Casey Hanson

643 total citations
9 papers, 236 citations indexed

About

Casey Hanson is a scholar working on Molecular Biology, Infectious Diseases and Computer Networks and Communications. According to data from OpenAlex, Casey Hanson has authored 9 papers receiving a total of 236 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 1 paper in Infectious Diseases and 1 paper in Computer Networks and Communications. Recurrent topics in Casey Hanson's work include Genomics and Chromatin Dynamics (4 papers), Gene expression and cancer classification (2 papers) and Network Security and Intrusion Detection (1 paper). Casey Hanson is often cited by papers focused on Genomics and Chromatin Dynamics (4 papers), Gene expression and cancer classification (2 papers) and Network Security and Intrusion Detection (1 paper). Casey Hanson collaborates with scholars based in United States and Sweden. Casey Hanson's co-authors include Saurabh Sinha, Kenneth L. McClain, B. A. Peterson, K Gajl-Peczalska, Glauco Frizzera, John H. Kersey, Junmei Cairns, Ingrida Verbiené, Ulla Delle and ANNA WEIMARCK and has published in prestigious journals such as Journal of Clinical Investigation, Genome Research and Developmental Biology.

In The Last Decade

Casey Hanson

9 papers receiving 222 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Casey Hanson United States	9	89	88	47	44	32	9	236
Lingqiu Gao United States	12	258 2.9×	59 0.7×	42 0.9×	19 0.4×	15 0.5×	17	363
Jason Clark United States	8	165 1.9×	44 0.5×	30 0.6×	78 1.8×	32 1.0×	14	312
Albertina Pereira United States	7	139 1.6×	52 0.6×	61 1.3×	11 0.3×	36 1.1×	11	403
Xiaoqun Chen China	10	231 2.6×	79 0.9×	6 0.1×	15 0.3×	31 1.0×	22	389
Laia Cubells Spain	8	350 3.9×	40 0.5×	18 0.4×	34 0.8×	9 0.3×	14	418
Neelam V. Desai United States	12	318 3.6×	182 2.1×	32 0.7×	22 0.5×	18 0.6×	29	538
Xinsong Chen Sweden	11	187 2.1×	123 1.4×	22 0.5×	36 0.8×	5 0.2×	23	346
Florence Mauger France	10	226 2.5×	61 0.7×	37 0.8×	51 1.2×	19 0.6×	21	376
Chung-Chieh Chiao Taiwan	11	269 3.0×	79 0.9×	14 0.3×	9 0.2×	38 1.2×	13	395
Kirstine A. Knox United Kingdom	13	270 3.0×	108 1.2×	38 0.8×	20 0.5×	22 0.7×	22	489

Countries citing papers authored by Casey Hanson

Since Specialization

Citations

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

Fields of papers citing papers by Casey Hanson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Casey Hanson

This figure shows the co-authorship network connecting the top 25 collaborators of Casey Hanson. A scholar is included among the top collaborators of Casey Hanson 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 Casey Hanson. Casey Hanson 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:

9 of 9 papers shown

1.

Hanson, Casey, et al.. (2021). An integrated multi-omics approach to identify regulatory mechanisms in cancer metastatic processes. Genome biology. 22(1). 19–19. 16 indexed citations

2.

Xie, Xiaoman, Casey Hanson, & Saurabh Sinha. (2019). Mechanistic interpretation of non-coding variants for discovering transcriptional regulators of drug response. BMC Biology. 17(1). 62–62. 10 indexed citations

3.

Hanson, Casey, Junmei Cairns, Liewei Wang, & Saurabh Sinha. (2018). Principled multi-omic analysis reveals gene regulatory mechanisms of phenotype variation. Genome Research. 28(8). 1207–1216. 13 indexed citations

4.

Suryamohan, Kushal, et al.. (2016). Redeployment of a conserved gene regulatory network during Aedes aegypti development. Developmental Biology. 416(2). 402–413. 16 indexed citations

5.

Hanson, Casey, Junmei Cairns, Li Wang, & Saurabh Sinha. (2015). Computational discovery of transcription factors associated with drug response. The Pharmacogenomics Journal. 16(6). 573–582. 11 indexed citations

6.

Hanson, Casey, et al.. (2013). Modeling and detecting anomalous topic access. 100–105. 19 indexed citations

7.

Hanson, Casey, et al.. (1996). A rapid and simplified technique for analysis of archival formalin-fixed, paraffin-embedded tissue by fluorescence in situ hybridization (FISH).. PubMed. 16(5A). 2533–6. 18 indexed citations

8.

Strahler, John R., Rork Kuick, Christoph Eckerskorn, et al.. (1990). Identification of two related markers for common acute lymphoblastic leukemia as heat shock proteins.. Journal of Clinical Investigation. 85(1). 200–207. 34 indexed citations

9.

Hanson, Casey, Glauco Frizzera, B. A. Peterson, et al.. (1988). Clonal rearrangement for immunoglobulin and T-cell receptor genes in systemic Castleman's disease. Association with Epstein-Barr virus.. PubMed. 131(1). 84–91. 99 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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