Gennifer D. Goode

1.9k total citations
9 papers, 381 citations indexed

About

Gennifer D. Goode is a scholar working on Cancer Research, Molecular Biology and Oncology. According to data from OpenAlex, Gennifer D. Goode has authored 9 papers receiving a total of 381 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Cancer Research, 5 papers in Molecular Biology and 3 papers in Oncology. Recurrent topics in Gennifer D. Goode's work include Cancer, Hypoxia, and Metabolism (6 papers), Effects and risks of endocrine disrupting chemicals (2 papers) and Cancer Research and Treatments (2 papers). Gennifer D. Goode is often cited by papers focused on Cancer, Hypoxia, and Metabolism (6 papers), Effects and risks of endocrine disrupting chemicals (2 papers) and Cancer Research and Treatments (2 papers). Gennifer D. Goode collaborates with scholars based in United States. Gennifer D. Goode's co-authors include Sakina E. Eltom, Venugopal Gunda, Pankaj K. Singh, Fang Yu, Enza Vernucci, Aneesha Dasgupta, Surendra K. Shukla, Ryan J. King, Nina V. Chaika and Jaime Abrego and has published in prestigious journals such as PLoS ONE, Cancer Research and Clinical Cancer Research.

In The Last Decade

Gennifer D. Goode

9 papers receiving 378 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gennifer D. Goode United States	7	232	167	115	41	38	9	381
Monserrat Olea‐Flores Mexico	11	272 1.2×	158 0.9×	148 1.3×	47 1.1×	29 0.8×	21	555
Amanda B. Parris United States	15	254 1.1×	96 0.6×	126 1.1×	51 1.2×	29 0.8×	22	409
Débora Kristina Alves-Fernandes Brazil	10	311 1.3×	95 0.6×	113 1.0×	25 0.6×	30 0.8×	14	544
Steven Rivera United States	9	198 0.9×	123 0.7×	77 0.7×	18 0.4×	74 1.9×	12	449
Zhi‐Tu Zhu China	13	281 1.2×	181 1.1×	121 1.1×	46 1.1×	15 0.4×	23	436
Brandie N. Radde United States	12	194 0.8×	79 0.5×	78 0.7×	45 1.1×	47 1.2×	12	395
Dede N. Ekoue United States	8	251 1.1×	105 0.6×	31 0.3×	60 1.5×	44 1.2×	15	453
Anthie Yiakouvaki United Kingdom	9	406 1.8×	113 0.7×	112 1.0×	39 1.0×	25 0.7×	9	615
Tomoko Muto Japan	12	295 1.3×	98 0.6×	96 0.8×	59 1.4×	81 2.1×	27	543
Mozhi Wang China	10	219 0.9×	194 1.2×	125 1.1×	41 1.0×	18 0.5×	24	395

Countries citing papers authored by Gennifer D. Goode

Since Specialization

Citations

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

Fields of papers citing papers by Gennifer D. Goode

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gennifer D. Goode. 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 Gennifer D. Goode. The network helps show where Gennifer D. Goode may publish in the future.

Co-authorship network of co-authors of Gennifer D. Goode

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

All Works

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9 of 9 papers shown

Murthy, Divya, Enza Vernucci, Gennifer D. Goode, Jaime Abrego, & Pankaj K. Singh. (2018). Evaluating the Metabolic Impact of Hypoxia on Pancreatic Cancer Cells. Methods in molecular biology. 1742. 81–93. 1 indexed citations

Gunda, Venugopal, Joshua J. Souchek, Jaime Abrego, et al.. (2017). MUC1-Mediated Metabolic Alterations Regulate Response to Radiotherapy in Pancreatic Cancer. Clinical Cancer Research. 23(19). 5881–5891. 74 indexed citations

Abrego, Jaime, Venugopal Gunda, Enza Vernucci, et al.. (2017). GOT1-mediated anaplerotic glutamine metabolism regulates chronic acidosis stress in pancreatic cancer cells. Cancer Letters. 400. 37–46. 76 indexed citations

Goode, Gennifer D., Venugopal Gunda, Nina V. Chaika, et al.. (2017). MUC1 facilitates metabolomic reprogramming in triple-negative breast cancer. PLoS ONE. 12(5). e0176820–e0176820. 32 indexed citations

Gunda, Venugopal, Joshua J. Souchek, Jaime Abrego, et al.. (2017). Abstract 459: Targeting MUC1 mediated nucleotide metabolism sensitizes pancreatic tumors to radiation therapy. Cancer Research. 77(13_Supplement). 459–459. 1 indexed citations

Shukla, Surendra K., Aneesha Dasgupta, Kamiya Mehla, et al.. (2015). Silibinin-mediated metabolic reprogramming attenuates pancreatic cancer-induced cachexia and tumor growth. Oncotarget. 6(38). 41146–41161. 69 indexed citations

Goode, Gennifer D., Siddharth Pratap, & Sakina E. Eltom. (2014). Depletion of the Aryl Hydrocarbon Receptor in MDA-MB-231 Human Breast Cancer Cells Altered the Expression of Genes in Key Regulatory Pathways of Cancer. PLoS ONE. 9(6). e100103–e100103. 29 indexed citations

Goode, Gennifer D., Billy R. Ballard, H. Charles Manning, et al.. (2013). Knockdown of aberrantly upregulated aryl hydrocarbon receptor reduces tumor growth and metastasis of MDA‐MB‐231 human breast cancer cell line. International Journal of Cancer. 133(12). 2769–2780. 55 indexed citations

Goode, Gennifer D., et al.. (2013). The Aryl Hydrocarbon Receptor: A Target for Breast Cancer Therapy. Journal of Cancer Therapy. 4(7). 1177–1186. 44 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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