Peter Dias

1.6k total citations
24 papers, 1.3k citations indexed

About

Peter Dias is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Cancer Research. According to data from OpenAlex, Peter Dias has authored 24 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 11 papers in Pulmonary and Respiratory Medicine and 5 papers in Cancer Research. Recurrent topics in Peter Dias's work include Sarcoma Diagnosis and Treatment (11 papers), Tumors and Oncological Cases (4 papers) and Muscle Physiology and Disorders (3 papers). Peter Dias is often cited by papers focused on Sarcoma Diagnosis and Treatment (11 papers), Tumors and Oncological Cases (4 papers) and Muscle Physiology and Disorders (3 papers). Peter Dias collaborates with scholars based in United States, United Kingdom and Kuwait. Peter Dias's co-authors include Peter J. Houghton, David M. Parham, David N. Shapiro, Peter J. Houghton, LH Shapiro, Bart G. Jones, Juan Rosaí, Sujay Singh, Bruce L. Webber and Glen S. Germain and has published in prestigious journals such as Journal of Clinical Investigation, Blood and American Journal Of Pathology.

In The Last Decade

Peter Dias

24 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peter Dias United States 18 635 580 293 250 197 24 1.3k
Jean‐Pierre Fryns Belgium 21 174 0.3× 1.2k 2.1× 130 0.4× 92 0.4× 85 0.4× 25 2.0k
B. de Leeuw Netherlands 16 409 0.6× 532 0.9× 150 0.5× 252 1.0× 150 0.8× 26 1.5k
David J. Bunyan United Kingdom 23 153 0.2× 991 1.7× 304 1.0× 232 0.9× 107 0.5× 60 2.0k
Nicolas Chassaing France 25 151 0.2× 1.1k 1.9× 148 0.5× 104 0.4× 175 0.9× 83 2.1k
Marios Kambouris United States 18 286 0.5× 436 0.8× 36 0.1× 123 0.5× 101 0.5× 50 1.3k
Fernando Gianfrancesco Italy 23 199 0.3× 613 1.1× 58 0.2× 309 1.2× 222 1.1× 73 1.4k
D. W. Burton United States 23 142 0.2× 599 1.0× 104 0.4× 447 1.8× 155 0.8× 38 1.2k
Teresa Esposito Italy 23 172 0.3× 660 1.1× 52 0.2× 261 1.0× 203 1.0× 82 1.4k
Monika Grabowski Germany 6 156 0.2× 490 0.8× 300 1.0× 344 1.4× 336 1.7× 7 1.7k
Nadia Sakati Saudi Arabia 22 111 0.2× 819 1.4× 106 0.4× 111 0.4× 123 0.6× 78 1.7k

Countries citing papers authored by Peter Dias

Since Specialization
Citations

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

Fields of papers citing papers by Peter Dias

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter Dias

This figure shows the co-authorship network connecting the top 25 collaborators of Peter Dias. A scholar is included among the top collaborators of Peter Dias 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 Peter Dias. Peter Dias 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.
Dias, Peter, et al.. (2008). Differential influence of gp63-like molecules in three distinct Leptomonas species on the adhesion to insect cells. Parasitology Research. 104(2). 347–353. 16 indexed citations
2.
Dias, Peter, Bin Chen, Hal E. Palmer, et al.. (2000). Strong Immunostaining for Myogenin in Rhabdomyosarcoma Is Significantly Associated with Tumors of the Alveolar Subclass. American Journal Of Pathology. 156(2). 399–408. 140 indexed citations
3.
Wu, Chen, Sujay Singh, Peter Dias, S. Kumar, & David Mann. (1999). Activated Astrocytes Display Increased 5-HT2a Receptor Expression in Pathological States. Experimental Neurology. 158(2). 529–533. 37 indexed citations
4.
Dias, Peter, et al.. (1998). Mutation of Thr115 in MyoD positively regulates function in murine fibroblasts and human rhabdomyosarcoma cells.. PubMed. 9(9). 699–711. 18 indexed citations
5.
Chen, Bin, et al.. (1998). Methylation alterations of the MyoD1 upstream region are predictive of subclassification of human rhabdomyosarcomas.. PubMed. 152(4). 1071–9. 32 indexed citations
6.
Wu, Chun, Elizabeth Yoder, Jean C. Shih, et al.. (1998). Development and Characterization of Monoclonal Antibodies Specific to the Serotonin 5-HT2A Receptor. Journal of Histochemistry & Cytochemistry. 46(7). 811–824. 61 indexed citations
7.
8.
Dias, Peter, et al.. (1997). Live food production using batch culture and chemostat systems in Kuwait. Hydrobiologia. 358(1-3). 173–178. 12 indexed citations
9.
Dias, Peter, et al.. (1996). Alpha 2a-interferon-induced differentiation of human alveolar rhabdomyosarcoma cells: correlation with down-regulation of the insulin-like growth factor type I receptor.. PubMed. 7(4). 531–41. 23 indexed citations
10.
Fletcher, Christopher D.�M., et al.. (1995). Immunohistochemistry of MyoD1 in Adult Pleomorphic Soft Tissue Sarcomas. The American Journal of Surgical Pathology. 19(3). 261–269. 34 indexed citations
11.
Parham, David M., T. E. Bertoríni, Peter Dias, et al.. (1994). Immunohistochemical analysis of the distribution of MyoD1 in muscle biopsies of primary myopathies and neurogenic atrophy. Acta Neuropathologica. 87(6). 605–611. 8 indexed citations
12.
Dias, Peter, et al.. (1994). The molecular basis of skeletal muscle differentiation.. PubMed. 11(1). 3–14. 73 indexed citations
13.
Shapiro, David N., Bart G. Jones, LH Shapiro, Peter Dias, & Peter J. Houghton. (1994). Antisense-mediated reduction in insulin-like growth factor-I receptor expression suppresses the malignant phenotype of a human alveolar rhabdomyosarcoma.. Journal of Clinical Investigation. 94(3). 1235–1242. 142 indexed citations
14.
Dilling, Michael B., Peter Dias, David N. Shapiro, et al.. (1994). Rapamycin selectively inhibits the growth of childhood rhabdomyosarcoma cells through inhibition of signaling via the type I insulin-like growth factor receptor.. PubMed. 54(4). 903–7. 115 indexed citations
15.
Parham, David M., Peter Dias, David R. Kelly, Joe C. Rutledge, & Peter J. Houghton. (1992). Desmin Positivity in Primitive Neuroectodermal Tumors of Childhood. The American Journal of Surgical Pathology. 16(5). 483–492. 78 indexed citations
16.
Dias, Peter, et al.. (1992). Prognostic relevance of DNA ploidy in rhabdomyosarcomas and other sarcomas of childhood.. PubMed. 12(4). 1173–7. 5 indexed citations
17.
Dias, Peter, David M. Parham, David N. Shapiro, Stephen J. Tapscott, & Peter J. Houghton. (1992). Monoclonal antibodies to the myogenic regulatory protein MyoD1: epitope mapping and diagnostic utility.. PubMed. 52(23). 6431–9. 92 indexed citations
18.
Rosaí, Juan, Peter Dias, David M. Parham, David N. Shapiro, & Peter Houghton. (1991). MyoDl Protein Expression in Alveolar Soft Part Sarcoma As Confirmatory Evidence of Its Skeletal Muscle Nature. The American Journal of Surgical Pathology. 15(10). 974–981. 85 indexed citations
19.
Dias, Peter, Patricia Kumar, H. B. Marsden, et al.. (1990). N‐myc gene is amplified in alveolar rhabdomyosarcomas (RMS) but not in embryonal RMS. International Journal of Cancer. 45(4). 593–596. 52 indexed citations
20.
Dias, Peter, Patricia Kumar, H. B. Marsden, et al.. (1987). Evaluation of desmin as a diagnostic and prognostic marker of childhood rhabdomyosarcomas and embryonal sarcomas. British Journal of Cancer. 56(3). 361–365. 31 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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