Ernst Ahlberg

1.0k total citations
26 papers, 338 citations indexed

About

Ernst Ahlberg is a scholar working on Computational Theory and Mathematics, Molecular Biology and Materials Chemistry. According to data from OpenAlex, Ernst Ahlberg has authored 26 papers receiving a total of 338 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computational Theory and Mathematics, 6 papers in Molecular Biology and 5 papers in Materials Chemistry. Recurrent topics in Ernst Ahlberg's work include Computational Drug Discovery Methods (17 papers), Machine Learning in Materials Science (5 papers) and Analytical Chemistry and Chromatography (4 papers). Ernst Ahlberg is often cited by papers focused on Computational Drug Discovery Methods (17 papers), Machine Learning in Materials Science (5 papers) and Analytical Chemistry and Chromatography (4 papers). Ernst Ahlberg collaborates with scholars based in Sweden, United Kingdom and Netherlands. Ernst Ahlberg's co-authors include Lars Carlsson, Ulf Norinder, Scott Boyer, Ola Engkvist, Hongming Chen, Elisabet Ahlberg, Jiangming Sun, Kari Laasonen, Michael Busch and Glenn J. Myatt and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Toxicological Sciences.

In The Last Decade

Ernst Ahlberg

24 papers receiving 326 citations

Peers

Ernst Ahlberg

CTM

Zheng Du China

Heather L. Ciallella United States

Natália Aniceto Portugal

Gabriel Idakwo United States

Tevfik Kizilören United Kingdom

Ricardo Arcila United Kingdom

Sybilla Corbett United Kingdom

Linlin Zhao United States

Mohan Rao United States

Emma J. Manners United Kingdom

Zheng Du China

Ernst Ahlberg

235 ×1.4

CTM

139 ×1.1

51 ×1.1

24 ×0.6

39 ×1.4

Citations per year, relative to Ernst Ahlberg Ernst Ahlberg (= 1×) peers Zheng Du

Countries citing papers authored by Ernst Ahlberg

Since Specialization

Citations

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

Fields of papers citing papers by Ernst Ahlberg

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ernst Ahlberg

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

All Works

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20 of 20 papers shown

Löfström, Tuve, et al.. (2025). Classification with reject option: Distribution-free error guarantees via conformal prediction. Machine Learning with Applications. 20. 100664–100664.

Norinder, Ulf, et al.. (2024). CPSign: conformal prediction for cheminformatics modeling. Journal of Cheminformatics. 16(1). 75–75. 4 indexed citations

Busch, Michael, Ernst Ahlberg, Elisabet Ahlberg, & Kari Laasonen. (2022). How to Predict the pK_a of Any Compound in Any Solvent. ACS Omega. 7(20). 17369–17383. 28 indexed citations

Ahlberg, Ernst, et al.. (2022). On the selection of relevant historical demand data for revenue management applied to transportation. Journal of Revenue and Pricing Management. 22(4). 266–275.

Oucheikh, Rachid, Tuve Löfström, Ernst Ahlberg, & Lars Carlsson. (2021). Rolling Cargo Management Using a Deep Reinforcement Learning Approach. SHILAP Revista de lepidopterología. 5(1). 10–10. 12 indexed citations

Buendía, Rubén, Thierry Kogej, Ola Engkvist, et al.. (2019). Accurate Hit Estimation for Iterative Screening Using Venn–ABERS Predictors. Journal of Chemical Information and Modeling. 59(3). 1230–1237. 6 indexed citations

Norinder, Ulf, Ernst Ahlberg, & Lars Carlsson. (2018). Predicting Ames Mutagenicity Using Conformal Prediction in the Ames/QSAR International Challenge Project. Mutagenesis. 34(1). 33–40. 11 indexed citations

Norinder, Ulf, Glenn J. Myatt, & Ernst Ahlberg. (2018). Predicting Aromatic Amine Mutagenicity with Confidence: A Case Study Using Conformal Prediction. Biomolecules. 8(3). 85–85. 20 indexed citations

Lampa, Samuel, et al.. (2018). Predicting Off-Target Binding Profiles With Confidence Using Conformal Prediction. Frontiers in Pharmacology. 9. 1256–1256. 24 indexed citations

10.

Sjögren, Anna-Karin, Ernst Ahlberg, Mikael Persson, et al.. (2018). A novel multi-parametric high content screening assay in ciPTEC-OAT1 to predict drug-induced nephrotoxicity during drug discovery. Archives of Toxicology. 92(10). 3175–3190. 25 indexed citations

11.

Ahlberg, Ernst, Rubén Buendía, & Lars Carlsson. (2018). Using Venn-Abers predictors to assess cardio-vascular risk.. 132–146. 3 indexed citations

12.

Winiwarter, Susanne, et al.. (2018). In silico ADME in drug design – enhancing the impact. ADMET & DMPK. 6(1). 15–15. 17 indexed citations

13.

Buendía, Rubén, Ola Engkvist, Lars Carlsson, Thierry Kogej, & Ernst Ahlberg. (2018). Venn-Abers predictors for improved compound iterative screening in drug discovery. 201–219. 1 indexed citations

14.

Lamore, Sarah D., Ernst Ahlberg, Scott Boyer, et al.. (2017). Deconvoluting Kinase Inhibitor Induced Cardiotoxicity. Toxicological Sciences. 158(1). 213–226. 33 indexed citations

15.

Ahlberg, Ernst, Claus Bendtsen, Lars Carlsson, et al.. (2017). Use of in silico models for compound property prediction to reduce the in vitro screening burden. Toxicology Letters. 280. S285–S285. 1 indexed citations

16.

Ahlberg, Ernst, et al.. (2017). Current application of conformal prediction in drug discovery. Annals of Mathematics and Artificial Intelligence. 81(1-2). 145–154. 4 indexed citations

17.

Carlsson, Lars, Claus Bendtsen, & Ernst Ahlberg. (2017). Comparing Performance of Different Inductive and Transductive Conformal Predictors Relevant to Drug Discovery.. 201–212. 2 indexed citations

18.

Chen, Hongming, et al.. (2017). Predicting the Risk of Phospholipidosis with in Silico Models and an Image-Based in Vitro Screen. Molecular Pharmaceutics. 14(12). 4346–4352. 9 indexed citations

19.

Lopes, Pedro, David Campos, Laura I. Furlong, et al.. (2013). Gathering and Exploring Scientific Knowledge in Pharmacovigilance. PLoS ONE. 8(12). e83016–e83016. 17 indexed citations

20.

Oliveira, José Luís, Pedro Lopes, David Campos, et al.. (2012). The EU‐ADR Web Platform: delivering advanced pharmacovigilance tools. Pharmacoepidemiology and Drug Safety. 22(5). 459–467. 33 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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