Gerald E. Hall

808 total citations
16 papers, 458 citations indexed

About

Gerald E. Hall is a scholar working on Molecular Biology, Oncology and Biotechnology. According to data from OpenAlex, Gerald E. Hall has authored 16 papers receiving a total of 458 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 7 papers in Oncology and 5 papers in Biotechnology. Recurrent topics in Gerald E. Hall's work include Cancer Immunotherapy and Biomarkers (5 papers), Transgenic Plants and Applications (3 papers) and Plant tissue culture and regeneration (3 papers). Gerald E. Hall is often cited by papers focused on Cancer Immunotherapy and Biomarkers (5 papers), Transgenic Plants and Applications (3 papers) and Plant tissue culture and regeneration (3 papers). Gerald E. Hall collaborates with scholars based in United States and Belgium. Gerald E. Hall's co-authors include Steven Spiker, Ruslan D. Novosiadly, Ivan Inigo, A. H. M. van der Geest, David Schaer, Michael Kalos, Jason R. Manro, Timothy C. Hall, Xiaohong Xu and Gregory D. Plowman and has published in prestigious journals such as Journal of Clinical Oncology, PLoS ONE and The Plant Cell.

In The Last Decade

Gerald E. Hall

16 papers receiving 448 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gerald E. Hall United States	8	230	218	128	91	74	16	458
Louise M.E. Janssen Netherlands	5	139 0.6×	180 0.8×	144 1.1×	19 0.2×	17 0.2×	5	412
Bhavna Murali United States	7	147 0.6×	103 0.5×	61 0.5×	32 0.4×	16 0.2×	9	319
Marlese A. Pisegna United States	6	326 1.4×	103 0.5×	27 0.2×	48 0.5×	17 0.2×	7	426
Roberto Montes de Oca Luna Mexico	7	378 1.6×	293 1.3×	17 0.1×	99 1.1×	78 1.1×	12	466
Teerawit Supakorndej United States	5	318 1.4×	63 0.3×	63 0.5×	29 0.3×	22 0.3×	6	463
Chiara Secondini Switzerland	9	171 0.7×	200 0.9×	137 1.1×	13 0.1×	20 0.3×	9	434
Shaofang Wu United States	13	336 1.5×	178 0.8×	19 0.1×	27 0.3×	33 0.4×	21	459
Yujiro Naito Japan	10	126 0.5×	177 0.8×	138 1.1×	10 0.1×	22 0.3×	29	386
Elisabeth Emilsen Norway	10	280 1.2×	167 0.8×	60 0.5×	11 0.1×	17 0.2×	17	428
Jessica R. Adams Canada	8	327 1.4×	202 0.9×	35 0.3×	31 0.3×	11 0.1×	11	450

Countries citing papers authored by Gerald E. Hall

Since Specialization

Citations

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

Fields of papers citing papers by Gerald E. Hall

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gerald E. Hall

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

All Works

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16 of 16 papers shown

Li, Yanxia, Nelusha Amaladas, Jason R. Manro, et al.. (2022). Treatment with a VEGFR-2 antibody results in intra-tumor immune modulation and enhances anti-tumor efficacy of PD-L1 blockade in syngeneic murine tumor models. PLoS ONE. 17(7). e0268244–e0268244. 11 indexed citations

Chaudhary, Ritu, Robbert J.C. Slebos, Feifei Song, et al.. (2020). Effects of checkpoint kinase 1 inhibition by prexasertib on the tumor immune microenvironment of head and neck squamous cell carcinoma. Molecular Carcinogenesis. 60(2). 138–150. 16 indexed citations

Chaudhary, Ritu, Robbert J.C. Slebos, Feifei Song, et al.. (2020). Effects of prexasertib, a CHK1 inhibitor, in the immune microenvironment of head and neck squamous cell carcinoma (HNSCC).. Journal of Clinical Oncology. 38(15_suppl). e18541–e18541. 1 indexed citations

Holmgaard, Rikke, David Schaer, Yanxia Li, et al.. (2018). Targeting the TGFβ pathway with galunisertib, a TGFβRI small molecule inhibitor, promotes anti-tumor immunity leading to durable, complete responses, as monotherapy and in combination with checkpoint blockade. Journal for ImmunoTherapy of Cancer. 6(1). 47–47. 267 indexed citations

Novosiadly, Ruslan D., David Schaer, Nelusha Amaladas, et al.. (2018). Abstract 4549: Pemetrexed enhances anti-tumor efficacy of PD1 pathway blockade by promoting intra tumor immune response via immunogenic tumor cell death and T cell intrinsic mechanisms. Cancer Research. 78(13_Supplement). 4549–4549. 8 indexed citations

Forest, Amélie, David Schaer, Ting Chen, et al.. (2018). Abstract 3632: Combination of EGFR antibody with PD-1 pathway inhibitors improves anti-tumor efficacy and enhances intra-tumor immune response in preclinical mouse tumor models. Cancer Research. 78(13_Supplement). 3632–3632. 1 indexed citations

Melchior, Maxine, Xuemei Guo, Gregory P. Donoho, et al.. (2018). Abstract B108: Antitumor efficacy of EGFR antibody necitumumab and dual PI3K/mTOR inhibitor (LY3023414) in preclinical tumor models. Molecular Cancer Therapeutics. 17(1_Supplement). B108–B108. 1 indexed citations

Schaer, David, Yanxia Li, Stephen Castaneda, et al.. (2016). Abstract A091: Targeting the TGFb pathway with galunisertib, a TGFbRI SMI, promotes antitumor immunity leading to durable, complete responses, as monotherapy and in combination with checkpoint inhibition. Cancer Immunology Research. 4(1_Supplement). A091–A091. 1 indexed citations

Schaer, David, Yanxia Li, Stephen Castaneda, et al.. (2015). Targeting the TGFβ pathway with galunisertib, a TGFβRI SMI, promotes anti-tumor immunity leading to durable, complete responses, as monotherapy and in combination with checkpoint inhibition. Journal for ImmunoTherapy of Cancer. 3(Suppl 2). P402–P402. 1 indexed citations

10.

Michalowski, Susan, George C. Allen, Gerald E. Hall, William F. Thompson, & Steven Spiker. (1999). Characterization of Randomly-Obtained Matrix Attachment Regions (MARs) from Higher Plants^,. Biochemistry. 38(39). 12795–12804. 36 indexed citations

11.

Hall, Gerald E., et al.. (1996). High-Level Transgene Expression in Plant Cells: Effects of a Strong Scaffold Attachment Region from Tobacco. The Plant Cell. 8(5). 899–899. 20 indexed citations

12.

Geest, A. H. M. van der, Gerald E. Hall, Steven Spiker, & Timothy C. Hall. (1994). The β‐phaseolin gene is flanked by matrix attachment regions. The Plant Journal. 6(3). 413–423. 67 indexed citations

13.

Allen, George C., et al.. (1993). Scaffold Attachment Regions Increase Reporter Gene Expression in Stably Transformed Plant Cells. The Plant Cell. 5(6). 603–603. 19 indexed citations

14.

Ryan, Clarence A., Thomas D. Moloshok, Gregory Pearce, et al.. (1990). Engineering Proteinase Inihibitor Genes For Plant Defense Against Predators. UNI ScholarWorks (University of Northern Iowa). 97(1). 9–14. 2 indexed citations

15.

Ray, Arthur J., et al.. (1984). Retroreflector Field Tracker. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 501. 283–283. 2 indexed citations

16.

Hall, Gerald E., et al.. (1973). Architectural Study. Anatolian Studies. 23. 245–269. 5 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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