Glyn Bradley

647 total citations
10 papers, 339 citations indexed

About

Glyn Bradley is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Immunology. According to data from OpenAlex, Glyn Bradley has authored 10 papers receiving a total of 339 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Pulmonary and Respiratory Medicine and 3 papers in Immunology. Recurrent topics in Glyn Bradley's work include Bioinformatics and Genomic Networks (5 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (2 papers) and Biomedical Text Mining and Ontologies (2 papers). Glyn Bradley is often cited by papers focused on Bioinformatics and Genomic Networks (5 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (2 papers) and Biomedical Text Mining and Ontologies (2 papers). Glyn Bradley collaborates with scholars based in United Kingdom, Switzerland and Russia. Glyn Bradley's co-authors include Edith M. Hessel, Alison M. Condliffe, Mark Lennon, Edwin R. Chilvers, Malcolm Begg, Jürgen Herre, Augustin Amour, David House, Charlotte Summers and Jatinder K. Juss and has published in prestigious journals such as The Lancet, Nature Communications and Nature Genetics.

In The Last Decade

Glyn Bradley

10 papers receiving 335 citations

Peers

Glyn Bradley

MB

IMMUN

PRM

EPIDE

CTM

Sanju Sinha United States

Douglas K. Brubaker United States

Zinnia P. Parra‐Guillén Spain

Matthew Cannon United States

Andrei Todor United States

Anat Klein Israel

Fredrik Barrenäs Sweden

Jinli Wei China

Zhaonian Hao China

Siôn L. Williams United States

Sanju Sinha United States

Glyn Bradley

259 ×1.7

MB

45 ×0.4

IMMUN

59 ×0.7

PRM

34 ×0.7

EPIDE

26 ×0.7

CTM

Citations per year, relative to Glyn Bradley Glyn Bradley (= 1×) peers Sanju Sinha

Countries citing papers authored by Glyn Bradley

Since Specialization

Citations

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

Fields of papers citing papers by Glyn Bradley

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Glyn Bradley

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

All Works

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10 of 10 papers shown

1.

Oostrum, Marc van, Danish Memon, Fabian Frommelt, et al.. (2025). A tissue-specific atlas of protein–protein associations enables prioritization of candidate disease genes. Nature Biotechnology. 4 indexed citations

2.

Barrio‐Hernandez, Inigo, Jeremy Schwartzentruber, Anjali Shrivastava, et al.. (2023). Network expansion of genetic associations defines a pleiotropy map of human cell biology. Nature Genetics. 55(3). 389–398. 42 indexed citations

3.

Perfetto, Livia, Márcio Luís Acencio, Glyn Bradley, et al.. (2019). CausalTAB: the PSI-MITAB 2.8 updated format for signalling data representation and dissemination. Bioinformatics. 35(19). 3779–3785. 20 indexed citations

4.

Begg, Malcolm, Anthony Cahn, Neda Farahi, et al.. (2019). Use of autologous ^99m Technetium-labelled neutrophils to quantify lung neutrophil clearance in COPD. Thorax. 74(7). 659–666. 19 indexed citations

5.

Stark, Anne‐Katrien, Anita Chandra, Krishnendu Chakraborty, et al.. (2018). PI3Kδ hyper-activation promotes development of B cells that exacerbate Streptococcus pneumoniae infection in an antibody-independent manner. Nature Communications. 9(1). 3174–3174. 55 indexed citations

6.

Bradley, Glyn, et al.. (2017). CausalR: extracting mechanistic sense from genome scale data. Bioinformatics. 33(22). 3670–3672. 20 indexed citations

7.

Juss, Jatinder K., David House, Augustin Amour, et al.. (2016). Acute Respiratory Distress Syndrome Neutrophils Have a Distinct Phenotype and Are Resistant to Phosphoinositide 3-Kinase Inhibition. American Journal of Respiratory and Critical Care Medicine. 194(8). 961–973. 97 indexed citations

8.

Herre, Jürgen, Malcolm Begg, Glyn Bradley, et al.. (2015). Genome-wide transcription profiling in neutrophils in acute respiratory distress syndrome. The Lancet. 385. S55–S55. 19 indexed citations

9.

Ratnam, Joseline, Barbara Zdrazil, Daniela Digles, et al.. (2014). The Application of the Open Pharmacological Concepts Triple Store (Open PHACTS) to Support Drug Discovery Research. PLoS ONE. 9(12). e115460–e115460. 23 indexed citations

10.

Menche, Jörg, Amitabh Sharma, Michael H. Cho, et al.. (2014). A diVIsive Shuffling Approach (VIStA) for gene expression analysis to identify subtypes in Chronic Obstructive Pulmonary Disease. BMC Systems Biology. 8(S2). S8–S8. 40 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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