Kevin Dick

827 total citations
43 papers, 564 citations indexed

About

Kevin Dick is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition and Epidemiology. According to data from OpenAlex, Kevin Dick has authored 43 papers receiving a total of 564 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 5 papers in Computer Vision and Pattern Recognition and 4 papers in Epidemiology. Recurrent topics in Kevin Dick's work include Bioinformatics and Genomic Networks (7 papers), Computational Drug Discovery Methods (4 papers) and Protein Structure and Dynamics (3 papers). Kevin Dick is often cited by papers focused on Bioinformatics and Genomic Networks (7 papers), Computational Drug Discovery Methods (4 papers) and Protein Structure and Dynamics (3 papers). Kevin Dick collaborates with scholars based in Canada, United States and United Kingdom. Kevin Dick's co-authors include James R. Green, Judith C. Chow, John G. Watson, John Lenard, Jingxin Cao, Janilyn Arsenio, Canhua Jiang, Xiangzhi Meng, Yan Xiang and L.‐W. Antony Chen and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Cleaner Production.

In The Last Decade

Kevin Dick

41 papers receiving 550 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kevin Dick Canada	14	129	96	74	70	54	43	564
Christoph Molnar Germany	10	57 0.4×	22 0.2×	13 0.2×	79 1.1×	31 0.6×	12	1.0k
Giuseppe Casalicchio Germany	9	100 0.8×	24 0.3×	15 0.2×	44 0.6×	32 0.6×	20	635
Hua Peng China	19	430 3.3×	12 0.1×	9 0.1×	22 0.3×	122 2.3×	73	1.1k
Liu Ji China	14	241 1.9×	9 0.1×	10 0.1×	19 0.3×	26 0.5×	55	807
Yuansheng Zhang China	15	367 2.8×	12 0.1×	32 0.4×	16 0.2×	20 0.4×	54	749
Yuzhe Zhang China	13	52 0.4×	31 0.3×	61 0.8×	158 2.3×	14 0.3×	62	626
Frauke Günther Germany	6	77 0.6×	22 0.2×	13 0.2×	55 0.8×	16 0.3×	7	636
Qiliang Liu China	18	114 0.9×	35 0.4×	21 0.3×	86 1.2×	223 4.1×	69	1.0k
He Zhang China	20	69 0.5×	42 0.4×	4 0.1×	96 1.4×	19 0.4×	65	1.1k
Fengyun Liu China	11	61 0.5×	22 0.2×	40 0.5×	29 0.4×	9 0.2×	42	526

Countries citing papers authored by Kevin Dick

Since Specialization

Citations

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

Fields of papers citing papers by Kevin Dick

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kevin Dick

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Dick, Kevin, Robin Ducharme, Alysha L. J. Dingwall‐Harvey, et al.. (2025). Transformer-based deep learning ensemble framework predicts autism spectrum disorder using health administrative and birth registry data. Scientific Reports. 15(1). 11816–11816. 1 indexed citations

Ducharme, Robin, Alysha L. J. Dingwall‐Harvey, Ruth Rennicks White, et al.. (2024). Deep learning prediction of renal anomalies for prenatal ultrasound diagnosis. Scientific Reports. 14(1). 9013–9013. 4 indexed citations

Ducharme, Robin, Alysha L. J. Dingwall‐Harvey, Steven Hawken, et al.. (2024). CAManim: Animating end-to-end network activation maps. PLoS ONE. 19(6). e0296985–e0296985. 2 indexed citations

Rajan, Sreeraman, et al.. (2023). Critical Electrical Infrastructure Segmentation in Arctic Conditions. 1–6. 4 indexed citations

Dick, Kevin, James M. Humber, Robin Ducharme, et al.. (2023). The Transformative Potential of AI in Obstetrics and Gynaecology. Journal of Obstetrics and Gynaecology Canada. 46(3). 102277–102277. 1 indexed citations

Dick, Kevin, Ashkan Golshani, Benjamin Mimee, et al.. (2023). Large-scale data mining pipeline for identifying novel soybean genes involved in resistance against the soybean cyst nematode. SHILAP Revista de lepidopterología. 3. 1199675–1199675. 1 indexed citations

Dick, Kevin, et al.. (2022). GasBotty: Multi-Metric Extraction in the Wild. IEEE Access. 10. 28487–28498. 1 indexed citations

Dick, Kevin, et al.. (2022). Reciprocal perspective as a super learner improves drug-target interaction prediction (MUSDTI). Scientific Reports. 12(1). 13237–13237. 3 indexed citations

Luscombe, Alex, Kevin Dick, & Kevin Walby. (2021). Algorithmic thinking in the public interest: navigating technical, legal, and ethical hurdles to web scraping in the social sciences. Quality & Quantity. 56(3). 1023–1044. 27 indexed citations

10.

Dick, Kevin, et al.. (2021). Machine learning pedagogy to support the research community. 43–48. 2 indexed citations

11.

Dick, Kevin, et al.. (2021). Multi-schema computational prediction of the comprehensive SARS-CoV-2 vs. human interactome. PeerJ. 9. e11117–e11117. 8 indexed citations

12.

Dick, Kevin, Bahram Samanfar, Elroy R. Cober, et al.. (2020). PIPE4: Fast PPI Predictor for Comprehensive Inter- and Cross-Species Interactomes. Scientific Reports. 10(1). 1390–1390. 20 indexed citations

13.

Dick, Kevin, et al.. (2020). RPmirDIP: Reciprocal Perspective improves miRNA targeting prediction. Scientific Reports. 10(1). 11770–11770. 13 indexed citations

14.

Dick, Kevin & James R. Green. (2018). Reciprocal Perspective for Improved Protein-Protein Interaction Prediction. Scientific Reports. 8(1). 11694–11694. 19 indexed citations

15.

Burnside, Daniel, Andrew Schoenrock, Houman Moteshareie, et al.. (2018). In Silico Engineering of Synthetic Binding Proteins from Random Amino Acid Sequences. iScience. 11. 375–387. 13 indexed citations

16.

Schoenrock, Andrew, Kevin Dick, James R. Green, et al.. (2018). Insights into the suitability of utilizing brown rats (Rattus norvegicus) as a model for healing spinal cord injury with epidermal growth factor and fibroblast growth factor-II by predicting protein-protein interactions. Computers in Biology and Medicine. 104. 220–226. 3 indexed citations

17.

Dick, Kevin, Daniel Burnside, Houman Moteshareie, et al.. (2017). Designing anti-Zika virus peptides derived from predicted human-Zika virus protein-protein interactions. Computational Biology and Chemistry. 71. 180–187. 19 indexed citations

18.

Smulders, Tom V., et al.. (2017). A Real-world <em>What-Where-When</em> Memory Test. Journal of Visualized Experiments. 1 indexed citations

19.

Chen, L.‐W. Antony, et al.. (2012). Wintertime particulate pollution episodes in an urban valley of the Western US: a case study. Atmospheric chemistry and physics. 12(21). 10051–10064. 60 indexed citations

20.

Hong, Andy, Tanya C. Burch, Carla Osiowy, et al.. (2012). The interaction between hepatitis B virus X protein and AIB1 oncogene is required for the activation of NFκB signal transduction. Biochemical and Biophysical Research Communications. 423(1). 6–12. 13 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.

Explore authors with similar magnitude of impact