Johan Ulander

1.9k total citations
33 papers, 1.3k citations indexed

About

Johan Ulander is a scholar working on Molecular Biology, Computational Theory and Mathematics and Physical and Theoretical Chemistry. According to data from OpenAlex, Johan Ulander has authored 33 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 10 papers in Computational Theory and Mathematics and 9 papers in Physical and Theoretical Chemistry. Recurrent topics in Johan Ulander's work include Computational Drug Discovery Methods (10 papers), Protein Structure and Dynamics (8 papers) and Spectroscopy and Quantum Chemical Studies (7 papers). Johan Ulander is often cited by papers focused on Computational Drug Discovery Methods (10 papers), Protein Structure and Dynamics (8 papers) and Spectroscopy and Quantum Chemical Studies (7 papers). Johan Ulander collaborates with scholars based in Sweden, United States and United Kingdom. Johan Ulander's co-authors include Garegin A. Papoian, Peter G. Wolynes, Roland Kjellander, Michael P. Eastwood, Zaida Luthey‐Schulten, A. D. J. Haymet, Hong Wan, Patrik Johansson, Stefan Geschwindner and Christian Tyrchan and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Nature Communications.

In The Last Decade

Johan Ulander

32 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Johan Ulander Sweden 19 777 315 227 196 175 33 1.3k
Tom Young United States 5 1.1k 1.4× 284 0.9× 314 1.4× 472 2.4× 138 0.8× 5 1.4k
Frank M. DiCapua United States 9 854 1.1× 229 0.7× 322 1.4× 212 1.1× 100 0.6× 9 1.3k
Paul Beroza United States 21 1.2k 1.6× 276 0.9× 384 1.7× 362 1.8× 131 0.7× 32 1.8k
Milan Hodošček Slovenia 24 1.1k 1.4× 411 1.3× 474 2.1× 203 1.0× 194 1.1× 84 1.9k
Mikael Peräkylä Finland 28 980 1.3× 237 0.8× 180 0.8× 185 0.9× 137 0.8× 79 2.0k
Changge Ji China 17 630 0.8× 268 0.9× 160 0.7× 308 1.6× 63 0.4× 34 1.1k
Hironori Kokubo Japan 19 866 1.1× 271 0.9× 236 1.0× 193 1.0× 55 0.3× 33 1.2k
Lin Frank Song United States 14 769 1.0× 345 1.1× 236 1.0× 220 1.1× 109 0.6× 33 1.5k
Chung F. Wong United States 24 1.4k 1.8× 306 1.0× 302 1.3× 460 2.3× 127 0.7× 86 2.0k
Niel M. Henriksen United States 21 857 1.1× 267 0.8× 181 0.8× 213 1.1× 229 1.3× 31 1.3k

Countries citing papers authored by Johan Ulander

Since Specialization
Citations

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

Fields of papers citing papers by Johan Ulander

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Johan Ulander

This figure shows the co-authorship network connecting the top 25 collaborators of Johan Ulander. A scholar is included among the top collaborators of Johan Ulander 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 Johan Ulander. Johan Ulander 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.
Tesei, Giulio, Ya‐Wen Hsiao, Aleksandra P. Dabkowska, et al.. (2024). Lipid shape and packing are key for optimal design of pH-sensitive mRNA lipid nanoparticles. Proceedings of the National Academy of Sciences. 121(2). e2311700120–e2311700120. 33 indexed citations
2.
Ulander, Johan. (2024). Boundary-preserving Lamperti-splitting schemes for some stochastic differential equations. 11(3). 289–317. 1 indexed citations
3.
Bréhier, Charles-Édouard, David Cohen, & Johan Ulander. (2024). Analysis of a positivity-preserving splitting scheme for some semilinear stochastic heat equations. ESAIM. Mathematical modelling and numerical analysis. 58(4). 1317–1346.
4.
Liu, Kai, Ralf Nilsson, Elisa Lázaro‐Ibáñez, et al.. (2023). Multiomics analysis of naturally efficacious lipid nanoparticle coronas reveals high-density lipoprotein is necessary for their function. Nature Communications. 14(1). 4007–4007. 66 indexed citations
5.
Audagnotto, Martina, Werngard Czechtizky, Leonardo De Maria, et al.. (2022). Machine learning/molecular dynamic protein structure prediction approach to investigate the protein conformational ensemble. Scientific Reports. 12(1). 10018–10018. 22 indexed citations
6.
Pettersen, Daniel, Johan Broddefalk, Hans Emtenäs, et al.. (2019). Discovery and Early Clinical Development of an Inhibitor of 5-Lipoxygenase Activating Protein (AZD5718) for Treatment of Coronary Artery Disease. Journal of Medicinal Chemistry. 62(9). 4312–4324. 31 indexed citations
7.
Lemurell, Malin, Johan Ulander, Hans Emtenäs, et al.. (2019). Novel Chemical Series of 5-Lipoxygenase-Activating Protein Inhibitors for Treatment of Coronary Artery Disease. Journal of Medicinal Chemistry. 62(9). 4325–4349. 11 indexed citations
8.
Grebner, Christoph, Daniel Lecina, V. Gil, et al.. (2017). Exploring Binding Mechanisms in Nuclear Hormone Receptors by Monte Carlo and X-ray-derived Motions. Biophysical Journal. 112(6). 1147–1156. 18 indexed citations
9.
Williams, Glyn, György G. Ferenczy, Johan Ulander, & György M. Keserű. (2016). Binding thermodynamics discriminates fragments from druglike compounds: a thermodynamic description of fragment-based drug discovery. Drug Discovery Today. 22(4). 681–689. 18 indexed citations
10.
Krämer, Christian, Göran Dahl, Christian Tyrchan, & Johan Ulander. (2016). A comprehensive company database analysis of biological assay variability. Drug Discovery Today. 21(8). 1213–1221. 24 indexed citations
11.
Grebner, Christoph, Jessica Iegre, Johan Ulander, et al.. (2016). Binding Mode and Induced Fit Predictions for Prospective Computational Drug Design. Journal of Chemical Information and Modeling. 56(4). 774–787. 26 indexed citations
12.
Fagerberg, Jonas H., Εva Karlsson, Johan Ulander, Gunilla Hanisch, & Christel A. S. Bergström. (2014). Computational Prediction of Drug Solubility in Fasted Simulated and Aspirated Human Intestinal Fluid. Pharmaceutical Research. 32(2). 578–589. 55 indexed citations
13.
Gustafsson, David, Jane McPheat, Fredrik Wågberg, et al.. (2013). A serendipitously identified novel small molecule procoagulant compound giving rise to a high-throughput screening assay based on human plasma. Thrombosis Research. 132(2). 248–255. 2 indexed citations
14.
Gabrielsson, Johan, Ola Fjellström, Johan Ulander, Michael Rowley, & Piet H. van der Graaf. (2011). Pharmacodynamic-Pharmacokinetic Integration as a Guide to Medicinal Chemistry. Current Topics in Medicinal Chemistry. 11(4). 404–418. 24 indexed citations
15.
Wan, Hong, Lars-Olof Larsson, Johan Ulander, et al.. (2010). Impact of Input Parameters on the Prediction of Hepatic Plasma Clearance Using the Well-Stirred Model. Current Drug Metabolism. 11(7). 583–594. 17 indexed citations
16.
Zong, Chenghang, Garegin A. Papoian, Johan Ulander, & Peter G. Wolynes. (2006). Role of Topology, Nonadditivity, and Water-Mediated Interactions in Predicting the Structures of α/β Proteins. Journal of the American Chemical Society. 128(15). 5168–5176. 29 indexed citations
17.
Wan, Hong & Johan Ulander. (2006). High-throughput pKascreening and prediction amenable for ADME profiling. Expert Opinion on Drug Metabolism & Toxicology. 2(1). 139–155. 66 indexed citations
18.
Ulander, Johan & A. D. J. Haymet. (2003). Permeation Across Hydrated DPPC Lipid Bilayers: Simulation of the Titrable Amphiphilic Drug Valproic Acid. Biophysical Journal. 85(6). 3475–3484. 97 indexed citations
19.
Kjellander, Roland & Johan Ulander. (2000). Charge renormalization and asymptotic decay in classical Coulomb systems. Journal de Physique IV (Proceedings). 10(PR5). Pr5–431. 1 indexed citations
20.

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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