Floriane Montanari

2.1k total citations · 1 hit paper
26 papers, 1.2k citations indexed

About

Floriane Montanari is a scholar working on Computational Theory and Mathematics, Molecular Biology and Pharmacology. According to data from OpenAlex, Floriane Montanari has authored 26 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computational Theory and Mathematics, 8 papers in Molecular Biology and 8 papers in Pharmacology. Recurrent topics in Floriane Montanari's work include Computational Drug Discovery Methods (19 papers), Drug Transport and Resistance Mechanisms (7 papers) and Machine Learning in Materials Science (5 papers). Floriane Montanari is often cited by papers focused on Computational Drug Discovery Methods (19 papers), Drug Transport and Resistance Mechanisms (7 papers) and Machine Learning in Materials Science (5 papers). Floriane Montanari collaborates with scholars based in Austria, Germany and Italy. Floriane Montanari's co-authors include Gerhard F. Ecker, Djork-Arné Clevert, Robin Winter, Frank Noé, Lara Kuhnke, Antonius ter Laak, Hans Briem, Andreas Steffen, Andreas H. Göller and Joerg Wichard and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Advanced Drug Delivery Reviews.

In The Last Decade

Floriane Montanari

26 papers receiving 1.2k 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.

Learning continuous and data-driven molecular descriptors by translating equivalent chemical representations

2018 326 citations Robin Winter, Floriane Montanari et al. Chemical Science profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Floriane Montanari Austria	17	801	587	458	166	135	26	1.2k
Elena Cibrián–Uhalte Germany	7	1.1k 1.4×	1.1k 1.9×	314 0.7×	140 0.8×	133 1.0×	9	1.8k
Alexander Sedykh United States	28	1.3k 1.6×	782 1.3×	412 0.9×	164 1.0×	311 2.3×	51	2.3k
Adrià Cereto‐Massagué Spain	12	872 1.1×	781 1.3×	252 0.6×	103 0.6×	67 0.5×	20	1.4k
María José Ojeda Spain	12	778 1.0×	677 1.2×	244 0.5×	104 0.6×	63 0.5×	20	1.3k
Ines Smit United Kingdom	5	1.1k 1.4×	1.0k 1.8×	316 0.7×	94 0.6×	148 1.1×	8	1.6k
H. C. Stephen Chan China	20	508 0.6×	983 1.7×	356 0.8×	80 0.5×	82 0.6×	33	1.9k
Jérémy Besnard United Kingdom	6	925 1.2×	863 1.5×	355 0.8×	86 0.5×	148 1.1×	10	1.6k
Youjun Xu China	13	873 1.1×	849 1.4×	446 1.0×	48 0.3×	139 1.0×	20	1.6k
Véronique Stoven France	19	645 0.8×	901 1.5×	146 0.3×	154 0.9×	133 1.0×	41	1.4k
G. Richard Bickerton United Kingdom	11	1.0k 1.3×	1.1k 1.8×	411 0.9×	103 0.6×	149 1.1×	12	1.8k

Countries citing papers authored by Floriane Montanari

Since Specialization

Citations

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

Fields of papers citing papers by Floriane Montanari

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Floriane Montanari

This figure shows the co-authorship network connecting the top 25 collaborators of Floriane Montanari. A scholar is included among the top collaborators of Floriane Montanari 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 Floriane Montanari. Floriane Montanari 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

Gadaleta, Domenico, et al.. (2025). Predicting Liver-Related In Vitro Endpoints with Machine Learning to Support Early Detection of Drug-Induced Liver Injury. Chemical Research in Toxicology. 38(4). 656–671. 1 indexed citations

Montanari, Floriane, et al.. (2024). Solvmate – a hybrid physical/ML approach to solvent recommendation leveraging a rank-based problem framework. Digital Discovery. 3(9). 1749–1760. 1 indexed citations

Montanari, Floriane, et al.. (2023). pH-dependent solubility prediction for optimized drug absorption and compound uptake by plants. Journal of Computer-Aided Molecular Design. 37(3). 129–145. 4 indexed citations

Heberle, Henry, et al.. (2022). ChemInformatics Model Explorer (CIME): exploratory analysis of chemical model explanations. Journal of Cheminformatics. 14(1). 21–21. 18 indexed citations

Montanari, Floriane, et al.. (2022). Modeling bioconcentration factors in fish with explainable deep learning. SHILAP Revista de lepidopterología. 2. 100047–100047. 8 indexed citations

Clevert, Djork-Arné, Tuan Le, Robin Winter, & Floriane Montanari. (2021). Img2Mol – accurate SMILES recognition from molecular graphical depictions. Chemical Science. 12(42). 14174–14181. 38 indexed citations

Göller, Andreas H., Lara Kuhnke, Floriane Montanari, et al.. (2020). Bayer’s in silico ADMET platform: a journey of machine learning over the past two decades. Drug Discovery Today. 25(9). 1702–1709. 119 indexed citations

Montanari, Floriane, et al.. (2020). Vienna LiverTox Workspace—A Set of Machine Learning Models for Prediction of Interactions Profiles of Small Molecules With Transporters Relevant for Regulatory Agencies. Frontiers in Chemistry. 7. 899–899. 21 indexed citations

Winter, Robin, Floriane Montanari, Andreas Steffen, et al.. (2019). Efficient multi-objective molecular optimization in a continuous latent space. Chemical Science. 10(34). 8016–8024. 156 indexed citations

10.

Montanari, Floriane, Lara Kuhnke, Antonius ter Laak, & Djork-Arné Clevert. (2019). Modeling Physico-Chemical ADMET Endpoints with Multitask Graph Convolutional Networks. Molecules. 25(1). 44–44. 70 indexed citations

11.

Winter, Robin, Floriane Montanari, Frank Noé, & Djork-Arné Clevert. (2018). Learning continuous and data-driven molecular descriptors by translating equivalent chemical representations. Chemical Science. 10(6). 1692–1701. 326 indexed citations breakdown →

12.

Montanari, Floriane, et al.. (2017). Predicting drug-induced liver injury: The importance of data curation. Toxicology. 389. 139–145. 56 indexed citations

13.

Montanari, Floriane, et al.. (2016). Virtual Screening of DrugBank Reveals Two Drugs as New BCRP Inhibitors. SLAS DISCOVERY. 22(1). 86–93. 26 indexed citations

14.

Montanari, Floriane, Barbara Zdrazil, Daniela Digles, & Gerhard F. Ecker. (2016). Selectivity profiling of BCRP versus P-gp inhibition: from automated collection of polypharmacology data to multi-label learning. Journal of Cheminformatics. 8(1). 7–7. 24 indexed citations

15.

Montanari, Floriane, Katrin Wlcek, Peter Chiba, et al.. (2016). Subtle Structural Differences Trigger Inhibitory Activity of Propafenone Analogues at the Two Polyspecific ABC Transporters: P‐Glycoprotein (P‐gp) and Breast Cancer Resistance Protein (BCRP). ChemMedChem. 11(12). 1380–1394. 16 indexed citations

16.

Sanz, Ferrán, Luigi Capoferri, Nico Vermeulen, et al.. (2015). Integrative Modeling Strategies for Predicting Drug Toxicities at the eTOX Project. Molecular Informatics. 34(6-7). 477–484. 10 indexed citations

17.

Montanari, Floriane & Gerhard F. Ecker. (2015). Prediction of drug–ABC-transporter interaction — Recent advances and future challenges. Advanced Drug Delivery Reviews. 86. 17–26. 194 indexed citations

18.

Montanari, Floriane, et al.. (2014). Exploiting Open Data: A New Era in Pharmacoinformatics. Future Medicinal Chemistry. 6(5). 503–514. 16 indexed citations

19.

Montanari, Floriane & Gerhard F. Ecker. (2014). BCRP Inhibition: from Data Collection to Ligand‐Based Modeling. Molecular Informatics. 33(5). 322–331. 23 indexed citations

20.

Montanari, Floriane, Denis C. Shields, & Nora Khaldi. (2011). Differences in the Number of Intrinsically Disordered Regions between Yeast Duplicated Proteins, and Their Relationship with Functional Divergence. PLoS ONE. 6(9). e24989–e24989. 11 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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