Maria Pires Pacheco

1.2k total citations
24 papers, 512 citations indexed

About

Maria Pires Pacheco is a scholar working on Molecular Biology, Physiology and Computational Theory and Mathematics. According to data from OpenAlex, Maria Pires Pacheco has authored 24 papers receiving a total of 512 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 4 papers in Physiology and 3 papers in Computational Theory and Mathematics. Recurrent topics in Maria Pires Pacheco's work include Microbial Metabolic Engineering and Bioproduction (12 papers), Bioinformatics and Genomic Networks (11 papers) and Metabolomics and Mass Spectrometry Studies (5 papers). Maria Pires Pacheco is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (12 papers), Bioinformatics and Genomic Networks (11 papers) and Metabolomics and Mass Spectrometry Studies (5 papers). Maria Pires Pacheco collaborates with scholars based in Luxembourg, Germany and Denmark. Maria Pires Pacheco's co-authors include Thomas Sauter, Nikos Vlassis, Thomas Pfau, Serge Haan, Elisabeth Letellier, Dagmar Kulms, Dominik Ternes, Paul Wilmes, Lasse Sinkkonen and Almut Heinken and has published in prestigious journals such as Molecules, Cell Reports and PLoS Computational Biology.

In The Last Decade

Maria Pires Pacheco

22 papers receiving 509 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Maria Pires Pacheco Luxembourg 11 422 85 41 36 35 24 512
Mihail Anton Sweden 8 666 1.6× 198 2.3× 41 1.0× 31 0.9× 47 1.3× 10 735
Chaoran Zhao China 8 355 0.8× 49 0.6× 47 1.1× 12 0.3× 16 0.5× 17 416
Ding Ma China 10 210 0.5× 37 0.4× 46 1.1× 13 0.4× 30 0.9× 38 363
Johan Gustafsson Sweden 8 382 0.9× 52 0.6× 46 1.1× 20 0.6× 40 1.1× 14 444
Pınar Kocabaş Türkiye 6 306 0.7× 51 0.6× 36 0.9× 19 0.5× 34 1.0× 9 361
Mark F. Ciaccio United States 9 282 0.7× 31 0.4× 22 0.5× 23 0.6× 14 0.4× 11 403
Tracy Walker United Kingdom 9 171 0.4× 78 0.9× 16 0.4× 14 0.4× 29 0.8× 11 397
Isha Gaurav India 8 187 0.4× 49 0.6× 88 2.1× 14 0.4× 28 0.8× 18 311

Countries citing papers authored by Maria Pires Pacheco

Since Specialization
Citations

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

Fields of papers citing papers by Maria Pires Pacheco

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maria Pires Pacheco

This figure shows the co-authorship network connecting the top 25 collaborators of Maria Pires Pacheco. A scholar is included among the top collaborators of Maria Pires Pacheco 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 Pires Pacheco. Maria Pires Pacheco 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.
Pacheco, Maria Pires, Déborah Gérard, Riley J. Mangan, et al.. (2025). Epigenetic control of metabolic identity across cell types. BMC Genomics. 27(1). 22–22.
2.
Žagare, Alise, Thomas Sauter, Maria Pires Pacheco, et al.. (2025). MIRO1 mutation leads to metabolic maladaptation resulting in Parkinson’s disease-associated dopaminergic neuron loss. npj Systems Biology and Applications. 11(1). 37–37.
3.
Pacheco, Maria Pires, et al.. (2024). Metabolic models predict fotemustine and the combination of eflornithine/rifamycin and adapalene/cannabidiol for the treatment of gliomas. Briefings in Bioinformatics. 25(3). 1 indexed citations
4.
Frías, Alex, Luca Di Leo, Asier Antoranz, et al.. (2023). Ambra1 modulates the tumor immune microenvironment and response to PD-1 blockade in melanoma. Journal for ImmunoTherapy of Cancer. 11(3). e006389–e006389. 5 indexed citations
5.
Pacheco, Maria Pires, Demetra Philippidou, Christiane Margue, et al.. (2023). Metabolic modelling-based in silico drug target prediction identifies six novel repurposable drugs for melanoma. Cell Death and Disease. 14(7). 468–468. 3 indexed citations
6.
Sauter, Thomas, et al.. (2022). Project-based learning course on metabolic network modelling in computational systems biology. PLoS Computational Biology. 18(1). e1009711–e1009711. 6 indexed citations
7.
Pacheco, Maria Pires, et al.. (2022). Drug Target Prediction Using Context-Specific Metabolic Models Reconstructed from rFASTCORMICS. Methods in molecular biology. 2535. 221–240. 4 indexed citations
8.
Pacheco, Maria Pires, Tony Heurtaux, Lasse Sinkkonen, et al.. (2022). Review of Current Human Genome-Scale Metabolic Models for Brain Cancer and Neurodegenerative Diseases. Cells. 11(16). 2486–2486. 4 indexed citations
9.
Pacheco, Maria Pires, et al.. (2021). Importance of the biomass formulation for cancer metabolic modeling and drug prediction. iScience. 24(10). 103110–103110. 10 indexed citations
10.
Pfau, Thomas, et al.. (2021). A dynamic multi-tissue model to study human metabolism. npj Systems Biology and Applications. 7(1). 5–5. 14 indexed citations
11.
Pacheco, Maria Pires, et al.. (2021). DCcov: Repositioning of drugs and drug combinations for SARS-CoV-2 infected lung through constraint-based modeling. iScience. 24(11). 103331–103331. 14 indexed citations
12.
Pacheco, Maria Pires, Dominik Ternes, Dagmar Kulms, et al.. (2019). Identifying and targeting cancer-specific metabolism with network-based drug target prediction. EBioMedicine. 43. 98–106. 53 indexed citations
13.
Rampler, Evelyn, Dominik Egger, Harald Schoeny, et al.. (2019). The Power of LC-MS Based Multiomics: Exploring Adipogenic Differentiation of Human Mesenchymal Stem/Stromal Cells. Molecules. 24(19). 3615–3615. 26 indexed citations
14.
Greenhalgh, Kacy, Javier Ramiro‐Garcia, Almut Heinken, et al.. (2019). Integrated In Vitro and In Silico Modeling Delineates the Molecular Effects of a Synbiotic Regimen on Colorectal-Cancer-Derived Cells. Cell Reports. 27(5). 1621–1632.e9. 68 indexed citations
15.
Pacheco, Maria Pires & Thomas Sauter. (2017). The FASTCORE Family: For the Fast Reconstruction of Compact Context-Specific Metabolic Networks Models. Methods in molecular biology. 1716. 101–110. 10 indexed citations
16.
Pacheco, Maria Pires, Thomas Pfau, & Thomas Sauter. (2016). Benchmarking Procedures for High-Throughput Context Specific Reconstruction Algorithms. Frontiers in Physiology. 6. 410–410. 27 indexed citations
17.
Pavlou, Maria Angeliki S., Christian Jaeger, Maria Pires Pacheco, et al.. (2015). The neural stem cell fate determinant TRIM32 regulates complex behavioral traits. Frontiers in Cellular Neuroscience. 9. 75–75. 16 indexed citations
18.
Pfau, Thomas, Maria Pires Pacheco, & Thomas Sauter. (2015). Towards improved genome-scale metabolic network reconstructions: unification, transcript specificity and beyond. Briefings in Bioinformatics. 17(6). bbv100–bbv100. 16 indexed citations
19.
Pacheco, Maria Pires, Elisabeth John, Tony Kaoma, et al.. (2015). Integrated metabolic modelling reveals cell-type specific epigenetic control points of the macrophage metabolic network. BMC Genomics. 16(1). 809–809. 31 indexed citations
20.
Vlassis, Nikos, Maria Pires Pacheco, & Thomas Sauter. (2014). Fast Reconstruction of Compact Context-Specific Metabolic Network Models. PLoS Computational Biology. 10(1). e1003424–e1003424. 179 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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