Justin B. Kinney

6.1k total citations · 3 hit papers
47 papers, 3.4k citations indexed

About

Justin B. Kinney is a scholar working on Molecular Biology, Genetics and Artificial Intelligence. According to data from OpenAlex, Justin B. Kinney has authored 47 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Molecular Biology, 14 papers in Genetics and 6 papers in Artificial Intelligence. Recurrent topics in Justin B. Kinney's work include RNA and protein synthesis mechanisms (16 papers), Genomics and Chromatin Dynamics (11 papers) and RNA Research and Splicing (8 papers). Justin B. Kinney is often cited by papers focused on RNA and protein synthesis mechanisms (16 papers), Genomics and Chromatin Dynamics (11 papers) and RNA Research and Splicing (8 papers). Justin B. Kinney collaborates with scholars based in United States, France and Sweden. Justin B. Kinney's co-authors include Gurinder S. Atwal, Ammar Tareen, Curtis G. Callan, Juan Maldacena, Shiraz Minwalla, Suvrat Raju, Anand Murugan, Junwei Shi, Christopher R. Vakoc and Eric Wang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Nature Communications.

In The Last Decade

Justin B. Kinney

44 papers receiving 3.4k citations

Hit Papers

Discovery of cancer drug ... 2007 2026 2013 2019 2015 2007 2014 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Justin B. Kinney United States 24 2.3k 693 419 227 182 47 3.4k
Anirvan M. Sengupta India 28 1.3k 0.6× 424 0.6× 481 1.1× 343 1.5× 116 0.6× 204 3.8k
C. Barnes United Kingdom 37 1.9k 0.8× 774 1.1× 942 2.2× 1.5k 6.5× 181 1.0× 84 5.0k
Vésteinn Thórsson United States 20 3.3k 1.4× 389 0.6× 360 0.9× 214 0.9× 116 0.6× 44 4.9k
Carl Herrmann Germany 24 1.5k 0.7× 237 0.3× 164 0.4× 88 0.4× 46 0.3× 56 2.4k
Stephen A. Ramsey United States 30 2.3k 1.0× 260 0.4× 120 0.3× 178 0.8× 75 0.4× 92 3.9k
Frank Lee United States 39 1.8k 0.8× 1.3k 1.9× 2.1k 5.0× 75 0.3× 38 0.2× 183 5.4k
Joel Rozowsky United States 42 5.8k 2.5× 1.1k 1.5× 856 2.0× 400 1.8× 87 0.5× 79 7.7k
Charles K. Kaufman United States 21 1.3k 0.5× 220 0.3× 57 0.1× 28 0.1× 244 1.3× 56 2.8k
Andrew Grimshaw United States 25 643 0.3× 77 0.1× 133 0.3× 135 0.6× 580 3.2× 129 5.6k
Anthony J. Cox United States 26 1.9k 0.8× 991 1.4× 549 1.3× 23 0.1× 359 2.0× 102 4.5k

Countries citing papers authored by Justin B. Kinney

Since Specialization
Citations

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

Fields of papers citing papers by Justin B. Kinney

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Justin B. Kinney. 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 Justin B. Kinney. The network helps show where Justin B. Kinney may publish in the future.

Co-authorship network of co-authors of Justin B. Kinney

This figure shows the co-authorship network connecting the top 25 collaborators of Justin B. Kinney. A scholar is included among the top collaborators of Justin B. Kinney 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 Justin B. Kinney. Justin B. Kinney 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.
Martí‐Gómez, Carlos, et al.. (2026). Inference and Visualization of Complex Genotype–Phenotype Maps. Molecular Biology and Evolution. 43(2).
2.
Posfai, Anna, et al.. (2025). Gauge fixing for sequence-function relationships. PLoS Computational Biology. 21(3). e1012818–e1012818. 2 indexed citations
3.
Alpsoy, Aktan, Jonathan J. Ipsaro, Damianos Skopelitis, et al.. (2025). Structural basis of DNA-dependent coactivator recruitment by the tuft cell master regulator POU2F3. Cell Reports. 44(11). 116572–116572.
4.
Ishigami, Yuma, Mandy S. Wong, Carlos Martí‐Gómez, et al.. (2024). Specificity, synergy, and mechanisms of splice-modifying drugs. Nature Communications. 15(1). 1880–1880. 17 indexed citations
5.
Sun, Dianqing, et al.. (2023). Advancing Pharmacy Education by Moving From Sequenced “Integration” to True Curricular Integration. American Journal of Pharmaceutical Education. 87(6). 100056–100056. 10 indexed citations
6.
Wong, Mandy S., et al.. (2022). Higher-order epistasis and phenotypic prediction. Proceedings of the National Academy of Sciences. 119(39). e2204233119–e2204233119. 23 indexed citations
7.
Molodtsov, Vadim, Mahdi Kooshkbaghi, Ammar Tareen, et al.. (2022). Structural and mechanistic basis of σ-dependent transcriptional pausing. Proceedings of the National Academy of Sciences. 119(23). e2201301119–e2201301119. 8 indexed citations
8.
Li, Lingting, Yuanchao Zhang, Irina O. Vvedenskaya, et al.. (2021). Promoter-sequence determinants and structural basis of primer-dependent transcription initiation in Escherichia coli. Proceedings of the National Academy of Sciences. 118(27). 7 indexed citations
9.
Ireland, William T., Nicholas S. McCarty, Nathan M. Belliveau, et al.. (2020). Deciphering the regulatory genome of Escherichia coli, one hundred promoters at a time. eLife. 9. 31 indexed citations
10.
Tareen, Ammar & Justin B. Kinney. (2019). Logomaker: beautiful sequence logos in Python. Bioinformatics. 36(7). 2272–2274. 254 indexed citations
11.
Barnes, Stephanie L., Nathan M. Belliveau, William T. Ireland, Justin B. Kinney, & Rob Phillips. (2019). Mapping DNA sequence to transcription factor binding energy in vivo. PLoS Computational Biology. 15(2). e1006226–e1006226. 29 indexed citations
12.
Belliveau, Nathan M., Stephanie L. Barnes, William T. Ireland, et al.. (2018). Systematic approach for dissecting the molecular mechanisms of transcriptional regulation in bacteria. Proceedings of the National Academy of Sciences. 115(21). E4796–E4805. 60 indexed citations
13.
Jones, Daniel, et al.. (2018). Measuring cis-regulatory energetics in living cells using allelic manifolds. eLife. 7. 16 indexed citations
14.
Şentürk, Şerif, Nitin H. Shirole, Dawid G. Nowak, et al.. (2017). Rapid and tunable method to temporally control gene editing based on conditional Cas9 stabilization. Nature Communications. 8(1). 14370–14370. 133 indexed citations
15.
Ipsaro, Jonathan J., Chen Shen, Eri Arai, et al.. (2017). Rapid generation of drug-resistance alleles at endogenous loci using CRISPR-Cas9 indel mutagenesis. PLoS ONE. 12(2). e0172177–e0172177. 23 indexed citations
16.
Sheu, Yi-Jun, Justin B. Kinney, & Bruce Stillman. (2016). Concerted activities of Mcm4, Sld3, and Dbf4 in control of origin activation and DNA replication fork progression. Genome Research. 26(3). 315–330. 27 indexed citations
17.
Kinney, Justin B.. (2015). Unification of field theory and maximum entropy methods for learning probability densities. Physical Review E. 92(3). 32107–32107. 10 indexed citations
18.
Kinney, Justin B. & Gurinder S. Atwal. (2014). Equitability, mutual information, and the maximal information coefficient. Proceedings of the National Academy of Sciences. 111(9). 3354–3359. 435 indexed citations breakdown →
19.
Kinney, Justin B. & Gurinder S. Atwal. (2014). Parametric Inference in the Large Data Limit Using Maximally Informative Models. Neural Computation. 26(4). 637–653. 10 indexed citations
20.
Kinney, Justin B. & Gurinder S. Atwal. (2012). Maximally informative models and diffeomorphic modes in the analysis of large data sets. arXiv (Cornell University). 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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