Willemsen, Francesco Amaldi, Claudia Bagni, Faraz Farzin, David Hessl, Robert F. Berman and Danuta Z. Loesch and has published in prestigious journals such as Nucleic Acids Research, Human Molecular Genetics and Cell Reports.

In The Last Decade

P. J. Hagerman

9 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
P. J. Hagerman United States	9	1.1k	754	667	171	104	9	1.2k
Randi J. Hagerman United States	19	1.4k 1.2×	852 1.1×	947 1.4×	182 1.1×	91 0.9×	31	1.6k
Sarah M. Coffey United States	11	990 0.9×	642 0.9×	596 0.9×	250 1.5×	126 1.2×	12	1.2k
John B. Vincent Canada	11	878 0.8×	656 0.9×	539 0.8×	113 0.7×	85 0.8×	19	1.1k
Jennifer B. Cogswell United States	16	1.4k 1.2×	896 1.2×	665 1.0×	345 2.0×	215 2.1×	20	1.5k
Sarah L. Nolin United States	21	1.4k 1.3×	833 1.1×	927 1.4×	135 0.8×	57 0.5×	44	1.6k
Susan Harris United States	9	1.1k 1.0×	595 0.8×	821 1.2×	108 0.6×	80 0.8×	13	1.2k
Holly N. Cukier United States	16	518 0.5×	525 0.7×	403 0.6×	147 0.9×	98 0.9×	26	1.0k
Reymundo Lozano United States	20	819 0.7×	552 0.7×	519 0.8×	100 0.6×	40 0.4×	44	1.1k
Crystal Hervey United States	9	698 0.6×	425 0.6×	566 0.8×	127 0.7×	38 0.4×	11	871
James Jaworski United States	17	588 0.5×	372 0.5×	546 0.8×	153 0.9×	60 0.6×	19	951

Countries citing papers authored by P. J. Hagerman

Since Specialization

Citations

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

Fields of papers citing papers by P. J. Hagerman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of P. J. Hagerman

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

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Ludwig, A. L., Dalyir Pretto, Glòria Arqué, et al.. (2014). CNS expression of murine fragile X protein (FMRP) as a function of CGG-repeat size. Human Molecular Genetics. 23(12). 3228–3238. 57 indexed citations

2.

Sellier, Chantal, Fernande Freyermuth, Ricardos Tabet, et al.. (2013). Sequestration of DROSHA and DGCR8 by Expanded CGG RNA Repeats Alters MicroRNA Processing in Fragile X-Associated Tremor/Ataxia Syndrome. Cell Reports. 3(3). 869–880. 189 indexed citations

3.

Garcia-Arocena, Dolores & P. J. Hagerman. (2010). Advances in understanding the molecular basis of FXTAS. Human Molecular Genetics. 19(R1). R83–R89. 114 indexed citations

4.

Ludwig, A. L., et al.. (2009). Translation of the FMR1 mRNA is not influenced by AGG interruptions. Nucleic Acids Research. 37(20). 6896–6904. 18 indexed citations

5.

Berman, Robert F., et al.. (2009). Murine hippocampal neurons expressing Fmr1 gene premutations show early developmental deficits and late degeneration. Human Molecular Genetics. 19(1). 196–208. 120 indexed citations

6.

Hagerman, P. J.. (2008). The fragile X prevalence paradox. Journal of Medical Genetics. 45(8). 498–499. 258 indexed citations

7.

Leehey, Maureen A., et al.. (2006). Size bias of fragile X premutation alleles in late-onset movement disorders. Journal of Medical Genetics. 43(10). 804–809. 89 indexed citations

8.

Farzin, Faraz, Hazel Perry, David Hessl, et al.. (2006). Autism Spectrum Disorders and Attention-Deficit/Hyperactivity Disorder in Boys with the Fragile X Premutation. Journal of Developmental & Behavioral Pediatrics. 27(Supplement 2). S137–S144. 243 indexed citations

9.

Tassone, Flora, et al.. (2002). Reduced FMR1 mRNA translation efficiency in Fragile X patients with premutations. RNA. 8(12). 1482–1488. 151 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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