Jacek Sroka

614 total citations · 1 hit paper
25 papers, 317 citations indexed

About

Jacek Sroka is a scholar working on Computer Networks and Communications, Information Systems and Management and Information Systems. According to data from OpenAlex, Jacek Sroka has authored 25 papers receiving a total of 317 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Networks and Communications, 9 papers in Information Systems and Management and 8 papers in Information Systems. Recurrent topics in Jacek Sroka's work include Scientific Computing and Data Management (9 papers), Distributed and Parallel Computing Systems (8 papers) and Cloud Computing and Resource Management (5 papers). Jacek Sroka is often cited by papers focused on Scientific Computing and Data Management (9 papers), Distributed and Parallel Computing Systems (8 papers) and Cloud Computing and Resource Management (5 papers). Jacek Sroka collaborates with scholars based in Poland, United Kingdom and Netherlands. Jacek Sroka's co-authors include Jan Hidders, Talal Rahwan, Tomasz Michalak, Michael Wooldridge, Nicholas R. Jennings, Paolo Missier, Peter McBurney, Marta Bauer, Ewa Szczurek and Wojciech Kamysz and has published in prestigious journals such as Nature Communications, Bioinformatics and BMC Bioinformatics.

In The Last Decade

Jacek Sroka

22 papers receiving 305 citations

Hit Papers

Discovering highly potent... 2023 2026 2024 2023 25 50 75
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Discovering highly potent antimicrobial peptides with deep generative model HydrAMP
    2023 98 citations Marcin Możejko, Marta Bauer et al. Nature Communications profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jacek Sroka Poland 9 107 78 72 70 60 25 317
Vishakha Singh India 11 85 0.8× 292 3.7× 6 0.1× 48 0.7× 3 0.1× 15 493
María Teresa Gómez-López Spain 11 41 0.4× 75 1.0× 43 0.6× 5 0.1× 10 0.2× 67 403
Sérgio Lifschitz Brazil 10 53 0.5× 134 1.7× 16 0.2× 2 0.0× 5 0.1× 79 326
Chaki Ng United States 7 22 0.2× 260 3.3× 80 1.1× 12 0.2× 10 324
Mark Parsons United Kingdom 9 18 0.2× 102 1.3× 14 0.2× 22 0.4× 25 230
Guillaume Blin France 8 74 0.7× 54 0.7× 23 0.3× 8 0.1× 19 225
Ankit Gupta India 9 98 0.9× 34 0.4× 18 0.3× 8 0.1× 1 0.0× 43 314
Arindam Khan India 7 22 0.2× 86 1.1× 29 0.4× 16 0.3× 30 280
Peter A. Covitz United States 13 529 4.9× 114 1.5× 41 0.6× 9 0.1× 15 810
Anna-Lena Lamprecht Germany 8 57 0.5× 54 0.7× 17 0.2× 2 0.0× 1 0.0× 35 217

Countries citing papers authored by Jacek Sroka

Since Specialization
Citations

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

Fields of papers citing papers by Jacek Sroka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jacek Sroka

This figure shows the co-authorship network connecting the top 25 collaborators of Jacek Sroka. A scholar is included among the top collaborators of Jacek Sroka 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 Sroka. Jacek Sroka 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.
Pawłowski, Tomasz, et al.. (2024). Emulation of Quantitative Systems Pharmacology models to accelerate virtual population inference in immuno-oncology. Methods. 223. 118–126. 6 indexed citations
2.
Możejko, Marcin, Marta Bauer, Damian Neubauer, et al.. (2023). Discovering highly potent antimicrobial peptides with deep generative model HydrAMP. Nature Communications. 14(1). 1453–1453. 98 indexed citations breakdown →
3.
Sroka, Jacek, Subhadip Basu, Paweł Trzaskoma, et al.. (2021). PartSeg: a tool for quantitative feature extraction from 3D microscopy images for dummies. BMC Bioinformatics. 22(1). 72–72. 14 indexed citations
4.
5.
Wu, Huihai, Axel von Kamp, Wataru Mori, et al.. (2016). MUFINS: multi-formalism interaction network simulator. npj Systems Biology and Applications. 2(1). 16032–16032. 17 indexed citations
6.
Sroka, Jacek, et al.. (2015). On Generating Hierarchical Workflow Nets and their Extensions and Verifying Hierarchicality. Fundamenta Informaticae. 141(4). 367–398. 2 indexed citations
7.
Sroka, Jacek, Jan Hidders, & Paolo Missier. (2014). Report from the second workshop on scalable workflow enactment engines and technology (SWEET'13). ACM SIGMOD Record. 42(4). 73–77. 1 indexed citations
8.
Hidders, Jan, Jacek Sroka, & Paolo Missier. (2013). Report from the first workshop on scalable workflow enactment engines and technology (SWEET'12). ACM SIGMOD Record. 41(4). 60–64. 1 indexed citations
9.
Sroka, Jacek & Jan Hidders. (2013). On generating ⁎-sound nets with substitution. Information Systems. 40. 32–46. 3 indexed citations
10.
Hidders, Jan, Paolo Missier, & Jacek Sroka. (2012). Proceedings of the 1st ACM SIGMOD Workshop on Scalable Workflow Execution Engines and Technologies. 8 indexed citations
11.
Sroka, Jacek, Jakub Łącki, Claudio Avignone–Rossa, et al.. (2011). Acorn: A grid computing system for constraint based modeling and visualization of the genome scale metabolic reaction networks via a web interface. BMC Bioinformatics. 12(1). 196–196. 11 indexed citations
12.
Sroka, Jacek, et al.. (2011). CalcTav—integration of a spreadsheet and Taverna workbench. Bioinformatics. 27(18). 2618–2619. 1 indexed citations
13.
Michalak, Tomasz, Jacek Sroka, Talal Rahwan, et al.. (2010). A distributed algorithm for anytime coalition structure generation. Adaptive Agents and Multi-Agents Systems. 1007–1014. 44 indexed citations
14.
Sroka, Jacek, et al.. (2010). JavaSpaces NetBeans. 23–27. 2 indexed citations
15.
Sroka, Jacek, Jan Hidders, Paolo Missier, & Carole Goble. (2009). A formal semantics for the Taverna 2 workflow model. Journal of Computer and System Sciences. 76(6). 490–508. 28 indexed citations
16.
Sroka, Jacek & Jan Hidders. (2009). Towards a Formal Semantics for the Process Model of the Taverna Workbench. Part II. Fundamenta Informaticae. 92(4). 373–396.
17.
Sroka, Jacek & Jan Hidders. (2009). Towards a Formal Semantics for the Process Model of the Taverna Workbench. Part I. Fundamenta Informaticae. 92(3). 279–299. 3 indexed citations
18.
Michalak, Tomasz, Talal Rahwan, Jacek Sroka, et al.. (2009). On representing coalitional games with externalities. Research Portal (King's College London). 11–20. 14 indexed citations
19.
Sroka, Jacek, et al.. (2006). XQTav: an XQuery processor for Taverna environment. Bioinformatics. 22(10). 1280–1281.
20.
Gambin, Anna, Jan Hidders, Natalia Kwaśnikowska, et al.. (2005). NRC as a formal model for expressing bioinformatics workflows. 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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