Stephen M. Becker

1.8k total citations
17 papers, 582 citations indexed

About

Stephen M. Becker is a scholar working on Surgery, Molecular Biology and Cancer Research. According to data from OpenAlex, Stephen M. Becker has authored 17 papers receiving a total of 582 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Surgery, 5 papers in Molecular Biology and 5 papers in Cancer Research. Recurrent topics in Stephen M. Becker's work include Parasitic Infections and Diagnostics (3 papers), Amoebic Infections and Treatments (3 papers) and Advanced Proteomics Techniques and Applications (2 papers). Stephen M. Becker is often cited by papers focused on Parasitic Infections and Diagnostics (3 papers), Amoebic Infections and Treatments (3 papers) and Advanced Proteomics Techniques and Applications (2 papers). Stephen M. Becker collaborates with scholars based in United States, Tanzania and Japan. Stephen M. Becker's co-authors include Eric R. Houpt, Jaco J. Verweij, Shihab U. Sobuz, Jean Gratz, Gibson Kibiki, Mami Taniuchi, Rashidul Haque, Doris M. Haverstick, Caroline Amour and Jie Liu and has published in prestigious journals such as Cancer Research, Journal of Clinical Microbiology and Molecular Microbiology.

In The Last Decade

Stephen M. Becker

16 papers receiving 571 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stephen M. Becker United States 10 248 194 116 114 69 17 582
Chuan Chiang-Ni Taiwan 16 318 1.3× 223 1.1× 21 0.2× 7 0.1× 32 0.5× 47 823
Shih-Hua Teng Taiwan 13 144 0.6× 171 0.9× 64 0.6× 7 0.1× 9 0.1× 18 581
M. D. Moody United States 13 340 1.4× 267 1.4× 23 0.2× 22 0.2× 7 0.1× 20 870
Jean-Philippe Émond France 12 88 0.4× 93 0.5× 7 0.1× 18 0.2× 25 0.4× 25 503
Kristin Surmann Germany 15 196 0.8× 329 1.7× 42 0.4× 5 0.0× 5 0.1× 42 602
B.K. Singh Germany 10 231 0.9× 108 0.6× 5 0.0× 24 0.2× 89 1.3× 21 498
Gregory A. Wasserman United States 16 326 1.3× 405 2.1× 22 0.2× 3 0.0× 17 0.2× 23 867
Anshika Singhal India 15 303 1.2× 307 1.6× 10 0.1× 10 0.1× 22 0.3× 20 623
Aušra Raudonikiene Lithuania 10 118 0.5× 279 1.4× 3 0.0× 56 0.5× 61 0.9× 18 706
Marcin Dembek United Kingdom 12 364 1.5× 260 1.3× 8 0.1× 11 0.1× 8 0.1× 15 649

Countries citing papers authored by Stephen M. Becker

Since Specialization
Citations

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

Fields of papers citing papers by Stephen M. Becker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephen M. Becker. 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 Stephen M. Becker. The network helps show where Stephen M. Becker may publish in the future.

Co-authorship network of co-authors of Stephen M. Becker

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

All Works

17 of 17 papers shown
1.
Becker, Stephen M., et al.. (2023). Can lung airway geometry be used to predict autism? A preliminary machine learning‐based study. The Anatomical Record. 307(2). 457–469. 1 indexed citations
2.
Manahan, Michele A., William A. Wooden, Stephen M. Becker, et al.. (2017). Evidence-Based Performance Measures: Quality Metrics for the Care of Patients Undergoing Breast Reconstruction. Plastic & Reconstructive Surgery. 140(6). 775e–781e. 9 indexed citations
3.
Karn, Thomas, Christos Hatzis, Nicole Sänger, et al.. (2017). Abstract S1-07: Immune sculpting of the triple negative breast cancer genome. Cancer Research. 77(4_Supplement). S1–7. 3 indexed citations
4.
Liu, Jie, Jean Gratz, Caroline Amour, et al.. (2012). A Laboratory-Developed TaqMan Array Card for Simultaneous Detection of 19 Enteropathogens. Journal of Clinical Microbiology. 51(2). 472–480. 277 indexed citations
5.
Becker, Stephen M., Paul Hoffman, & Eric R. Houpt. (2011). Efficacy of Antiamebic Drugs in a Mouse Model. American Journal of Tropical Medicine and Hygiene. 84(4). 581–586. 27 indexed citations
6.
Taran, Florin‐Andrei, Stephen M. Becker, Ralf Rothmund, et al.. (2011). Onkologie. Das Sentinel-Lymphknoten-Konzept beim Endometriumkarzinom. Geburtshilfe und Frauenheilkunde. 71(12). 1092–1094.
7.
Becker, Stephen M., et al.. (2010). Epithelial Cell Apoptosis Facilitates Entamoeba histolytica Infection in the Gut. American Journal Of Pathology. 176(3). 1316–1322. 36 indexed citations
8.
Becker, Stephen M., et al.. (2010). The NF-κB p50 Subunit Is Protective during Intestinal Entamoeba histolytica Infection of 129 and C57BL/6 Mice. Infection and Immunity. 78(4). 1475–1481. 5 indexed citations
9.
Hamano, Shinjiro, Stephen M. Becker, Amon Asgharpour, et al.. (2008). Gender and genetic control of resistance to intestinal amebiasis in inbred mice. Genes and Immunity. 9(5). 452–461. 12 indexed citations
10.
Becker, Stephen M., Robert Jeraj, & T Mackie. (2005). 474 Loss of buildup in prone breast treatments. Radiotherapy and Oncology. 76. S204–S204. 1 indexed citations
11.
Griffith, Kevin L., Stephen M. Becker, & Richard E. Wolf. (2005). Characterization of TetD as a transcriptional activator of a subset of genes of the Escherichia coli SoxS/MarA/Rob regulon. Molecular Microbiology. 56(4). 1103–1117. 17 indexed citations
12.
Laronga, Christine, Stephen M. Becker, Patrice Watson, et al.. (2004). SELDI‐TOF Serum Profiling for Prognostic and Diagnostic Classification of Breast Cancers. Disease Markers. 19(4-5). 229–238. 72 indexed citations
13.
Becker, Stephen M., Lisa H. Cazares, Patrice Watson, et al.. (2004). Surfaced-Enhanced Laser Desorption/Ionization Time-of-Flight (SELDI-TOF) Differentiation of Serum Protein Profiles of BRCA-1 and Sporadic Breast Cancer. Annals of Surgical Oncology. 11(10). 907–914. 75 indexed citations
14.
Becker, Stephen M., et al.. (2004). Discrimination of pre- and post-treatment breast cancer serum using SELDI-TOF MS (surfaced-enhanced laser desorption/ionization-time of flight mass spectrometry). Journal of the American College of Surgeons. 199(3). 89–89. 1 indexed citations
15.
Becker, Stephen M. & Kathleen L. McCoy. (2003). Gallium Arsenide Selectively Up-Regulates Inflammatory Cytokine Expression at Exposure Site. Journal of Pharmacology and Experimental Therapeutics. 307(3). 1045–1053. 4 indexed citations
16.
Haines, G. Kenneth, Stephen M. Becker, Ghanashyam D. Ghadge, et al.. (1993). Expression of the Double-Stranded RNA-Dependent Protein Kinase (p68) in Squamous Cell Carcinoma of the Head and Neck Region. Archives of Otolaryngology - Head and Neck Surgery. 119(10). 1142–1147. 24 indexed citations
17.
Haines, G. Kenneth, Ghanashyam D. Ghadge, Stephen M. Becker, et al.. (1993). Correlation of the expression of double-stranded RNA-dependent protein kinase (p68) with differentiation in head and neck squamous cell carcinoma. Virchows Archiv B Cell Pathology Including Molecular Pathology. 63(1). 289–295. 18 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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