Matthew Page

852 total citations
12 papers, 179 citations indexed

About

Matthew Page is a scholar working on Molecular Biology, Dermatology and Computational Theory and Mathematics. According to data from OpenAlex, Matthew Page has authored 12 papers receiving a total of 179 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 2 papers in Dermatology and 2 papers in Computational Theory and Mathematics. Recurrent topics in Matthew Page's work include Computational Drug Discovery Methods (2 papers), Bioinformatics and Genomic Networks (2 papers) and Gene expression and cancer classification (2 papers). Matthew Page is often cited by papers focused on Computational Drug Discovery Methods (2 papers), Bioinformatics and Genomic Networks (2 papers) and Gene expression and cancer classification (2 papers). Matthew Page collaborates with scholars based in United Kingdom, Belgium and United States. Matthew Page's co-authors include Martin Armstrong, Johann de Jong, Holger Fröhlich, Ioana Cutcutache, Patrice Godard, Timothy Blackmore, Hannah B Edwards, Stevan Shaw, Kyoko Koshibu and Martin Hofmann‐Apitius and has published in prestigious journals such as Nature Communications, Brain and The Journal of Urology.

In The Last Decade

Matthew Page

10 papers receiving 177 citations

Peers

Matthew Page
Matthew Page
Citations per year, relative to Matthew Page Matthew Page (= 1×) peers Yuhua Zheng

Countries citing papers authored by Matthew Page

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Page

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Page

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

All Works

12 of 12 papers shown
1.
Aschenbrenner, Dominik, Isar Nassiri, Suresh Venkateswaran, et al.. (2024). An isoform quantitative trait locus in SBNO2 links genetic susceptibility to Crohn’s disease with defective antimicrobial activity. Nature Communications. 15(1). 4529–4529.
2.
Nejstgaard, Camilla Hansen, An‐Wen Chan, Kerry Dwan, et al.. (2024). A scoping review identifies comments suggesting modifications to PRISMA-P 2015. OSF Preprints (OSF Preprints).
3.
Rastrick, Joseph, et al.. (2024). The roles of interleukin (IL)-17A and IL-17F in hidradenitis suppurativa pathogenesis: evidence from human in vitro preclinical experiments and clinical samples. British Journal of Dermatology. 192(4). 660–671. 5 indexed citations
4.
Mann, Jake P., Satish Patel, Luis Carlos Tábara, et al.. (2023). A mouse model of human mitofusin-2-related lipodystrophy exhibits adipose-specific mitochondrial stress and reduced leptin secretion. eLife. 12. 3 indexed citations
6.
Jong, Johann de, et al.. (2021). Towards realizing the vision of precision medicine: AI based prediction of clinical drug response. Brain. 144(6). 1738–1750. 64 indexed citations
7.
Jong, Johann de, et al.. (2020). Towards Realizing the Vision of Precision Medicine: AI Based Prediction of Clinical Drug Response. SSRN Electronic Journal. 3 indexed citations
10.
Godard, Patrice & Matthew Page. (2016). PCAN: phenotype consensus analysis to support disease-gene association. BMC Bioinformatics. 17(1). 518–518. 16 indexed citations
11.
Page, Matthew, et al.. (2015). Procognitive Compounds Promote Neurite Outgrowth. Pharmacology. 96(3-4). 131–136. 14 indexed citations
12.
Adhikari, Subash, et al.. (2015). NeuroTransDB: highly curated and structured transcriptomic metadata for neurodegenerative diseases. Database. 2015. bav099–bav099. 14 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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