Beryl Ampong

444 total citations
8 papers, 383 citations indexed

About

Beryl Ampong is a scholar working on Molecular Biology, Physiology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Beryl Ampong has authored 8 papers receiving a total of 383 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 2 papers in Physiology and 1 paper in Cellular and Molecular Neuroscience. Recurrent topics in Beryl Ampong's work include Muscle Physiology and Disorders (7 papers), Hormonal Regulation and Hypertension (1 paper) and Viral Infections and Immunology Research (1 paper). Beryl Ampong is often cited by papers focused on Muscle Physiology and Disorders (7 papers), Hormonal Regulation and Hypertension (1 paper) and Viral Infections and Immunology Research (1 paper). Beryl Ampong collaborates with scholars based in United States, Japan and Australia. Beryl Ampong's co-authors include Kanneboyina Nagaraju, Rashmi Rawat, Tatiana V. Cohen, Andrea Henriques‐Pons, Eric P. Hoffman, Michihiro Imamura, Shin’ichi Takeda, Mikiharu Yoshida, Sree Rayavarapu and J. H. van der Meulen and has published in prestigious journals such as Human Molecular Genetics, American Journal Of Pathology and The Journal of Pathology.

In The Last Decade

Beryl Ampong

8 papers receiving 381 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Beryl Ampong United States	8	316	113	76	57	49	8	383
Vanessa E. Jahnke United States	9	357 1.1×	178 1.6×	43 0.6×	58 1.0×	32 0.7×	12	441
Yi-Wei Lin United States	16	258 0.8×	112 1.0×	99 1.3×	43 0.8×	27 0.6×	19	453
Reem Abo‐Zahrah United States	6	208 0.7×	93 0.8×	77 1.0×	62 1.1×	21 0.4×	7	301
Shouta Miyatake Japan	10	282 0.9×	106 0.9×	16 0.2×	63 1.1×	32 0.7×	14	372
Casey L. Egan Australia	3	356 1.1×	156 1.4×	62 0.8×	85 1.5×	83 1.7×	7	511
Megan Krumpoch United States	4	261 0.8×	181 1.6×	79 1.0×	20 0.4×	24 0.5×	7	385
Patricio V. Sepulveda United States	7	359 1.1×	195 1.7×	43 0.6×	40 0.7×	34 0.7×	8	473
Zoe White Canada	11	250 0.8×	204 1.8×	42 0.6×	37 0.6×	49 1.0×	23	378
Myra E. Woodworth‐Hobbs United States	7	287 0.9×	155 1.4×	55 0.7×	45 0.8×	25 0.5×	10	408
T. Hata Japan	4	420 1.3×	232 2.1×	32 0.4×	73 1.3×	23 0.5×	6	531

Countries citing papers authored by Beryl Ampong

Since Specialization

Citations

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

Fields of papers citing papers by Beryl Ampong

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Beryl Ampong

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

All Works

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8 of 8 papers shown

1.

Dillingham, Blythe C., Ramkishore Gernapudi, Sree Rayavarapu, et al.. (2015). Inhibition of inflammation with celastrol fails to improve muscle function in dysferlin-deficient A/J mice. Journal of the Neurological Sciences. 356(1-2). 157–162. 12 indexed citations

2.

Henriques‐Pons, Andrea, Qing Yu, Sree Rayavarapu, et al.. (2013). Role of toll-like receptors in the pathogenesis of dystrophin-deficient skeletal and heart muscle. Human Molecular Genetics. 23(10). 2604–2617. 58 indexed citations

3.

Uaesoontrachoon, Kitipong, Hee‐Jae Cha, Beryl Ampong, et al.. (2013). The effects of MyD88 deficiency on disease phenotype in dysferlin‐deficient A/J mice: role of endogenous TLR ligands. The Journal of Pathology. 231(2). 199–209. 24 indexed citations

4.

Coley, William, Sree Rayavarapu, Richard L. Sabina, et al.. (2012). The molecular basis of skeletal muscle weakness in a mouse model of inflammatory myopathy. Arthritis & Rheumatism. 64(11). 3750–3759. 48 indexed citations

5.

Rawat, Rashmi, Tatiana V. Cohen, Beryl Ampong, et al.. (2010). Inflammasome Up-Regulation and Activation in Dysferlin-Deficient Skeletal Muscle. American Journal Of Pathology. 176(6). 2891–2900. 150 indexed citations

6.

Nishiyama, Akiyo, Beryl Ampong, Jin‐Hong Shin, et al.. (2008). Recombinant Adeno-Associated Virus Type 8-Mediated Extensive Therapeutic Gene Delivery into Skeletal Muscle of α -Sarcoglycan-Deficient Mice. Human Gene Therapy. 19(7). 719–730. 10 indexed citations

7.

Ampong, Beryl, et al.. (2005). Intracellular localization of dysferlin and its association with the dihydropyridine receptor.. PubMed. 24(2). 134–44. 71 indexed citations

8.

Ampong, Beryl, Hideo Honda, & Hiroshi Kogo. (2002). Effect of hypothyroidism on β-adrenoceptor-mediated relaxation in the rat thoracic aortae. Vascular Pharmacology. 38(3). 149–155. 10 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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