Maria Mateescu

464 total citations
10 papers, 141 citations indexed

About

Maria Mateescu is a scholar working on Molecular Biology, Computational Theory and Mathematics and Physical and Theoretical Chemistry. According to data from OpenAlex, Maria Mateescu has authored 10 papers receiving a total of 141 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 2 papers in Computational Theory and Mathematics and 2 papers in Physical and Theoretical Chemistry. Recurrent topics in Maria Mateescu's work include Gene Regulatory Network Analysis (9 papers), Microbial Metabolic Engineering and Bioproduction (6 papers) and Bioinformatics and Genomic Networks (5 papers). Maria Mateescu is often cited by papers focused on Gene Regulatory Network Analysis (9 papers), Microbial Metabolic Engineering and Bioproduction (6 papers) and Bioinformatics and Genomic Networks (5 papers). Maria Mateescu collaborates with scholars based in Austria, Switzerland and Germany. Maria Mateescu's co-authors include Thomas A. Henzinger, Verena Wolf, Jasmin Fisher and Nir Piterman and has published in prestigious journals such as Theoretical Computer Science, BMC Systems Biology and IEEE/ACM Transactions on Computational Biology and Bioinformatics.

In The Last Decade

Maria Mateescu

10 papers receiving 132 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Maria Mateescu Austria	5	120	30	27	16	13	10	141
Russ Harmer France	5	145 1.2×	36 1.2×	12 0.4×	5 0.3×	10 0.8×	8	181
Yannik Schälte Germany	8	66 0.6×	6 0.2×	16 0.6×	9 0.6×	13 1.0×	14	152
Mathilde Noual France	9	156 1.3×	53 1.8×	38 1.4×	3 0.2×	8 0.6×	13	197
Andre Skusa Germany	5	217 1.8×	18 0.6×	19 0.7×	6 0.4×	10 0.8×	8	245
Étienne Roquain France	9	43 0.4×	6 0.2×	14 0.5×	39 2.4×	5 0.4×	28	199
John D. Eblen United States	5	47 0.4×	27 0.9×	6 0.2×	4 0.3×	13 1.0×	7	113
Mercedes Pérez Millán Argentina	7	137 1.1×	62 2.1×	4 0.1×	3 0.2×	17 1.3×	9	184
Sergey Petoukhov Russia	8	127 1.1×	7 0.2×	24 0.9×	1 0.1×	9 0.7×	39	210
Vida Ravanmehr United States	5	110 0.9×	21 0.7×	58 2.1×	3 0.2×	5 0.4×	15	168
Lutz Strüngmann Germany	12	302 2.5×	49 1.6×	81 3.0×	4 0.3×	2 0.2×	70	428

Countries citing papers authored by Maria Mateescu

Since Specialization

Citations

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

Fields of papers citing papers by Maria Mateescu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maria Mateescu

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

All Works

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10 of 10 papers shown

1.

Henzinger, Thomas A. & Maria Mateescu. (2012). The Propagation Approach for Computing Biochemical Reaction Networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 10(2). 310–322. 1 indexed citations

2.

Henzinger, Thomas A. & Maria Mateescu. (2011). Tail approximation for the chemical master equation. 2 indexed citations

3.

Henzinger, Thomas A. & Maria Mateescu. (2011). Propagation models for computing biochemical reaction networks. 1–3. 2 indexed citations

4.

Wolf, Verena, et al.. (2010). Solving the chemical master equation using sliding windows. BMC Systems Biology. 4(1). 42–42. 53 indexed citations

5.

Henzinger, Thomas A., et al.. (2010). SABRE: A Tool for Stochastic Analysis of Biochemical Reaction Networks. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 193–194. 7 indexed citations

6.

Henzinger, Thomas A., et al.. (2010). Approximation of event probabilities in noisy cellular processes. Theoretical Computer Science. 412(21). 2128–2141. 1 indexed citations

7.

Henzinger, Thomas A., et al.. (2010). Hybrid numerical solution of the chemical master equation. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 55–65. 23 indexed citations

8.

Mateescu, Maria, et al.. (2010). Fast adaptive uniformisation of the chemical master equation. IET Systems Biology. 4(6). 441–452. 24 indexed citations

9.

Henzinger, Thomas A., et al.. (2009). Fast Adaptive Uniformization of the Chemical Master Equation. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 118–127. 27 indexed citations

10.

Fisher, Jasmin, Thomas A. Henzinger, Maria Mateescu, & Nir Piterman. (2007). Bounded Asynchrony: A Biologically Inspired Notion of Concurrency. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 1 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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