Mateusz Mach

411 citations
23 papers · 326 · h-index 11

Impact in

    • Carbohydrate Chemistry and Synthesis
    • Synthetic Organic Chemistry Methods
    • Glycosylation and Glycoproteins Research
    • Chemical Synthesis and Analysis
    • Enzyme Catalysis and Immobilization

Papers in

    • Carbohydrate Chemistry and Synthesis 17
    • Glycosylation and Glycoproteins Research 8
    • Enzyme Catalysis and Immobilization 7
    • Receptor Mechanisms and Signaling 3
    • Chemical Synthesis and Analysis 3

Mateusz Mach

23 papers receiving 303 citations

Peers

Mateusz Mach
Comparison fields: 5 of 52
  • Organic Chemistry 264
  • Molecular Biology 236
  • Biotechnology 27
  • Endocrinology, Diabetes and Metabolism 27
  • Pharmaceutical Science 9
Replace John B. Etienne with:
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Citations per field
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Citations per year

Countries citing papers authored by Mateusz Mach

Since Specialization
Citations

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

Fields of papers citing papers by Mateusz Mach

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Mateusz Mach, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mateusz Mach Line = papers co-authored together Mateusz Mach links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200263
2 200234
3 200233
4 200229
5 200024
6 200121
7 199818
8 199816
9 202113
10 202111
11 199911
12 20229
13 20018
14 20037
15 19976
16 20016
17
Synthesis of Sucrose Derivatives Modified at the Terminal Carbon Atoms
19995
18 20214
19 20192
20 20012

About Mateusz Mach

Mateusz Mach is a scholar working on Organic Chemistry, Molecular Biology, Endocrinology, Diabetes and Metabolism, Surgery and Cellular and Molecular Neuroscience, having authored 23 papers that have together received 326 indexed citations. Recurring topics across this work include Carbohydrate Chemistry and Synthesis (17 papers), Glycosylation and Glycoproteins Research (8 papers), Enzyme Catalysis and Immobilization (7 papers), Diabetes Treatment and Management (5 papers), Receptor Mechanisms and Signaling (3 papers), Pancreatic function and diabetes (3 papers), Chemical Synthesis and Analysis (3 papers) and Amino Acid Enzymes and Metabolism (2 papers). The work is most often cited by research in Organic Chemistry (264 citations), Molecular Biology (236 citations), Biotechnology (27 citations), Endocrinology, Diabetes and Metabolism (27 citations) and Pharmaceutical Science (9 citations). Mateusz Mach has collaborated with scholars based in Poland, Spain and United States. Frequent co-authors include Sławomir Jarosz, Bert Fraser‐Reid, Kevin C. Hazen, Jadwiga Frelek, J. Cristobal López, K. V. Radhakrishnan, Clara Uriel, Ana M. Gómez, Arkadiusz Listkowski and P. SALANSKI. Their work appears in journals such as Tetrahedron, Diabetes, European Journal of Organic Chemistry, European Journal of Medicinal Chemistry and Canadian Journal of Chemistry.

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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