Dawn Wilkins

3.1k total citations
47 papers, 741 citations indexed

About

Dawn Wilkins is a scholar working on Molecular Biology, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Dawn Wilkins has authored 47 papers receiving a total of 741 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 17 papers in Artificial Intelligence and 7 papers in Computer Networks and Communications. Recurrent topics in Dawn Wilkins's work include Gene expression and cancer classification (15 papers), Bioinformatics and Genomic Networks (10 papers) and Machine Learning in Bioinformatics (6 papers). Dawn Wilkins is often cited by papers focused on Gene expression and cancer classification (15 papers), Bioinformatics and Genomic Networks (10 papers) and Machine Learning in Bioinformatics (6 papers). Dawn Wilkins collaborates with scholars based in United States, China and France. Dawn Wilkins's co-authors include Yuanyuan Ding, Pamela B. Lawhead, Xiaofei Nan, Zhendong Zhao, Yixin Chen, Michael Macias, Christopher Ma, Krishnan Pillaipakkamnatt, Vijay Raghavan and Lisa Hellerstein and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, PLoS Biology and BMC Bioinformatics.

In The Last Decade

Dawn Wilkins

43 papers receiving 690 citations

Peers

Dawn Wilkins

AI

CNC

MB

IS

CVPR

Zhanhuai Li China

Aman Sharma India

Christian Murphy United States

Rizik Al-Sayyed Jordan

Marco Mesiti Italy

Amjad Hudaib Jordan

Giuliano Armano Italy

Huan Sun United States

Rajaraman Kanagasabai Singapore

Zhanhuai Li China

Dawn Wilkins

446 ×2.1

AI

230 ×1.1

CNC

138 ×0.8

MB

280 ×1.9

IS

87 ×0.7

CVPR

Citations per year, relative to Dawn Wilkins Dawn Wilkins (= 1×) peers Zhanhuai Li

Countries citing papers authored by Dawn Wilkins

Since Specialization

Citations

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

Fields of papers citing papers by Dawn Wilkins

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dawn Wilkins

This figure shows the co-authorship network connecting the top 25 collaborators of Dawn Wilkins. A scholar is included among the top collaborators of Dawn Wilkins 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 Dawn Wilkins. Dawn Wilkins 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

1.

Wilkins, Dawn, et al.. (2022). Th1, Th2 and Th17 inflammatory pathways synergistically predict cardiometabolic protein expression in serum of COVID-19 patients. Molecular Omics. 18(5). 408–416. 1 indexed citations

2.

Zhang, Silu, et al.. (2019). Estimating Feature-Label Dependence Using Gini Distance Statistics. IEEE Transactions on Pattern Analysis and Machine Intelligence. 43(6). 1947–1963. 13 indexed citations

3.

Zhang, Silu, et al.. (2019). Improving Performance of Convolutional Neural Networks via Feature Embedding. 31–38. 1 indexed citations

4.

Zhang, Silu, et al.. (2017). Novel gene selection method for breast cancer intrinsic subtypes from two large cohort study. 2198–2203. 4 indexed citations

5.

Ma, Christopher, et al.. (2016). Survey on swarm intelligence based routing protocols for wireless sensor networks: An extensive study. 1944–1949. 58 indexed citations

6.

Liu, Sheng, et al.. (2014). Learning accurate and interpretable models based on regularized random forests regression. BMC Systems Biology. 8(S3). S5–S5. 13 indexed citations

7.

Zhao, Zhendong, Gang Fu, Sheng Liu, et al.. (2013). Drug activity prediction using multiple-instance learning via joint instance and feature selection. BMC Bioinformatics. 14(S14). S16–S16. 16 indexed citations

8.

Fu, Gang, Xiaofei Nan, Haining Liu, et al.. (2012). Implementation of multiple-instance learning in drug activity prediction. BMC Bioinformatics. 13(S15). S3–S3. 27 indexed citations

9.

Liu, Sheng, Yixin Chen, & Dawn Wilkins. (2012). Large margin classifiers and Random Forests for integrated biological prediction. International Journal of Bioinformatics Research and Applications. 8(1/2). 38–38. 1 indexed citations

10.

Nan, Xiaofei, Gang Fu, Sheng Liu, et al.. (2011). Leveraging domain information to restructure biological prediction. BMC Bioinformatics. 12(S10). S22–S22. 2 indexed citations

11.

Nan, Xiaofei, Yixin Chen, Xin Dang, & Dawn Wilkins. (2010). Learning to rank using 1-norm regularization and convex hull reduction. 1–6. 3 indexed citations

12.

Gao, Cuilan, Xin Dang, Yixin Chen, & Dawn Wilkins. (2009). Graph ranking for exploratory gene data analysis. BMC Bioinformatics. 10(S11). S19–S19. 13 indexed citations

13.

Wren, Jonathan D., Dawn Wilkins, James C. Fuscoe, et al.. (2008). Proceedings of the 2008 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Conference. BMC Bioinformatics. 9(S9). S1–S1. 2 indexed citations

14.

Wilkins, Dawn, et al.. (2007). Proceedings of the Fourth Annual Conference of the MidSouth Computational Biology and Bioinformatics Society. BMC Bioinformatics. 8(S7). 2 indexed citations

15.

Ding, Yuanyuan, et al.. (2007). Robust clustering in high dimensional data using statistical depths. BMC Bioinformatics. 8(S7). S8–S8. 13 indexed citations

16.

Ding, Yuanyuan & Dawn Wilkins. (2006). Improving the Performance of SVM-RFE to Select Genes in Microarray Data. BMC Bioinformatics. 7(S2). S12–S12. 66 indexed citations

17.

Ding, Yuanyuan & Dawn Wilkins. (2004). The Effect of Normalization on Microarray Data Analysis. DNA and Cell Biology. 23(10). 635–642. 12 indexed citations

18.

Ptitsyn, Andrey, et al.. (2004). Regional Societies: Fostering Competitive Research Through Virtual Infrastructures. PLoS Biology. 2(12). e372–e372. 2 indexed citations

19.

Pillaipakkamnatt, Krishnan & Dawn Wilkins. (1998). A Tool For Homework Submission Using the World Wide Web.. WebNet.

20.

Zhou, Yan, Dawn Wilkins, & Robert P. Cook. (1998). Neural network control for a fire-fighting robot. 19(3). 146–152. 6 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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