Danielle Morrow

589 total citations · 1 hit paper
13 papers, 358 citations indexed

About

Danielle Morrow is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Cancer Research. According to data from OpenAlex, Danielle Morrow has authored 13 papers receiving a total of 358 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 5 papers in Cellular and Molecular Neuroscience and 4 papers in Cancer Research. Recurrent topics in Danielle Morrow's work include Neuroscience and Neuropharmacology Research (5 papers), Cancer, Hypoxia, and Metabolism (3 papers) and Cancer, Lipids, and Metabolism (3 papers). Danielle Morrow is often cited by papers focused on Neuroscience and Neuropharmacology Research (5 papers), Cancer, Hypoxia, and Metabolism (3 papers) and Cancer, Lipids, and Metabolism (3 papers). Danielle Morrow collaborates with scholars based in United States, United Kingdom and Brazil. Danielle Morrow's co-authors include Stephen J. Moss, Tarek Z. Deeb, David A. Nathanson, Todd K. O’Buckley, A. Leslie Morrow, Antoniette M. Maldonado‐Devincci, Anthony E. Jones, Steven J. Bensinger, Yasuko Nakamura and Timothy F. Cloughesy and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Neuroscience and Cancer Cell.

In The Last Decade

Danielle Morrow

13 papers receiving 356 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.

CDKN2A deletion remodels lipid metabolism to prime glioblastoma for ferroptosis

2023 102 citations Danielle Morrow, Nicholas Bayley et al. Cancer Cell profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Danielle Morrow United States	10	197	157	70	66	40	13	358
Taasin Srivastava United States	9	220 1.1×	218 1.4×	49 0.7×	40 0.6×	35 0.9×	10	475
E. Edwards United States	7	265 1.3×	60 0.4×	68 1.0×	62 0.9×	12 0.3×	8	460
Oleksii Nikolaienko Ukraine	14	374 1.9×	124 0.8×	88 1.3×	43 0.7×	40 1.0×	27	580
Mitsushi Ikemoto Japan	13	181 0.9×	125 0.8×	23 0.3×	37 0.6×	16 0.4×	28	380
Anandita Rajpurohit United States	8	444 2.3×	36 0.2×	114 1.6×	35 0.5×	56 1.4×	11	590
Angel Y.F. Kam United States	13	303 1.5×	253 1.6×	43 0.6×	13 0.2×	51 1.3×	19	487
Emilia Rejmak Poland	7	177 0.9×	156 1.0×	98 1.4×	8 0.1×	35 0.9×	13	402
Laurie R. Earls United States	9	376 1.9×	143 0.9×	93 1.3×	16 0.2×	31 0.8×	12	488
Marija Schwirtlich Serbia	13	282 1.4×	80 0.5×	63 0.9×	11 0.2×	15 0.4×	24	433
Geneviève Beaudry Canada	8	192 1.0×	217 1.4×	91 1.3×	45 0.7×	21 0.5×	9	439

Countries citing papers authored by Danielle Morrow

Since Specialization

Citations

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

Fields of papers citing papers by Danielle Morrow

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Danielle Morrow

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

All Works

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13 of 13 papers shown

Desousa, Brandon R., Kristen K.O. Kim, Anthony E. Jones, et al.. (2023). Calculation of ATP production rates using the Seahorse XF Analyzer. EMBO Reports. 24(10). e56380–e56380. 41 indexed citations

Morrow, Danielle, Nicholas Bayley, Elízabeth Fernández, et al.. (2023). TMET-12. CDKN2A DELETION REMODELS LIPID METABOLISM TO PRIME GLIOBLASTOMA FOR FERROPTOSIS. Neuro-Oncology. 25(Supplement_5). v275–v275. 1 indexed citations

Morrow, Danielle, Nicholas Bayley, Elízabeth Fernández, et al.. (2023). CDKN2A deletion remodels lipid metabolism to prime glioblastoma for ferroptosis. Cancer Cell. 41(6). 1048–1060.e9. 102 indexed citations breakdown →

Cho, Nicholas S., Akifumi Hagiwara, Jingwen Yao, et al.. (2022). Amine‐weighted chemical exchange saturation transfer magnetic resonance imaging in brain tumors. NMR in Biomedicine. 36(6). e4785–e4785. 9 indexed citations

Morrow, Danielle, et al.. (2021). Metabolic Vulnerabilities in Brain Cancer. Neurosurgery Clinics of North America. 32(2). 159–169. 5 indexed citations

Hagiwara, Akifumi, Jingwen Yao, Catalina Raymond, et al.. (2021). “Aerobic glycolytic imaging” of human gliomas using combined pH-, oxygen-, and perfusion-weighted magnetic resonance imaging. NeuroImage Clinical. 32. 102882–102882. 8 indexed citations

Nakamura, Yasuko, et al.. (2020). Phosphorylation on Ser-359 of the α2 subunit in GABA type A receptors down-regulates their density at inhibitory synapses. Journal of Biological Chemistry. 295(35). 12330–12342. 9 indexed citations

Nakamura, Yasuko, Danielle Morrow, Amit Modgil, et al.. (2016). Proteomic Characterization of Inhibitory Synapses Using a Novel pHluorin-tagged γ-Aminobutyric Acid Receptor, Type A (GABAA), α2 Subunit Knock-in Mouse. Journal of Biological Chemistry. 291(23). 12394–12407. 43 indexed citations

Maldonado‐Devincci, Antoniette M., et al.. (2016). Chronic Intermittent Ethanol Exposure Alters Stress Effects on (3α,5α)-3-hydroxy-pregnan-20-one (3α,5α-THP) Immunolabeling of Amygdala Neurons in C57BL/6J Mice. Frontiers in Cellular Neuroscience. 10. 40–40. 13 indexed citations

10.

Sivakumaran, Sudhir, Ross A. Cardarelli, Jamie Maguire, et al.. (2015). Selective Inhibition of KCC2 Leads to Hyperexcitability and Epileptiform Discharges in Hippocampal Slices andIn Vivo. Journal of Neuroscience. 35(21). 8291–8296. 77 indexed citations

11.

Maldonado‐Devincci, Antoniette M., Todd K. O’Buckley, Danielle Morrow, et al.. (2014). Chronic Intermittent Ethanol Exposure and Withdrawal Alters (3α,5α)‐3‐Hydroxy‐Pregnan‐20‐One Immunostaining in Cortical and Limbic Brain Regions ofC57BL/6JMice. Alcoholism Clinical and Experimental Research. 38(10). 2561–2571. 29 indexed citations

12.

Nelli, Stephanie, et al.. (2014). Ethanol Alters Local Cellular Levels of (3α,5α)-3-Hydroxypregnan-20-one (3α,5α-THP) Independent of the Adrenals in Subcortical Brain Regions. Neuropsychopharmacology. 39(8). 1978–1987. 11 indexed citations

13.

Maldonado‐Devincci, Antoniette M., et al.. (2014). Reduction of circulating and selective limbic brain levels of (3α,5α)-3-hydroxy-pregnan-20-one (3α,5α-THP) following forced swim stress in C57BL/6J mice. Psychopharmacology. 231(17). 3281–3292. 10 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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