Jessica C. Mar

8.3k total citations · 1 hit paper
60 papers, 3.2k citations indexed

About

Jessica C. Mar is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Jessica C. Mar has authored 60 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Molecular Biology, 13 papers in Immunology and 9 papers in Oncology. Recurrent topics in Jessica C. Mar's work include Single-cell and spatial transcriptomics (16 papers), Gene expression and cancer classification (14 papers) and Bioinformatics and Genomic Networks (14 papers). Jessica C. Mar is often cited by papers focused on Single-cell and spatial transcriptomics (16 papers), Gene expression and cancer classification (14 papers) and Bioinformatics and Genomic Networks (14 papers). Jessica C. Mar collaborates with scholars based in United States, Australia and Japan. Jessica C. Mar's co-authors include John Quackenbush, Paul S. Frenette, Qiaozhi Wei, Toshihide Mizoguchi, Sandra Pinho, Shuonan Chen, Dachuan Zhang, Ingmar Bruns, Christoph Scheiermann and Daniel Lucas and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Jessica C. Mar

59 papers receiving 3.1k citations

Hit Papers

Arteriolar niches maintain haematopoietic stem cell quies... 2013 2026 2017 2021 2013 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jessica C. Mar United States 28 1.7k 822 656 511 397 60 3.2k
Ernesto Bockamp Germany 27 1.8k 1.1× 1.0k 1.2× 921 1.4× 570 1.1× 340 0.9× 54 3.7k
Jonathan R. Keller United States 33 1.7k 1.0× 728 0.9× 1.3k 1.9× 771 1.5× 369 0.9× 91 3.4k
Simon Haas Germany 19 1.9k 1.1× 982 1.2× 872 1.3× 346 0.7× 338 0.9× 40 3.1k
Debashis Sahoo United States 33 2.7k 1.6× 594 0.7× 1.1k 1.7× 1.0k 2.0× 282 0.7× 98 5.1k
Stephen M. Sykes United States 27 2.4k 1.5× 765 0.9× 382 0.6× 996 1.9× 302 0.8× 80 3.6k
Sandra Offner Switzerland 25 2.7k 1.6× 1.4k 1.7× 1.2k 1.9× 600 1.2× 459 1.2× 37 4.5k
Michael P. Cooke United States 21 1.4k 0.9× 861 1.0× 2.1k 3.2× 547 1.1× 482 1.2× 69 3.9k
Marieke Essers Germany 23 2.8k 1.7× 1.6k 2.0× 1.5k 2.3× 803 1.6× 583 1.5× 43 5.0k
Katrin Busch Germany 14 1.4k 0.8× 651 0.8× 1.9k 2.8× 356 0.7× 192 0.5× 18 3.5k
Mira Jeong United States 28 2.8k 1.7× 1.7k 2.0× 763 1.2× 264 0.5× 581 1.5× 47 4.1k

Countries citing papers authored by Jessica C. Mar

Since Specialization
Citations

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

Fields of papers citing papers by Jessica C. Mar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jessica C. Mar. 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 Jessica C. Mar. The network helps show where Jessica C. Mar may publish in the future.

Co-authorship network of co-authors of Jessica C. Mar

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

All Works

20 of 20 papers shown
1.
Zimmerman, Samuel, Hannah C. Leeson, Christian M. Nefzger, et al.. (2024). Superior Induced Pluripotent Stem Cell Generation through Phactr3-Driven Mechanomodulation of Both Early and Late Phases of Cell Reprogramming. Biomaterials Research. 28. 25–25. 5 indexed citations
2.
Fard, Atefeh Taherian, Hannah C. Leeson, Julio Aguado, et al.. (2023). Deconstructing heterogeneity of replicative senescence in human mesenchymal stem cells at single cell resolution. GeroScience. 46(1). 999–1015. 10 indexed citations
4.
Kulkarni, Ameya, et al.. (2022). scShapes: a statistical framework for identifying distribution shapes in single-cell RNA-sequencing data. GigaScience. 12. 5 indexed citations
5.
Fard, Atefeh Taherian, et al.. (2022). Computational Methods for Single-Cell Imaging and Omics Data Integration. Frontiers in Molecular Biosciences. 8. 768106–768106. 21 indexed citations
6.
Galbo, Phillip M., Ameya Kulkarni, Atefeh Taherian Fard, et al.. (2022). Redox signaling by glutathione peroxidase 2 links vascular modulation to metabolic plasticity of breast cancer. Proceedings of the National Academy of Sciences. 119(8). 37 indexed citations
7.
Ratnakumar, Abhirami, Nils Weinhold, Jessica C. Mar, & Nadeem Riaz. (2020). Protein-Protein interactions uncover candidate ‘core genes’ within omnigenic disease networks. PLoS Genetics. 16(7). e1008903–e1008903. 15 indexed citations
8.
Yu, Bo, Naresh Doni Jayavelu, Stephanie L. Battle, et al.. (2020). Single-cell analysis of transcriptome and DNA methylome in human oocyte maturation. PLoS ONE. 15(11). e0241698–e0241698. 34 indexed citations
9.
Wei, Qiaozhi, Fumio Nakahara, Noboru Asada, et al.. (2020). Snai2 Maintains Bone Marrow Niche Cells by Repressing Osteopontin Expression. Developmental Cell. 53(5). 503–513.e5. 14 indexed citations
10.
Montagna, Cristina, et al.. (2019). A novel approach to modelling transcriptional heterogeneity identifies the oncogene candidate CBX2 in invasive breast carcinoma. British Journal of Cancer. 120(7). 746–753. 26 indexed citations
11.
Xu, Chunliang, Xin Gao, Qiaozhi Wei, et al.. (2018). Stem cell factor is selectively secreted by arterial endothelial cells in bone marrow. Nature Communications. 9(1). 2449–2449. 138 indexed citations
12.
Zimmerman, Samuel, et al.. (2017). pathVar: a new method for pathway-based interpretation of gene expression variability. PeerJ. 5. e3334–e3334. 5 indexed citations
13.
Li, Wenge, R. Brent Calder, Jessica C. Mar, & Jan Vijg. (2015). Single-cell transcriptogenomics reveals transcriptional exclusion of ENU-mutated alleles. Mutation research. Fundamental and molecular mechanisms of mutagenesis. 772. 55–62. 29 indexed citations
14.
Hasegawa, Yu, et al.. (2015). Variability of Gene Expression Identifies Transcriptional Regulators of Early Human Embryonic Development. PLoS Genetics. 11(8). e1005428–e1005428. 37 indexed citations
15.
Mar, Jessica C., Nicholas Matigian, John Quackenbush, & Christine A. Wells. (2011). attract: A Method for Identifying Core Pathways That Define Cellular Phenotypes. PLoS ONE. 6(10). e25445–e25445. 31 indexed citations
16.
Zhao, Bo, James Zou, Hongfang Wang, et al.. (2011). Epstein-Barr virus exploits intrinsic B-lymphocyte transcription programs to achieve immortal cell growth. Proceedings of the National Academy of Sciences. 108(36). 14902–14907. 159 indexed citations
18.
Haas, David W., Daniel E. Geraghty, Janet Andersen, et al.. (2006). Immunogenetics of CD4 Lymphocyte Count Recovery during Antiretroviral Therapy: An AIDS Clinical Trials Group Study. The Journal of Infectious Diseases. 194(8). 1098–1107. 55 indexed citations
19.
Mar, Jessica C., Renee Rubio, & John Quackenbush. (2006). Inferring steady state single-cell gene expression distributions from analysis of mesoscopic samples. Genome biology. 7(12). R119–R119. 10 indexed citations
20.
McLachlan, Geoffrey J., et al.. (2004). On the simultaneous use of clinical and microarray expression data in the cluster analysis of tissue samples. Queensland's institutional digital repository (The University of Queensland). 29. 167–171. 1 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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