Jacek Jasiecki

446 citations
21 papers · 373 indexed · h-index 11
Topics
Cholinesterase and Neurodegenerative Diseases (8 papers)Computational Drug Discovery Methods (7 papers)Bacterial Genetics and Biotechnology (5 papers)
Partner nations
PolandFinlandDenmark

In The Last Decade

Jacek Jasiecki

20 papers receiving 370 citations

Peers

Jacek Jasiecki
Comparison fields: 5 of 82
  • Molecular Biology 161
  • Pharmacology 124
  • Genetics 86
  • Computational Theory and Mathematics 67
  • Plant Science 49
Replace Gerda Brunhofer with:
Gerda Brunhofer Austria
Abbasali Emamjomeh Iran
Jin Wook South Korea
Jim N. Burnell Australia
Lynsey MacIntyre United Kingdom
Reza Dowlatabadi Iran
Fernanda Majolo Brazil
Mika Miyake Japan
Dharmarajan Sriram India
Shuaizhang Li United States
Jacek Jasiecki relative to Gerda Brunhofer Austria Gerda Brunhofer's profile →
Citations per field
00.5×6.1×
Gerda Brunhofer · 1×
Citations per year

Countries citing papers authored by Jacek Jasiecki

Since Specialization
Citations

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

Fields of papers citing papers by Jacek Jasiecki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jacek Jasiecki

This figure shows the co-authorship network connecting the top 25 collaborators of Jacek Jasiecki. A scholar is included among the top collaborators of Jacek Jasiecki 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 Jacek Jasiecki. Jacek Jasiecki 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
#WorkIndexed citations
1 0
2 8
3 4
4 3
5 2
6 20
7 16
8 46
9 6
10 5
11 14
12 53
13 14
14 30
15 8
16 7
17 19
18 14
19 44
20 2

About Jacek Jasiecki

Jacek Jasiecki is a scholar working on Pharmacology, Computational Theory and Mathematics and Endocrinology, having authored 21 papers that have together received 373 indexed citations. Recurring topics across this work include Cholinesterase and Neurodegenerative Diseases (8 papers), Computational Drug Discovery Methods (7 papers) and Bacterial Genetics and Biotechnology (5 papers). The work is most often cited by research in Pharmacology (124 citations), Endocrinology (22 citations) and Computational Theory and Mathematics (67 citations). Jacek Jasiecki has collaborated with scholars based in Poland, Finland and Denmark. Frequent co-authors include Bartosz Wasąg, Grzegorz Węgrzyn, Krzysztof Waleron, Agata Czyż, Anna Janaszak‐Jasiecka, Dominik Cysewski, Bartosz Wielgomas, Piotr M. Skowron, Magdalena Chmara and Krzysztof Lewandowski. Their work appears in journals such as PLoS ONE, Applied and Environmental Microbiology and Scientific Reports.

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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