Heather Eckart

759 total citations
11 papers, 387 citations indexed

About

Heather Eckart is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Heather Eckart has authored 11 papers receiving a total of 387 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 4 papers in Immunology and 3 papers in Oncology. Recurrent topics in Heather Eckart's work include Single-cell and spatial transcriptomics (7 papers), Reproductive System and Pregnancy (2 papers) and Cancer-related molecular mechanisms research (2 papers). Heather Eckart is often cited by papers focused on Single-cell and spatial transcriptomics (7 papers), Reproductive System and Pregnancy (2 papers) and Cancer-related molecular mechanisms research (2 papers). Heather Eckart collaborates with scholars based in United States and China. Heather Eckart's co-authors include Anindita Basu, Bingqing Xie, Susan Olalekan, Kevin P. White, Tonya M. Brunetti, Vineet K. Dhiman, Shan Yu, Yuwen Liu, Sebastian Pott and Yoav Gilad and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Scientific Reports.

In The Last Decade

Heather Eckart

10 papers receiving 386 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Heather Eckart United States	8	291	99	74	54	41	11	387
Pratik Home United States	15	717 2.5×	68 0.7×	74 1.0×	39 0.7×	12 0.3×	21	885
Fanny Jaulin France	11	227 0.8×	40 0.4×	24 0.3×	74 1.4×	14 0.3×	24	423
Danyu Lu China	11	290 1.0×	35 0.4×	20 0.3×	32 0.6×	33 0.8×	19	397
Kuniko Nakajima Japan	12	489 1.7×	57 0.6×	28 0.4×	36 0.7×	64 1.6×	19	580
Denise G. Lanza United States	9	165 0.6×	41 0.4×	132 1.8×	70 1.3×	21 0.5×	18	328
Bela Patel United States	15	484 1.7×	68 0.7×	33 0.4×	24 0.4×	74 1.8×	24	681
Qiuyue Yuan China	6	139 0.5×	83 0.8×	25 0.3×	55 1.0×	19 0.5×	9	231
Wenlin Jiao China	9	160 0.5×	54 0.5×	34 0.5×	12 0.2×	29 0.7×	11	277
Yuichiro Semba Japan	12	203 0.7×	29 0.3×	25 0.3×	30 0.6×	19 0.5×	35	305
Aurore Morlon France	5	246 0.8×	43 0.4×	67 0.9×	31 0.6×	19 0.5×	6	324

Countries citing papers authored by Heather Eckart

Since Specialization

Citations

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

Fields of papers citing papers by Heather Eckart

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Heather Eckart

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

All Works

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11 of 11 papers shown

Weigert, Melanie, Yan Li, Heather Eckart, et al.. (2025). A cell atlas of the human fallopian tube throughout the menstrual cycle and menopause. Nature Communications. 16(1). 372–372. 4 indexed citations

Xie, Bingqing, et al.. (2024). Exploring the tumor micro-environment in primary and metastatic tumors of different ovarian cancer histotypes. Frontiers in Cell and Developmental Biology. 11. 1297219–1297219. 2 indexed citations

Luo, Kaixuan, Xiaotong Sun, Heather Eckart, et al.. (2023). Single-cell genomics improves the discovery of risk variants and genes of atrial fibrillation. Nature Communications. 14(1). 4999–4999. 13 indexed citations

Lengyel, Ernst, Yan Li, Melanie Weigert, et al.. (2022). A molecular atlas of the human postmenopausal fallopian tube and ovary from single-cell RNA and ATAC sequencing. Cell Reports. 41(12). 111838–111838. 29 indexed citations

Olalekan, Susan, et al.. (2021). Characterizing the tumor microenvironment of metastatic ovarian cancer by single-cell transcriptomics. Cell Reports. 35(8). 109165–109165. 101 indexed citations

Xie, Bingqing, et al.. (2021). mDrop-Seq: Massively Parallel Single-Cell RNA-Seq of Saccharomyces cerevisiae and Candida albicans. Vaccines. 10(1). 30–30. 14 indexed citations

Kweon, Junghun, Heather Eckart, Andrew D. Hoffmann, et al.. (2020). Hedgehog–FGF signaling axis patterns anterior mesoderm during gastrulation. Proceedings of the National Academy of Sciences. 117(27). 15712–15723. 27 indexed citations

Eckart, Heather, Bingqing Xie, Reem Elorbany, et al.. (2020). Systematic Comparison of High-throughput Single-Cell and Single-Nucleus Transcriptomes during Cardiomyocyte Differentiation. Scientific Reports. 10(1). 66 indexed citations

Olalekan, Susan, et al.. (2020). Characterizing the Tumor Microenvironment of Metastatic Ovarian Cancer by Single Cell Transcriptomics. SSRN Electronic Journal.

10.

Meng, Qingtuan, Kangli Wang, Tonya M. Brunetti, et al.. (2018). The DGCR5 long noncoding RNA may regulate expression of several schizophrenia-related genes. Science Translational Medicine. 10(472). 58 indexed citations

11.

Liu, Yuwen, Shan Yu, Vineet K. Dhiman, et al.. (2017). Functional assessment of human enhancer activities using whole-genome STARR-sequencing. Genome biology. 18(1). 219–219. 73 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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