Daniel J. Smıth

35.5k total citations · 5 hit papers
346 papers, 12.4k citations indexed

About

Daniel J. Smıth is a scholar working on Psychiatry and Mental health, Genetics and Physiology. According to data from OpenAlex, Daniel J. Smıth has authored 346 papers receiving a total of 12.4k indexed citations (citations by other indexed papers that have themselves been cited), including 113 papers in Psychiatry and Mental health, 54 papers in Genetics and 50 papers in Physiology. Recurrent topics in Daniel J. Smıth's work include Bipolar Disorder and Treatment (75 papers), Schizophrenia research and treatment (45 papers) and Genetic Associations and Epidemiology (34 papers). Daniel J. Smıth is often cited by papers focused on Bipolar Disorder and Treatment (75 papers), Schizophrenia research and treatment (45 papers) and Genetic Associations and Epidemiology (34 papers). Daniel J. Smıth collaborates with scholars based in United Kingdom, United States and Sweden. Daniel J. Smıth's co-authors include Martin A. Taubman, Jill P. Pell, Joey Ward, Breda Cullen, Daniel Mackay, Douglas Blackwood, Stewart W Mercer, Donald M. Lyall, Gary McLean and Walter Muir and has published in prestigious journals such as Science, The Lancet and Journal of Clinical Investigation.

In The Last Decade

Daniel J. Smıth

331 papers receiving 11.9k citations

Hit Papers

The 2006 California Heat ... 2008 2026 2014 2020 2008 2019 2018 2018 2025 100 200 300 400 500

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Daniel J. Smıth 2.9k 1.7k 1.7k 1.5k 1.4k 346 12.4k
Hans Helenius 2.2k 0.8× 4.0k 2.3× 1.5k 0.9× 2.3k 1.5× 1.7k 1.2× 341 16.7k
Jari Haukka 4.1k 1.4× 2.8k 1.6× 943 0.6× 1.2k 0.8× 838 0.6× 321 12.1k
Henry Völzke 1.1k 0.4× 1.3k 0.8× 3.2k 1.9× 1.9k 1.2× 3.8k 2.7× 791 22.3k
Leiv Sandvik 1.2k 0.4× 1.1k 0.7× 2.0k 1.2× 1.5k 1.0× 1.8k 1.3× 431 19.0k
Rebecca Hardy 1.7k 0.6× 1.6k 0.9× 4.1k 2.4× 4.4k 2.8× 1.6k 1.1× 448 21.5k
Ulrich John 1.2k 0.4× 3.4k 2.0× 2.9k 1.7× 2.1k 1.4× 3.7k 2.7× 535 16.5k
Boo Johansson 3.0k 1.0× 649 0.4× 3.2k 1.9× 937 0.6× 1.5k 1.1× 218 12.4k
Bernardo Lessa Horta 5.1k 1.7× 2.2k 1.3× 1.3k 0.8× 4.6k 3.0× 3.9k 2.8× 466 18.5k
Anna Chaimani 2.4k 0.8× 1.1k 0.6× 1.6k 1.0× 1.3k 0.8× 1.6k 1.2× 94 17.1k
Hannu Kautiainen 2.4k 0.8× 855 0.5× 2.4k 1.4× 2.0k 1.3× 2.1k 1.6× 913 22.1k

Countries citing papers authored by Daniel J. Smıth

Since Specialization
Citations

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

Fields of papers citing papers by Daniel J. Smıth

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel J. Smıth

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel J. Smıth. A scholar is included among the top collaborators of Daniel J. Smıth 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 Daniel J. Smıth. Daniel J. Smıth 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.
Marwick, Katie, et al.. (2025). Affective disorders and chronic inflammatory conditions: analysis of 1.5 million participants in Our Future Health. BMJ Mental Health. 28(1). e301706–e301706. 2 indexed citations
2.
Fleetwood, Kelly, Bruce Guthrie, Caroline Jackson, et al.. (2025). Depression and physical multimorbidity: A cohort study of physical health condition accrual in UK Biobank. PLoS Medicine. 22(2). e1004532–e1004532. 9 indexed citations
3.
Fleetwood, Kelly, Caroline Jackson, Stewart W Mercer, et al.. (2025). Robustly measuring multimorbidity using disparate linked datasets. Communications Medicine. 5(1). 283–283.
4.
Georgiadis, Foivos, Daniel Barthelmes, Daniel J. Smıth, et al.. (2025). Estimating Accelerated Retinal Decline in Mental Health Disorders Through Normative Modeling. Schizophrenia Bulletin.
5.
Lyall, Laura M., Xingxing Zhu, Donald M. Lyall, et al.. (2023). Subjective and objective sleep and circadian parameters as predictors of depression-related outcomes: A machine learning approach in UK Biobank. Journal of Affective Disorders. 335. 83–94. 20 indexed citations
6.
Campbell, Desmond, Michael J. Green, Neil M Davies, et al.. (2022). Effects of depression on employment and social outcomes: a Mendelian randomisation study. Journal of Epidemiology & Community Health. 76(6). 563–571. 33 indexed citations
8.
Zhu, Xingxing, Joey Ward, Breda Cullen, et al.. (2021). Polygenic Risk for Schizophrenia, Brain Structure, and Environmental Risk in UK Biobank. Schizophrenia Bulletin Open. 2(1). 8 indexed citations
9.
Ward, Joey, et al.. (2021). The association between C-reactive protein, mood disorder, and cognitive function in UK Biobank. European Psychiatry. 64(1). e14–e14. 25 indexed citations
10.
Thompson, Katherine, Christopher Hübel, Rosa Cheesman, et al.. (2021). Age and sex‐related variability in the presentation of generalized anxiety and depression symptoms. Depression and Anxiety. 38(10). 1054–1065. 16 indexed citations
11.
Wyse, Cathy, Grace O’Malley, Andrew N. Coogan, Samuel McConkey, & Daniel J. Smıth. (2021). Seasonal and daytime variation in multiple immune parameters in humans: Evidence from 329,261 participants of the UK Biobank cohort. iScience. 24(4). 102255–102255. 55 indexed citations
12.
Campbell, Desmond, Michael Green, Neil M Davies, et al.. (2021). Effects of increased body mass index on employment status: a Mendelian randomisation study. International Journal of Obesity. 45(8). 1790–1801. 9 indexed citations
13.
Jones, Rhys Bevan, Anita Thapar, Frances Rice, et al.. (2020). A Digital Intervention for Adolescent Depression (MoodHwb): Mixed Methods Feasibility Evaluation. JMIR Mental Health. 7(7). e14536–e14536. 27 indexed citations
14.
Lyall, Laura M., Cathy Wyse, Kate Campbell, et al.. (2020). Accelerometry-assessed sleep duration and timing in late childhood and adolescence in Scottish schoolchildren: A feasibility study. PLoS ONE. 15(12). e0242080–e0242080. 5 indexed citations
15.
Strawbridge, Rona J., Joey Ward, Mark E.S. Bailey, et al.. (2019). Carotid Intima-Media Thickness. Arteriosclerosis Thrombosis and Vascular Biology. 40(2). 446–461. 21 indexed citations
16.
Jones, Rhys Bevan, Anita Thapar, Frances Rice, et al.. (2018). A Web-Based Psychoeducational Intervention for Adolescent Depression: Design and Development of MoodHwb. JMIR Mental Health. 5(1). e13–e13. 40 indexed citations
17.
Martin, Daniel J. & Daniel J. Smıth. (2013). Cardiometabolic comorbidity in bipolar disorder. Dusunen Adam The Journal of Psychiatry and Neurological Sciences. 315–319. 1 indexed citations
18.
Altınbaş, Kürşat, et al.. (2010). Comparing the effectiveness of mood stabilizers and antidepressants for bipolar depression treatment: a retrospective chart review. Dusunen Adam The Journal of Psychiatry and Neurological Sciences. 115–120.
20.
Wang, Lilin, et al.. (2002). Noncoding RNA danger motifs bridge innate and adaptive immunity and are potent adjuvants for vaccination. Journal of Clinical Investigation. 110(8). 1175–1184. 61 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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