Mateusz Maciejewski

1.2k total citations
28 papers, 561 citations indexed

About

Mateusz Maciejewski is a scholar working on Rheumatology, Molecular Biology and Immunology. According to data from OpenAlex, Mateusz Maciejewski has authored 28 papers receiving a total of 561 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Rheumatology, 7 papers in Molecular Biology and 6 papers in Immunology. Recurrent topics in Mateusz Maciejewski's work include Rheumatoid Arthritis Research and Therapies (7 papers), Computational Drug Discovery Methods (5 papers) and Complement system in diseases (4 papers). Mateusz Maciejewski is often cited by papers focused on Rheumatoid Arthritis Research and Therapies (7 papers), Computational Drug Discovery Methods (5 papers) and Complement system in diseases (4 papers). Mateusz Maciejewski collaborates with scholars based in United States, United Kingdom and Sweden. Mateusz Maciejewski's co-authors include Paul N. Barlow, Daniel Ziemek, Anne Mai Wassermann, Meir Glick, Hongjun Bai, John D. Lambris, Hui Chen, Αποστολία Τζέκου, Florea Lupu and Edimara S. Reis and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Mateusz Maciejewski

26 papers receiving 546 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mateusz Maciejewski United States 14 184 182 124 91 66 28 561
Andreas Scherer Finland 20 115 0.6× 530 2.9× 38 0.3× 64 0.7× 25 0.4× 49 1.1k
Mark Penney United Kingdom 15 207 1.1× 507 2.8× 27 0.2× 73 0.8× 61 0.9× 18 1.1k
Leonor Puchades‐Carrasco Spain 17 82 0.4× 533 2.9× 49 0.4× 13 0.1× 53 0.8× 34 843
Prajakta Badri United States 15 54 0.3× 266 1.5× 86 0.7× 13 0.1× 21 0.3× 30 1.1k
Ekaterina Gibiansky United States 19 302 1.6× 361 2.0× 62 0.5× 77 0.8× 177 2.7× 42 1.3k
Lars Philipsen Germany 17 345 1.9× 477 2.6× 22 0.2× 14 0.2× 28 0.4× 32 943
Andreas Boettcher Switzerland 9 168 0.9× 467 2.6× 15 0.1× 35 0.4× 58 0.9× 13 576
Lorah Perlee United States 13 179 1.0× 242 1.3× 25 0.2× 9 0.1× 58 0.9× 35 684
Sumit Chakraborty India 11 75 0.4× 262 1.4× 161 1.3× 14 0.2× 20 0.3× 24 652
Pablo Conesa‐Zamora Spain 22 188 1.0× 480 2.6× 82 0.7× 21 0.2× 43 0.7× 85 1.3k

Countries citing papers authored by Mateusz Maciejewski

Since Specialization
Citations

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

Fields of papers citing papers by Mateusz Maciejewski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mateusz Maciejewski

This figure shows the co-authorship network connecting the top 25 collaborators of Mateusz Maciejewski. A scholar is included among the top collaborators of Mateusz Maciejewski 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 Mateusz Maciejewski. Mateusz Maciejewski 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.
Kim, SungYe, et al.. (2025). Joint Denoising and Upscaling via Multi-branch and Multi-scale Feature Network. Proceedings of the ACM on Computer Graphics and Interactive Techniques. 8(1). 1–18.
2.
Brynedal, Boel, Niyaz Yoosuf, Daniel Ziemek, et al.. (2023). Molecular signature of methotrexate response among rheumatoid arthritis patients. Frontiers in Medicine. 10. 1146353–1146353. 5 indexed citations
3.
Hedman, Åsa K., Eitan Winter, Niyaz Yoosuf, et al.. (2023). Peripheral blood cellular dynamics of rheumatoid arthritis treatment informs about efficacy of response to disease modifying drugs. Scientific Reports. 13(1). 10058–10058. 10 indexed citations
4.
Yoosuf, Niyaz, Mateusz Maciejewski, Daniel Ziemek, et al.. (2021). Early prediction of clinical response to anti-TNF treatment using multi-omics and machine learning in rheumatoid arthritis. Lara D. Veeken. 61(4). 1680–1689. 39 indexed citations
5.
Maciejewski, Mateusz, Caroline Sands, Nisha Nair, et al.. (2021). Prediction of response of methotrexate in patients with rheumatoid arthritis using serum lipidomics. Scientific Reports. 11(1). 7266–7266. 29 indexed citations
6.
Liu, Tianyun, Lichy Han, Lovisa Afzelius, et al.. (2021). Distinct clinical phenotypes for Crohn’s disease derived from patient surveys. BMC Gastroenterology. 21(1). 160–160. 7 indexed citations
7.
Walsh, Jonathan R., John M. Long, Craig B. Davis, et al.. (2020). Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data. BMC Bioinformatics. 21(1). 119–119. 47 indexed citations
8.
Das, Rahul, Raymond T. Yan, Craig B. Davis, et al.. (2020). Causal modeling of TCGA, NSCLC, and HNSCC data to identify network drivers of tumor immune subtypes.. Journal of Clinical Oncology. 38(5_suppl). 68–68. 1 indexed citations
9.
Plant, Darren, Mateusz Maciejewski, Samantha Smith, et al.. (2019). 018 Gene expression profiling identifies classifier of methotrexate non-response in patients with rheumatoid arthritis. Lara D. Veeken. 58(Supplement_3). 2 indexed citations
10.
Plant, Darren, Mateusz Maciejewski, Samantha Smith, et al.. (2019). Profiling of Gene Expression Biomarkers as a Classifier of Methotrexate Nonresponse in Patients With Rheumatoid Arthritis. Arthritis & Rheumatology. 71(5). 678–684. 49 indexed citations
11.
Maciejewski, Mateusz, Eugen Lounkine, Steven Whitebread, et al.. (2017). Reverse translation of adverse event reports paves the way for de-risking preclinical off-targets. eLife. 6. 38 indexed citations
12.
Maciejewski, Mateusz, et al.. (2016). Public Domain HTS Fingerprints: Design and Evaluation of Compound Bioactivity Profiles from PubChem’s Bioassay Repository. Journal of Chemical Information and Modeling. 56(2). 390–398. 41 indexed citations
13.
Pearlstein, Robert A., Keith A. MacCannell, Gül Erdemli, et al.. (2016). Implications of Dynamic Occupancy, Binding Kinetics, and Channel Gating Kinetics for hERG Blocker Safety Assessment and Mitigation. Current Topics in Medicinal Chemistry. 16(16). 1792–1818. 15 indexed citations
14.
Urbán, László, Mateusz Maciejewski, Eugen Lounkine, et al.. (2014). Translation of off-target effects: prediction of ADRs by integrated experimental and computational approach. Toxicology Research. 3(6). 433–444. 12 indexed citations
15.
Guariento, Mara, Mateusz Maciejewski, Richard E. Hauhart, et al.. (2013). Using Mutagenesis and Structural Biology to Map the Binding Site for the Plasmodium falciparum Merozoite Protein PfRh4 on the Human Immune Adherence Receptor. Journal of Biological Chemistry. 289(1). 450–463. 25 indexed citations
16.
Koutsoukas, Alexios, et al.. (2013). Diversity Selection of Compounds Based on ‘Protein Affinity Fingerprints’ Improves Sampling of Bioactive Chemical Space. Chemical Biology & Drug Design. 82(3). 252–266. 12 indexed citations
17.
Maciejewski, Mateusz, Paul N. Barlow, & Nico Tjandra. (2013). Decoding the components of dynamics in three‐domain proteins. Journal of Computational Chemistry. 35(7). 518–525. 1 indexed citations
18.
Mertens, Haydyn D. T., Mateusz Maciejewski, Dinesh C. Soares, et al.. (2012). Solution Structure of CCP Modules 10–12 Illuminates Functional Architecture of the Complement Regulator, Factor H. Journal of Molecular Biology. 424(5). 295–312. 22 indexed citations
19.
Qu, Hongchang, Daniel Ricklin, Hongjun Bai, et al.. (2012). New analogs of the clinical complement inhibitor compstatin with subnanomolar affinity and enhanced pharmacokinetic properties. Immunobiology. 218(4). 496–505. 119 indexed citations
20.
Maciejewski, Mateusz, Damian Wojcieszak, M. Mazur, et al.. (2010). Influence of droplet size and surface preparation of TiO. 48–51. 2 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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