Christopher J. Morrow

3.7k total citations
47 papers, 1.7k citations indexed

About

Christopher J. Morrow is a scholar working on Molecular Biology, Oncology and Genetics. According to data from OpenAlex, Christopher J. Morrow has authored 47 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 11 papers in Oncology and 11 papers in Genetics. Recurrent topics in Christopher J. Morrow's work include Estrogen and related hormone effects (10 papers), Advanced Breast Cancer Therapies (6 papers) and PI3K/AKT/mTOR signaling in cancer (5 papers). Christopher J. Morrow is often cited by papers focused on Estrogen and related hormone effects (10 papers), Advanced Breast Cancer Therapies (6 papers) and PI3K/AKT/mTOR signaling in cancer (5 papers). Christopher J. Morrow collaborates with scholars based in United Kingdom, United States and Australia. Christopher J. Morrow's co-authors include Caroline Dive, Stephen S. Taylor, Cassandra L. Hodgkinson, Fiona Blackhall, Sarah Elderkin, Deema Hussein, Yunmei Wang, Lynsey Priest, Anthony Tighe and Victoria Johnson and has published in prestigious journals such as Journal of Clinical Investigation, Nature Medicine and Journal of Clinical Oncology.

In The Last Decade

Christopher J. Morrow

42 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Christopher J. Morrow United Kingdom 19 976 652 568 326 292 47 1.7k
Manuela Vecchi Italy 27 1.5k 1.5× 1.0k 1.6× 531 0.9× 351 1.1× 260 0.9× 42 2.6k
Sean G. Buchanan United States 20 1.0k 1.0× 605 0.9× 146 0.3× 128 0.4× 380 1.3× 47 1.8k
Mikhail A. Nikiforov United States 30 2.1k 2.1× 580 0.9× 486 0.9× 376 1.2× 96 0.3× 69 2.8k
Karen Crasta Singapore 15 1.2k 1.2× 270 0.4× 319 0.6× 547 1.7× 51 0.2× 25 1.6k
Giuseppe Roscilli Italy 25 1.1k 1.1× 573 0.9× 367 0.6× 118 0.4× 173 0.6× 48 1.8k
Andrew P. VanDemark United States 23 1.7k 1.7× 188 0.3× 193 0.3× 224 0.7× 148 0.5× 42 2.0k
Maurice C. Owen New Zealand 16 779 0.8× 371 0.6× 820 1.4× 243 0.7× 144 0.5× 33 1.7k
Wun‐Shaing Wayne Chang Taiwan 19 603 0.6× 376 0.6× 704 1.2× 232 0.7× 147 0.5× 34 1.4k
M. Brett Waddell United States 15 1.3k 1.3× 480 0.7× 165 0.3× 210 0.6× 92 0.3× 23 1.7k
Florian Grebien Austria 25 1.3k 1.3× 450 0.7× 195 0.3× 147 0.5× 107 0.4× 62 2.4k

Countries citing papers authored by Christopher J. Morrow

Since Specialization
Citations

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

Fields of papers citing papers by Christopher J. Morrow

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Christopher J. Morrow

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

All Works

20 of 20 papers shown
1.
Heintz, Caroline, Ayse Sena Mutlu, Mary Piper, et al.. (2025). The efficacy of longevity interventions in Caenorhabditis elegans is determined by the early life activity of RNA splicing factors. PLoS Biology. 23(11). e3003504–e3003504.
2.
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Gaitatzis, Athanasios, et al.. (2025). Multimorbidity in adults with epilepsy attending an outpatient epilepsy clinic. Epilepsy & Behavior. 172. 110547–110547.
4.
Morrow, Christopher J., Jared T. Hinkle, Kate Perepezko, et al.. (2024). Impact of Acute Dopamine Replacement on Cognitive Function in Parkinson's Disease. Movement Disorders Clinical Practice. 11(5). 534–542. 6 indexed citations
5.
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Harrod, Alison, Chun‐Fui Lai, Daniela Barsotti Santos, et al.. (2022). Genome engineering for estrogen receptor mutations reveals differential responses to anti-estrogens and new prognostic gene signatures for breast cancer. Oncogene. 41(44). 4905–4915. 17 indexed citations
7.
Wehmann, Enikő, et al.. (2021). Novel prophage-like sequences in Mycoplasma anserisalpingitidis. Infection Genetics and Evolution. 92. 104886–104886. 4 indexed citations
8.
Gyuranecz, Miklós, et al.. (2020). Isolation of Mycoplasma anserisalpingitidis from swan goose (Anser cygnoides) in China. BMC Veterinary Research. 16(1). 178–178. 14 indexed citations
9.
Toy, Weiyi, Hazel M. Weir, Pedram Razavi, et al.. (2016). Activating ESR1 Mutations Differentially Affect the Efficacy of ER Antagonists. Cancer Discovery. 7(3). 277–287. 269 indexed citations
10.
Galvin, Melanie, Alice Lallo, Cassandra L. Hodgkinson, et al.. (2016). Inhibition of PI3K/BMX Cell Survival Pathway Sensitizes to BH3 Mimetics in SCLC. Molecular Cancer Therapeutics. 15(6). 1248–1260. 26 indexed citations
11.
Carter, Louise, Dominic G. Rothwell, Bárbara Mesquita, et al.. (2016). Molecular analysis of circulating tumor cells identifies distinct copy-number profiles in patients with chemosensitive and chemorefractory small-cell lung cancer. Nature Medicine. 23(1). 114–119. 239 indexed citations
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Polański, Radosław, Cassandra L. Hodgkinson, Alberto Fusi, et al.. (2013). Activity of the Monocarboxylate Transporter 1 Inhibitor AZD3965 in Small Cell Lung Cancer. Clinical Cancer Research. 20(4). 926–937. 282 indexed citations
14.
Cawthorne, Christopher, Natalie Burrows, Roben G. Gieling, et al.. (2013). [18F]-FLT Positron Emission Tomography Can Be Used to Image the Response of Sensitive Tumors to PI3-Kinase Inhibition with the Novel Agent GDC-0941. Molecular Cancer Therapeutics. 12(5). 819–828. 12 indexed citations
15.
Klymenko, Tetyana, et al.. (2011). The Novel Bcl-2 Inhibitor ABT-737 Is More Effective in Hypoxia and Is Able to Reverse Hypoxia-Induced Drug Resistance in Neuroblastoma Cells. Molecular Cancer Therapeutics. 10(12). 2373–2383. 26 indexed citations
16.
Micha, Dimitra, Kathryn Simpson, Christopher J. Morrow, et al.. (2011). Hypoxic human cancer cells are sensitized to BH-3 mimetic–induced apoptosis via downregulation of the Bcl-2 protein Mcl-1. Journal of Clinical Investigation. 121(3). 1075–1087. 48 indexed citations
17.
Morrow, Christopher J., Mohammad A. Ghattas, Christopher G. Smith, et al.. (2010). Src Family Kinase Inhibitor Saracatinib (AZD0530) Impairs Oxaliplatin Uptake in Colorectal Cancer Cells and Blocks Organic Cation Transporters. Cancer Research. 70(14). 5931–5941. 24 indexed citations
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Morrow, Christopher J., et al.. (2005). Bub1 and aurora B cooperate to maintain BubR1-mediated inhibition of APC/CCdc20. Journal of Cell Science. 118(16). 3639–3652. 145 indexed citations
20.
Morrow, Christopher J., Alexander Gray, & Caroline Dive. (2005). Comparison of phosphatidylinositol‐3‐kinase signalling within a panel of human colorectal cancer cell lines with mutant or wild‐type PIK3CA. FEBS Letters. 579(23). 5123–5128. 26 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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