James A. Heward

1.8k total citations · 1 hit paper
21 papers, 1.0k citations indexed

About

James A. Heward is a scholar working on Molecular Biology, Cancer Research and Pathology and Forensic Medicine. According to data from OpenAlex, James A. Heward has authored 21 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 8 papers in Cancer Research and 5 papers in Pathology and Forensic Medicine. Recurrent topics in James A. Heward's work include Cancer-related molecular mechanisms research (6 papers), Lymphoma Diagnosis and Treatment (5 papers) and Epigenetics and DNA Methylation (3 papers). James A. Heward is often cited by papers focused on Cancer-related molecular mechanisms research (6 papers), Lymphoma Diagnosis and Treatment (5 papers) and Epigenetics and DNA Methylation (3 papers). James A. Heward collaborates with scholars based in United Kingdom, United States and Australia. James A. Heward's co-authors include Mark A. Lindsay, Benoît Roux, Louise Donnelly, Simon W. Jones, David Sims, Ian Goodhead, Nicholas E. Ilott, Luca Lenzi, Neil Hall and Peter Fenwick and has published in prestigious journals such as Nature Communications, The Journal of Experimental Medicine and Cancer Research.

In The Last Decade

James A. Heward

19 papers receiving 1.0k citations

Hit Papers

Correction: Corrigendum: Long non-coding RNAs and enhance... 2015 2026 2018 2022 2015 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
James A. Heward United Kingdom 11 532 523 142 98 90 21 1.0k
Eleni Tsitsiou United Kingdom 11 664 1.2× 677 1.3× 222 1.6× 66 0.7× 90 1.0× 11 1.4k
Zhuqing Wang China 18 935 1.8× 404 0.8× 103 0.7× 27 0.3× 39 0.4× 56 1.5k
Guobing Wang China 17 298 0.6× 153 0.3× 105 0.7× 31 0.3× 52 0.6× 92 880
José Ignacio Arias Spain 19 381 0.7× 247 0.5× 114 0.8× 27 0.3× 89 1.0× 80 1.2k
Jinliang Ma China 18 413 0.8× 220 0.4× 103 0.7× 35 0.4× 114 1.3× 60 926
Paige Martin United States 13 798 1.5× 474 0.9× 66 0.5× 18 0.2× 39 0.4× 30 1.3k
Diana J. Laird United States 18 1.2k 2.2× 101 0.2× 208 1.5× 54 0.6× 39 0.4× 44 1.9k
Shu Yang China 24 747 1.4× 474 0.9× 119 0.8× 25 0.3× 83 0.9× 77 1.6k
Anna Fagotti Italy 25 390 0.7× 161 0.3× 122 0.9× 21 0.2× 94 1.0× 136 1.9k
Maria Antonietta Di Bella Italy 13 892 1.7× 448 0.9× 162 1.1× 12 0.1× 30 0.3× 26 1.4k

Countries citing papers authored by James A. Heward

Since Specialization
Citations

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

Fields of papers citing papers by James A. Heward

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James A. Heward. 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 James A. Heward. The network helps show where James A. Heward may publish in the future.

Co-authorship network of co-authors of James A. Heward

This figure shows the co-authorship network connecting the top 25 collaborators of James A. Heward. A scholar is included among the top collaborators of James A. Heward 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 James A. Heward. James A. Heward 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.
Kumar, Emil, Koorosh Korfi, Findlay Bewicke‐Copley, et al.. (2024). CREBBP histone acetyltransferase domain mutations predict response to mTOR inhibition in relapsed/refractory follicular lymphoma. British Journal of Haematology. 205(5). 1804–1809. 1 indexed citations
2.
Wang, Shenqiu, S. Parsa, Man Jiang, et al.. (2024). SETD1B mutations confer apoptosis resistance and BCL2 independence in B cell lymphoma. The Journal of Experimental Medicine. 221(10). 5 indexed citations
3.
Carter, Edward, et al.. (2023). HDAC Inhibition Restores Response to HER2-Targeted Therapy in Breast Cancer via PHLDA1 Induction. International Journal of Molecular Sciences. 24(7). 6228–6228. 5 indexed citations
5.
Carter, Edward, James A. Heward, Saadia A. Karim, et al.. (2022). Nuclear FGFR1 promotes pancreatic stellate cell-driven invasion through up-regulation of Neuregulin 1. Oncogene. 42(7). 491–500. 13 indexed citations
6.
Heward, James A., Annalisa D’Avola, Alison Yeomans, et al.. (2019). S844 KDM5 INHIBITION OFFERS A NOVEL THERAPEUTIC STRATEGY FOR THE TREATMENT OF KMT2D MUTANT LYMPHOMAS. HemaSphere. 3(S1). 376–377. 1 indexed citations
7.
Heward, James A., Emil Kumar, Koorosh Korfi, Jessica Okosun, & Jude Fitzgibbon. (2018). Precision medicine and lymphoma. Current Opinion in Hematology. 25(4). 329–334. 6 indexed citations
8.
Hamann, Philip, Benoît Roux, James A. Heward, et al.. (2017). Transcriptional profiling identifies differential expression of long non-coding RNAs in Jo-1 associated and inclusion body myositis. Scientific Reports. 7(1). 8024–8024. 31 indexed citations
9.
Roux, Benoît, James A. Heward, Louise Donnelly, Simon W. Jones, & Mark A. Lindsay. (2017). Catalog of Differentially Expressed Long Non-Coding RNA following Activation of Human and Mouse Innate Immune Response. Frontiers in Immunology. 8. 1038–1038. 45 indexed citations
10.
Wang, Jun, Eleni Maniati, James A. Heward, et al.. (2016). Reduced Expression of Histone Methyltransferases KMT2C and KMT2D Correlates with Improved Outcome in Pancreatic Ductal Adenocarcinoma. Cancer Research. 76(16). 4861–4871. 72 indexed citations
11.
Roux, Benoît, Mark A. Lindsay, & James A. Heward. (2016). Knockdown of Nuclear-Located Enhancer RNAs and Long ncRNAs Using Locked Nucleic Acid GapmeRs. Methods in molecular biology. 1468. 11–18. 15 indexed citations
12.
Ilott, Nicholas E., James A. Heward, Benoît Roux, et al.. (2015). Correction: Corrigendum: Long non-coding RNAs and enhancer RNAs regulate the lipopolysaccharide-induced inflammatory response in human monocytes. Nature Communications. 6(1). 322 indexed citations breakdown →
13.
Pearson, Mark, Ashleigh M. Philp, James A. Heward, et al.. (2015). Long Intergenic Noncoding RNAs Mediate the Human Chondrocyte Inflammatory Response and Are Differentially Expressed in Osteoarthritis Cartilage. Arthritis & Rheumatology. 68(4). 845–856. 107 indexed citations
14.
Araf, Shamzah, et al.. (2015). Epigenetic Dysregulation in Follicular Lymphoma. Epigenomics. 8(1). 77–84. 11 indexed citations
15.
Heward, James A., et al.. (2014). Long non-coding RNAs and enhancer RNAs regulate the lipopolysaccharide-induced inflammatory response in human monocytes. Immunology. 143. 110–110. 1 indexed citations
16.
Heward, James A. & Mark A. Lindsay. (2014). Long non-coding RNAs in the regulation of the immune response. Trends in Immunology. 35(9). 408–419. 335 indexed citations
17.
Heward, James A., Benoît Roux, & Mark A. Lindsay. (2014). Divergent signalling pathways regulate lipopolysaccharide‐induced eRNA expression in human monocytic THP1 cells. FEBS Letters. 589(3). 396–406. 15 indexed citations
18.
Crook, Paul, et al.. (2008). Identifying semi-Invariant Features on Mouse Contours. 84.1–84.10. 2 indexed citations
19.
Armstrong, J. Douglas, et al.. (2005). Sex, Flies and no Videotape.
20.
Heward, James A., et al.. (2005). FlyTracker: Real-time analysis of insect courtship.

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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