Roland Mathis

668 total citations · 1 hit paper
7 papers, 389 citations indexed

About

Roland Mathis is a scholar working on Molecular Biology, Computational Theory and Mathematics and Sociology and Political Science. According to data from OpenAlex, Roland Mathis has authored 7 papers receiving a total of 389 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 2 papers in Computational Theory and Mathematics and 1 paper in Sociology and Political Science. Recurrent topics in Roland Mathis's work include Gene Regulatory Network Analysis (3 papers), Bioinformatics and Genomic Networks (2 papers) and Computational Drug Discovery Methods (2 papers). Roland Mathis is often cited by papers focused on Gene Regulatory Network Analysis (3 papers), Bioinformatics and Genomic Networks (2 papers) and Computational Drug Discovery Methods (2 papers). Roland Mathis collaborates with scholars based in Switzerland, Australia and Germany. Roland Mathis's co-authors include Matteo Manica, Evangelos Eleftheriou, Heiner Giefers, Alessandro Curioni, Abu Sebastian, Tomáš Tůma, Manuel Le Gallo, Costas Bekas, María Rodríguez Martínez and Martin Ackermann and has published in prestigious journals such as Bioinformatics, BMC Evolutionary Biology and Nature Electronics.

In The Last Decade

Roland Mathis

6 papers receiving 383 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.

Mixed-precision in-memory computing

2018 333 citations Manuel Le Gallo, Abu Sebastian et al. Nature Electronics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Roland Mathis Switzerland	5	312	95	82	56	40	7	389
Shin-Hee Han South Korea	10	419 1.3×	90 0.9×	46 0.6×	91 1.6×	81 2.0×	20	590
Advait Madhavan United States	12	383 1.2×	144 1.5×	73 0.9×	17 0.3×	37 0.9×	37	483
Evgeny Pikhay Israel	10	380 1.2×	50 0.5×	79 1.0×	41 0.7×	30 0.8×	42	439
Zhan Liu United States	6	309 1.0×	142 1.5×	48 0.6×	45 0.8×	13 0.3×	6	391
Loai Danial Israel	8	267 0.9×	84 0.9×	97 1.2×	24 0.4×	30 0.8×	17	317
Yasmin Halawani United Arab Emirates	9	268 0.9×	62 0.7×	79 1.0×	25 0.4×	8 0.2×	29	318
Yoon Ho Jang South Korea	11	381 1.2×	186 2.0×	95 1.2×	72 1.3×	14 0.3×	34	440
Yaoyu Tao China	11	253 0.8×	79 0.8×	30 0.4×	17 0.3×	53 1.3×	32	336
Siyan Lin China	7	348 1.1×	57 0.6×	120 1.5×	73 1.3×	12 0.3×	19	432
Janguk Han South Korea	10	395 1.3×	180 1.9×	120 1.5×	26 0.5×	17 0.4×	29	431

Countries citing papers authored by Roland Mathis

Since Specialization

Citations

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

Fields of papers citing papers by Roland Mathis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roland Mathis

This figure shows the co-authorship network connecting the top 25 collaborators of Roland Mathis. A scholar is included among the top collaborators of Roland Mathis 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 Roland Mathis. Roland Mathis 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:

7 of 7 papers shown

1.

Mathis, Roland, et al.. (2024). Reliable LLM-based User Simulator for Task-Oriented Dialogue Systems. 19–35.

2.

Manica, Matteo, Roland Mathis, Peter G. Hains, et al.. (2021). On the feasibility of deep learning applications using raw mass spectrometry data. Bioinformatics. 37(Supplement_1). i245–i253. 10 indexed citations

3.

Manica, Matteo, Charlotte Bunne, Roland Mathis, et al.. (2020). COSIFER: a Python package for the consensus inference of molecular interaction networks. Bioinformatics. 37(14). 2070–2072. 5 indexed citations

4.

Manica, Matteo, et al.. (2019). PIMKL: Pathway-Induced Multiple Kernel Learning. npj Systems Biology and Applications. 5(1). 8–8. 23 indexed citations

5.

Manica, Matteo, et al.. (2019). FPGA Accelerated Analysis of Boolean Gene Regulatory Networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 17(6). 2141–2147. 3 indexed citations

6.

Gallo, Manuel Le, Abu Sebastian, Roland Mathis, et al.. (2018). Mixed-precision in-memory computing. Nature Electronics. 1(4). 246–253. 333 indexed citations breakdown →

7.

Mathis, Roland & Martin Ackermann. (2017). Asymmetric cellular memory in bacteria exposed to antibiotics. BMC Evolutionary Biology. 17(1). 73–73. 15 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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