Joel S. Bader

27.5k total citations · 3 hit papers
127 papers, 9.7k citations indexed

About

Joel S. Bader is a scholar working on Molecular Biology, Genetics and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Joel S. Bader has authored 127 papers receiving a total of 9.7k indexed citations (citations by other indexed papers that have themselves been cited), including 82 papers in Molecular Biology, 24 papers in Genetics and 14 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Joel S. Bader's work include Bioinformatics and Genomic Networks (28 papers), RNA and protein synthesis mechanisms (15 papers) and Fungal and yeast genetics research (14 papers). Joel S. Bader is often cited by papers focused on Bioinformatics and Genomic Networks (28 papers), RNA and protein synthesis mechanisms (15 papers) and Fungal and yeast genetics research (14 papers). Joel S. Bader collaborates with scholars based in United States, United Kingdom and China. Joel S. Bader's co-authors include Jef D. Boeke, B. J. Berne, David Chandler, Andrew J. Ewald, Daniel Yuan, Hailiang Huang, Xuewen Pan, Veena Padmanaban, Robert A. Kuharski and Jonathan M. Rothberg and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Joel S. Bader

121 papers receiving 9.6k citations

Hit Papers

E-cadherin is required for metastasis in multiple models ... 2016 2026 2019 2022 2019 2016 2017 100 200 300 400 500

Peers

Joel S. Bader
Rosemary Braun United States
İvet Bahar United States
Sunhwan Jo United States
Elizabeth Villa United States
Emil Alexov United States
Rosemary Braun United States
Joel S. Bader
Citations per year, relative to Joel S. Bader Joel S. Bader (= 1×) peers Rosemary Braun

Countries citing papers authored by Joel S. Bader

Since Specialization
Citations

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

Fields of papers citing papers by Joel S. Bader

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joel S. Bader. 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 Joel S. Bader. The network helps show where Joel S. Bader may publish in the future.

Co-authorship network of co-authors of Joel S. Bader

This figure shows the co-authorship network connecting the top 25 collaborators of Joel S. Bader. A scholar is included among the top collaborators of Joel S. Bader 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 Joel S. Bader. Joel S. Bader 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.
Lerner, Michael G., Hildur Knútsdóttir, Fatemeh Shojaeian, et al.. (2025). P4HA1 Mediates Hypoxia-Induced Invasion in Human Pancreatic Cancer Organoids. Cancer Research Communications. 5(5). 881–895. 2 indexed citations
2.
Duong, ThuyVy, Thomas R. Austin, Jennifer A. Brody, et al.. (2024). Circulating Blood Plasma Profiling Reveals Proteomic Signature and a Causal Role for SVEP1 in Sudden Cardiac Death. Circulation Genomic and Precision Medicine. 17(5). e004494–e004494.
3.
Lerner, Michael G., et al.. (2024). Prioritizing drug targets by perturbing biological network response functions. PLoS Computational Biology. 20(6). e1012195–e1012195. 3 indexed citations
4.
Zhou, Chun, Yun Wang, Yongpan An, et al.. (2024). The de novo design and synthesis of yeast chromosome XIII facilitates investigations on aging. Nature Communications. 15(1). 10139–10139. 3 indexed citations
5.
Knútsdóttir, Hildur, Fatemeh Shojaeian, Michael G. Lerner, et al.. (2023). Morphology-guided transcriptomic analysis of human pancreatic cancer organoids reveals microenvironmental signals that enhance invasion. Journal of Clinical Investigation. 133(8). 14 indexed citations
6.
Henriet, Elodie, Hildur Knútsdóttir, Eloïse M. Grasset, et al.. (2023). Triple negative breast tumors contain heterogeneous cancer cells expressing distinct KRAS-dependent collective and disseminative invasion programs. Oncogene. 42(10). 737–747. 10 indexed citations
7.
Danchik, Carina, et al.. (2021). Genetic Determinants of Intrinsic Antibiotic Tolerance in Mycobacterium avium. Microbiology Spectrum. 9(2). e0024621–e0024621. 5 indexed citations
8.
Chan, Isaac S., Hildur Knútsdóttir, Veena Padmanaban, et al.. (2020). Cancer cells educate natural killer cells to a metastasis-promoting cell state. The Journal of Cell Biology. 219(9). 104 indexed citations
9.
Dutta, Noton K., Lee G. Klinkenberg, Gonzalo Colmenarejo, et al.. (2019). Inhibiting the stringent response blocks Mycobacterium tuberculosis entry into quiescence and reduces persistence. Science Advances. 5(3). eaav2104–eaav2104. 97 indexed citations
10.
Shen, Michael, Yi Wu, Kun Yang, et al.. (2018). Heterozygous diploid and interspecies SCRaMbLEing. Nature Communications. 9(1). 1934–1934. 67 indexed citations
11.
Foreman, Taylor W., Nirmalya Bandyopadhyay, Uma Shankar Gautam, et al.. (2017). Hypoxia Sensing and Persistence Genes Are Expressed during the Intragranulomatous Survival of Mycobacterium tuberculosis. American Journal of Respiratory Cell and Molecular Biology. 56(5). 637–647. 41 indexed citations
12.
Cheung, Kevin J., Veena Padmanaban, Vanesa L. Silvestri, et al.. (2016). Polyclonal breast cancer metastases arise from collective dissemination of keratin 14-expressing tumor cell clusters. Proceedings of the National Academy of Sciences. 113(7). E854–63. 541 indexed citations breakdown →
13.
Pan, Xuewen, Ping Ye, Daniel Yuan, et al.. (2013). A DNA Integrity Network in the Yeast Saccharomyces cerevisiae. Cell. 153(5). 1165–1165.
14.
Suhail, Yasir, Kshitiz Gupta, Justin Lee, et al.. (2013). Modeling Intercellular Transfer of Biomolecules Through Tunneling Nanotubes. Bulletin of Mathematical Biology. 75(8). 1400–1416. 6 indexed citations
15.
Annaluru, Narayana, Héloïse Muller, Sivaprakash Ramalingam, et al.. (2012). Assembling DNA Fragments by USER Fusion. Methods in molecular biology. 852. 77–95. 12 indexed citations
16.
Zou, Beiyan, et al.. (2010). Profiling Diverse Compounds by Flux- and Electrophysiology-Based Primary Screens for Inhibition of Human Ether-à-go-go Related Gene Potassium Channels. Assay and Drug Development Technologies. 8(6). 743–754. 23 indexed citations
17.
Rivera, Corban G., Rachit M. Vakil, & Joel S. Bader. (2010). NeMo: Network Module identification in Cytoscape. BMC Bioinformatics. 11(S1). S61–S61. 98 indexed citations
18.
Bader, Joel S., et al.. (2010). Predicting functional associations from metabolism using bi-partite network algorithms. BMC Systems Biology. 4(1). 95–95. 6 indexed citations
19.
Dymond, Jessica S., et al.. (2010). CLONEQC: lightweight sequence verification for synthetic biology. Nucleic Acids Research. 38(8). 2617–2623. 6 indexed citations
20.
Qi, Yan, Yasir Suhail, Yu-Yi Lin, Jef D. Boeke, & Joel S. Bader. (2008). Finding friends and enemies in an enemies-only network: A graph diffusion kernel for predicting novel genetic interactions and co-complex membership from yeast genetic interactions. Genome Research. 18(12). 1991–2004. 69 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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