Jackson Chief Elk

412 total citations · 1 hit paper
5 papers, 194 citations indexed

About

Jackson Chief Elk is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Jackson Chief Elk has authored 5 papers receiving a total of 194 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 3 papers in Computational Theory and Mathematics and 3 papers in Materials Chemistry. Recurrent topics in Jackson Chief Elk's work include Computational Drug Discovery Methods (3 papers), Machine Learning in Materials Science (2 papers) and Protein Structure and Dynamics (1 paper). Jackson Chief Elk is often cited by papers focused on Computational Drug Discovery Methods (3 papers), Machine Learning in Materials Science (2 papers) and Protein Structure and Dynamics (1 paper). Jackson Chief Elk collaborates with scholars based in United States. Jackson Chief Elk's co-authors include Matthew P. Repasky, Steven V. Jerome, David R. Calkins, Karl Leswing, John C. Shelley, Ryne C. Johnston, Kun Yao, Ilan Benjamin, Mohammad Atif Faiz Afzal and Andrea Browning and has published in prestigious journals such as Langmuir, Journal of Chemical Theory and Computation and Journal of Chemical Information and Modeling.

In The Last Decade

Jackson Chief Elk

5 papers receiving 191 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Epik: p K _a and Protonation State Prediction through Machine Learning

2023 130 citations Ryne C. Johnston, Kun Yao et al. Journal of Chemical Theory and Computation profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jackson Chief Elk United States	4	73	65	43	37	17	5	194
Egidijus Kazlauskas Lithuania	8	210 2.9×	99 1.5×	34 0.8×	62 1.7×	12 0.7×	14	286
Szymon Pach Germany	8	146 2.0×	119 1.8×	24 0.6×	64 1.7×	31 1.8×	13	283
David Schaller Germany	7	161 2.2×	123 1.9×	28 0.7×	91 2.5×	40 2.4×	14	291
Agata Kranjc Italy	11	194 2.7×	34 0.5×	33 0.8×	60 1.6×	11 0.6×	18	326
Carlos Ramírez-Palacios Netherlands	7	224 3.1×	46 0.7×	63 1.5×	46 1.2×	8 0.5×	10	288
Antonius P. A. Janssen Netherlands	10	141 1.9×	68 1.0×	22 0.5×	78 2.1×	76 4.5×	24	267
Stefania Pfeiffer‐Marek Germany	11	254 3.5×	78 1.2×	48 1.1×	21 0.6×	19 1.1×	14	329
Magdalena Korczynska United States	8	270 3.7×	61 0.9×	37 0.9×	30 0.8×	28 1.6×	12	305
Karthikeyan Swaminathan United States	5	99 1.4×	91 1.4×	28 0.7×	14 0.4×	5 0.3×	10	197
Martin Šrejber Czechia	7	180 2.5×	48 0.7×	11 0.3×	29 0.8×	20 1.2×	14	291

Countries citing papers authored by Jackson Chief Elk

Since Specialization

Citations

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

Fields of papers citing papers by Jackson Chief Elk

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jackson Chief Elk. 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 Jackson Chief Elk. The network helps show where Jackson Chief Elk may publish in the future.

Co-authorship network of co-authors of Jackson Chief Elk

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

All Works

Sort: Min cites: Since: Top N: Style:

5 of 5 papers shown

1.

Paull, Evan, Phani Ghanakota, Jackson Chief Elk, et al.. (2025). Predicting Resistance to Small Molecule Kinase Inhibitors. Journal of Chemical Information and Modeling. 65(5). 2543–2557. 1 indexed citations

2.

Chew, Alex K., Anand Chandrasekaran, Jackson Chief Elk, et al.. (2024). Advancing material property prediction: using physics-informed machine learning models for viscosity. Journal of Cheminformatics. 16(1). 31–31. 40 indexed citations

3.

Johnston, Ryne C., Kun Yao, Karl Leswing, et al.. (2023). Epik: p K _a and Protonation State Prediction through Machine Learning. Journal of Chemical Theory and Computation. 19(8). 2380–2388. 130 indexed citations breakdown →

4.

Svensson, Mats, Mitsunori Kato, Karen H. Dingley, et al.. (2023). A Computational Physics-based Approach to Predict Unbound Brain-to-Plasma Partition Coefficient, K _p,uu. Journal of Chemical Information and Modeling. 63(12). 3786–3798. 11 indexed citations

5.

Elk, Jackson Chief & Ilan Benjamin. (2015). β-Cyclodextrin at the Water/1-Bromobutane Interface: Molecular Insight into Reverse Phase Transfer Catalysis. Langmuir. 31(18). 5086–5092. 12 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.

Explore authors with similar magnitude of impact