Deborah E. Geiman

3.5k total citations · 1 hit paper
25 papers, 2.9k citations indexed

About

Deborah E. Geiman is a scholar working on Molecular Biology, Epidemiology and Infectious Diseases. According to data from OpenAlex, Deborah E. Geiman has authored 25 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 12 papers in Epidemiology and 7 papers in Infectious Diseases. Recurrent topics in Deborah E. Geiman's work include Mycobacterium research and diagnosis (8 papers), Tuberculosis Research and Epidemiology (7 papers) and Adipose Tissue and Metabolism (4 papers). Deborah E. Geiman is often cited by papers focused on Mycobacterium research and diagnosis (8 papers), Tuberculosis Research and Epidemiology (7 papers) and Adipose Tissue and Metabolism (4 papers). Deborah E. Geiman collaborates with scholars based in United States, Netherlands and Israel. Deborah E. Geiman's co-authors include M. Daniel Lane, Robert J. Christy, Vincent W. Yang, Klaus H. Kaestner, William R. Bishai, Yusaku Nakabeppu, Alan D. Friedman, William Landschulz, James M. Ntambi and Thomas J. Kelly and has published in prestigious journals such as New England Journal of Medicine, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Deborah E. Geiman

25 papers receiving 2.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Differentiation-induced gene expression in 3T3-L1 preadipocytes: CCAAT/enhancer binding protein interacts with and activates the promoters of two adipocyte-specific genes.

1989 531 citations Robert J. Christy, Vincent W. Yang et al. Genes & Development profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Deborah E. Geiman United States	17	1.7k	775	525	500	469	25	2.9k
Sei Yoshida Japan	23	1.1k 0.7×	566 0.7×	333 0.6×	368 0.7×	152 0.3×	41	2.6k
Atsuhito Yagihashi Japan	29	1.5k 0.8×	347 0.4×	280 0.5×	291 0.6×	191 0.4×	78	2.9k
Brian K. Dieckgraefe United States	33	1.4k 0.8×	572 0.7×	914 1.7×	137 0.3×	184 0.4×	64	3.4k
Sumio Watanabe Japan	22	1.1k 0.6×	677 0.9×	166 0.3×	175 0.3×	235 0.5×	85	2.5k
Neelam Sharma-Walia United States	31	1.2k 0.7×	1.0k 1.3×	201 0.4×	229 0.5×	233 0.5×	51	3.1k
Keun Il Kim South Korea	41	3.1k 1.8×	836 1.1×	398 0.8×	268 0.5×	148 0.3×	86	5.2k
Thomas Sternsdorf Germany	23	1.7k 1.0×	577 0.7×	492 0.9×	121 0.2×	130 0.3×	31	3.2k
Ariel Werman United States	11	1.2k 0.7×	429 0.6×	311 0.6×	548 1.1×	126 0.3×	14	2.0k
Shanchun Guo United States	24	1.4k 0.8×	390 0.5×	341 0.6×	214 0.4×	185 0.4×	78	3.1k
William L. McPheat United Kingdom	21	1.2k 0.7×	568 0.7×	155 0.3×	340 0.7×	126 0.3×	39	2.4k

Countries citing papers authored by Deborah E. Geiman

Since Specialization

Citations

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

Fields of papers citing papers by Deborah E. Geiman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Deborah E. Geiman. 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 Deborah E. Geiman. The network helps show where Deborah E. Geiman may publish in the future.

Co-authorship network of co-authors of Deborah E. Geiman

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

All Works

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20 of 20 papers shown

Lee, Jong‐Hee, Nicole C. Ammerman, Scott T. Nolan, et al.. (2012). Isoniazid resistance without a loss of fitness in Mycobacterium tuberculosis. Nature Communications. 3(1). 753–753. 29 indexed citations

Parthasarathy, Geetha, Shichun Lun, Haidan Guo, et al.. (2012). Rv2190c, an NlpC/P60 Family Protein, Is Required for Full Virulence of Mycobacterium tuberculosis. PLoS ONE. 7(8). e43429–e43429. 29 indexed citations

Converse, Paul J., Kathleen D. Eisenach, Sue A. Theus, et al.. (2010). The Impact of Mouse Passaging of Mycobacterium tuberculosis Strains prior to Virulence Testing in the Mouse and Guinea Pig Aerosol Models. PLoS ONE. 5(4). e10289–e10289. 12 indexed citations

Ly, Lan H., et al.. (2008). Altered cellular infiltration and cytokine levels during early Mycobacterium tuberculosis sigC mutant infection are associated with late-stage disease attenuation and milder immunopathology in mice. BMC Microbiology. 8(1). 151–151. 16 indexed citations

Lee, Jong‐Hee, Deborah E. Geiman, & William R. Bishai. (2007). Role of Stress Response Sigma Factor SigG in Mycobacterium tuberculosis. Journal of Bacteriology. 190(3). 1128–1133. 41 indexed citations

Giardiello, Francis M., Robert A. Casero, Stanley R. Hamilton, et al.. (2004). Prostanoids, ornithine decarboxylase, and polyamines in primary chemoprevention of familial adenomatous polyposis. Gastroenterology. 126(2). 425–431. 44 indexed citations

Lamichhane, Gyanu, Matteo Zignol, Natalie J. Blades, et al.. (2003). A postgenomic method for predicting essential genes at subsaturation levels of mutagenesis: Application to Mycobacterium tuberculosis. Proceedings of the National Academy of Sciences. 100(12). 7213–7218. 280 indexed citations

Giardiello, Francis M., Vincent W. Yang, Linda M. Hylind, et al.. (2002). Primary Chemoprevention of Familial Adenomatous Polyposis with Sulindac. New England Journal of Medicine. 346(14). 1054–1059. 272 indexed citations

Chen, Xinming, David C. Johns, Deborah E. Geiman, et al.. (2001). Krüppel-like Factor 4 (Gut-enriched Krüppel-like Factor) Inhibits Cell Proliferation by Blocking G1/S Progression of the Cell Cycle. Journal of Biological Chemistry. 276(32). 30423–30428. 212 indexed citations

10.

Yang, Vincent W., Deborah E. Geiman, Walter C. Hubbard, et al.. (2000). Tissue prostanoids as biomarkers for chemoprevention of colorectal neoplasia: correlation between prostanoid synthesis and clinical response in familial adenomatous polyposis. Prostaglandins & Other Lipid Mediators. 60(1-3). 83–96. 16 indexed citations

11.

Geiman, Deborah E.. (2000). Transactivation and growth suppression by the gut-enriched Kruppel-like factor (Kruppel-like factor 4) are dependent on acidic amino acid residues and protein-protein interaction. Nucleic Acids Research. 28(5). 1106–1113. 106 indexed citations

12.

Zhang, Weiqing, Deborah E. Geiman, Janiel M. Shields, et al.. (2000). The Gut-enriched Krüppel-like Factor (Krüppel-like Factor 4) Mediates the Transactivating Effect of p53 on the p21 Promoter. Journal of Biological Chemistry. 275(24). 18391–18398. 285 indexed citations

13.

Christy, Robert J., Klaus H. Kaestner, Deborah E. Geiman, & M. Daniel Lane. (1991). CCAAT/enhancer binding protein gene promoter: binding of nuclear factors during differentiation of 3T3-L1 preadipocytes.. Proceedings of the National Academy of Sciences. 88(6). 2593–2597. 344 indexed citations

14.

Christy, Robert J., Vincent W. Yang, James M. Ntambi, et al.. (1989). Differentiation-induced gene expression in 3T3-L1 preadipocytes: CCAAT/enhancer binding protein interacts with and activates the promoters of two adipocyte-specific genes.. Genes & Development. 3(9). 1323–1335. 531 indexed citations breakdown →

15.

Chua, Chu Chang, Denis Barritault, Deborah E. Geiman, & Roger L. Ladda. (1987). Induction and Suppression of Type I Collagenase in Cultured Human Cells. Collagen and Related Research. 7(4). 277–284. 8 indexed citations

16.

Chua, Chu Chang, Deborah E. Geiman, & Roger L. Ladda. (1986). Receptor for epidermal growth factor retains normal structure and function in aging cells. Mechanisms of Ageing and Development. 34(1). 35–55. 18 indexed citations

17.

Chua, Chu Chang, Deborah E. Geiman, George H. Keller, & Roger L. Ladda. (1985). 250 INDUCTION OF COLLAGENASE SECRETION IN HUMAN FIBROBLAST CULTURES BY GROWTH PROMOTING FACTORS. Pediatric Research. 19(4). 152A–152A. 2 indexed citations

18.

Chua, Chu Chang, Deborah E. Geiman, Alain B. Schreiber, & Roger L. Ladda. (1984). Nonfunctional epidermal growth factor receptor in cells transformed by Kirsten sarcoma virus. Biochemical and Biophysical Research Communications. 118(2). 538–547. 8 indexed citations

19.

Chua, Chu Chang, Deborah E. Geiman, & Roger L. Ladda. (1983). Transforming growth factors released from Kirsten sarcoma virus transformed cells do not compete for epidermal growth factor membrane receptors. Journal of Cellular Physiology. 117(1). 116–122. 13 indexed citations

20.

Chua, Chu Chang, Deborah E. Geiman, & Roger L. Ladda. (1983). Detection of an Mr 200,000 glycoprotein in the culture medium of skin fibroblasts from patients with Huntington disease. Biochemical and Biophysical Research Communications. 111(2). 690–699. 1 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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