Jill Thaisz

680 total citations
8 papers, 572 citations indexed

About

Jill Thaisz is a scholar working on Genetics, Molecular Biology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Jill Thaisz has authored 8 papers receiving a total of 572 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Genetics, 3 papers in Molecular Biology and 2 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Jill Thaisz's work include Genetic Mapping and Diversity in Plants and Animals (3 papers), Signaling Pathways in Disease (2 papers) and Genetic Associations and Epidemiology (2 papers). Jill Thaisz is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (3 papers), Signaling Pathways in Disease (2 papers) and Genetic Associations and Epidemiology (2 papers). Jill Thaisz collaborates with scholars based in United States, Japan and Switzerland. Jill Thaisz's co-authors include Stephen F. Vatner, Atsuko Yatani, Dorothy E. Vatner, Junichi Sadoshima, Keith DiPetrillo, Mari Odashima, Song‐Jung Kim, Shimako Yamamoto, Daniela Zablocki and Chull Hong and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Investigation and Hypertension.

In The Last Decade

Jill Thaisz

7 papers receiving 560 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jill Thaisz United States	7	288	149	127	85	68	8	572
Ruhong Cheng China	13	210 0.7×	45 0.3×	95 0.7×	52 0.6×	29 0.4×	42	521
Jia‐Ping Wu Taiwan	13	310 1.1×	55 0.4×	46 0.4×	55 0.6×	42 0.6×	29	556
Jun Hou China	12	187 0.6×	68 0.5×	25 0.2×	74 0.9×	82 1.2×	46	590
Camille Garcia France	11	302 1.0×	71 0.5×	67 0.5×	39 0.5×	11 0.2×	20	476
Wakako Murakami Japan	10	271 0.9×	166 1.1×	48 0.4×	46 0.5×	36 0.5×	13	472
Lin Deng China	13	487 1.7×	73 0.5×	23 0.2×	47 0.6×	203 3.0×	34	743
Nadia Walter Switzerland	11	470 1.6×	26 0.2×	35 0.3×	175 2.1×	41 0.6×	14	684
Ae Lee Jeong South Korea	14	213 0.7×	25 0.2×	42 0.3×	81 1.0×	28 0.4×	25	432
Marie Marcinko United States	7	344 1.2×	75 0.5×	451 3.6×	273 3.2×	10 0.1×	7	731
Sanae Shoji-Kawata United States	6	335 1.2×	26 0.2×	67 0.5×	402 4.7×	40 0.6×	7	654

Countries citing papers authored by Jill Thaisz

Since Specialization

Citations

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

Fields of papers citing papers by Jill Thaisz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jill Thaisz

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

All Works

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8 of 8 papers shown

1.

Churchill, Gary A., Frank Staedtler, Ron Korstanje, et al.. (2020). Genome-Wide Association Mapping of Quantitative Traits in Outbred Mice. UNC Libraries.

2.

Zhang, Jimin, Franziska Leifer, Sasha J. Rose, et al.. (2018). Amikacin Liposome Inhalation Suspension (ALIS) Penetrates Non-tuberculous Mycobacterial Biofilms and Enhances Amikacin Uptake Into Macrophages. Frontiers in Microbiology. 9. 131 indexed citations

3.

Thaisz, Jill, Shirng‐Wern Tsaih, Minjie Feng, et al.. (2012). Genetic analysis of albuminuria in collaborative cross and multiple mouse intercross populations. American Journal of Physiology-Renal Physiology. 303(7). F972–F981. 17 indexed citations

4.

Zhang, Weidong, Ron Korstanje, Jill Thaisz, et al.. (2012). Genome-Wide Association Mapping of Quantitative Traits in Outbred Mice. G3 Genes Genomes Genetics. 2(2). 167–174. 39 indexed citations

5.

Feng, Minjie, M. Elizabeth Deerhake, Ryan Keating, et al.. (2009). Genetic Analysis of Blood Pressure in 8 Mouse Intercross Populations. Hypertension. 54(4). 802–809. 31 indexed citations

6.

Yamamoto, Shimako, Guiping Yang, Daniela Zablocki, et al.. (2003). Activation of Mst1 causes dilated cardiomyopathy by stimulating apoptosis without compensatory ventricular myocyte hypertrophy. Journal of Clinical Investigation. 111(10). 1463–1474. 247 indexed citations

7.

Yamamoto, Shimako, Guiping Yang, Daniela Zablocki, et al.. (2003). Activation of Mst1 causes dilated cardiomyopathy by stimulating apoptosis without compensatory ventricular myocyte hypertrophy. Journal of Clinical Investigation. 111(10). 1463–1474. 11 indexed citations

8.

Kim, Young-Kwon, Song-Jung Kim, Atsuko Yatani, et al.. (2003). Mechanism of Enhanced Cardiac Function in Mice with Hypertrophy Induced by Overexpressed Akt. Journal of Biological Chemistry. 278(48). 47622–47628. 96 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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