Jakub Paś

602 total citations
11 papers, 293 citations indexed

About

Jakub Paś is a scholar working on Molecular Biology, Plant Science and Materials Chemistry. According to data from OpenAlex, Jakub Paś has authored 11 papers receiving a total of 293 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 3 papers in Plant Science and 3 papers in Materials Chemistry. Recurrent topics in Jakub Paś's work include Protein Structure and Dynamics (3 papers), Enzyme Structure and Function (3 papers) and CRISPR and Genetic Engineering (2 papers). Jakub Paś is often cited by papers focused on Protein Structure and Dynamics (3 papers), Enzyme Structure and Function (3 papers) and CRISPR and Genetic Engineering (2 papers). Jakub Paś collaborates with scholars based in Poland. Jakub Paś's co-authors include Lucjan Wyrwicz, Leszek Rychlewski, Marcin von Grotthuss, Janusz M. Bujnicki, Marcin Feder, Jan Barciszewski, Krzysztof Ginalski, Grzegorz Koczyk, Stanisław Nowak and Eliza Wyszko and has published in prestigious journals such as Bioinformatics, FEBS Letters and Gene.

In The Last Decade

Jakub Paś

11 papers receiving 283 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jakub Paś Poland	7	201	47	35	31	27	11	293
Su‐Hwi Hung United States	7	351 1.7×	30 0.6×	32 0.9×	19 0.6×	21 0.8×	7	440
Michael C. Cavalier United States	9	234 1.2×	26 0.6×	37 1.1×	23 0.7×	25 0.9×	15	320
Amitava Roy United States	12	204 1.0×	43 0.9×	24 0.7×	62 2.0×	16 0.6×	23	306
Saikat Chakrabarti India	13	423 2.1×	52 1.1×	21 0.6×	49 1.6×	24 0.9×	33	503
Alastair Muir United Kingdom	8	234 1.2×	23 0.5×	15 0.4×	44 1.4×	31 1.1×	10	334
Erik C Hansen United States	8	213 1.1×	25 0.5×	47 1.3×	24 0.8×	61 2.3×	11	351
Jason van Rooyen South Africa	8	206 1.0×	27 0.6×	12 0.3×	49 1.6×	22 0.8×	15	338
Franco L. Simonetti Argentina	8	320 1.6×	50 1.1×	26 0.7×	39 1.3×	19 0.7×	12	383
Francis Gaudreault Canada	10	214 1.1×	51 1.1×	27 0.8×	38 1.2×	15 0.6×	18	275
Dana Weekes United States	9	263 1.3×	49 1.0×	27 0.8×	41 1.3×	19 0.7×	10	358

Countries citing papers authored by Jakub Paś

Since Specialization

Citations

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

Fields of papers citing papers by Jakub Paś

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jakub Paś

This figure shows the co-authorship network connecting the top 25 collaborators of Jakub Paś. A scholar is included among the top collaborators of Jakub Paś 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 Jakub Paś. Jakub Paś is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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11 of 11 papers shown

Paś, Jakub. (2012). GRDB – Gene Relational DataBase. 2659–2659. 1 indexed citations

Wyszko, Eliza, H. Pospieszny, M. Szymański, et al.. (2006). Leadzyme formed in vivo interferes with tobacco mosaic virus infection in Nicotiana tabacum. FEBS Journal. 273(22). 5022–5031. 5 indexed citations

Paś, Jakub, Eliza Wyszko, Katarzyna Rolle, et al.. (2006). Analysis of structure and function of tenascin-C. The International Journal of Biochemistry & Cell Biology. 38(9). 1594–1602. 40 indexed citations

Fischer, Daniel, Jakub Paś, & Leszek Rychlewski. (2004). The PDB-Preview database: a repository of in-silico models of ‘on-hold’ PDB entries. Bioinformatics. 20(15). 2482–2484. 2 indexed citations

Paś, Jakub, Marcin von Grotthuss, Lucjan Wyrwicz, Leszek Rychlewski, & Jan Barciszewski. (2004). Structure prediction, evolution and ligand interaction of CHASE domain. FEBS Letters. 576(3). 287–290. 28 indexed citations

Narożna, Dorota, et al.. (2004). Two sequences encoding chalcone synthase in yellow lupin (Lupinus luteus l.) may have evolved by gene duplication.. PubMed. 9(1). 95–105. 1 indexed citations

Grotthuss, Marcin von, Grzegorz Koczyk, Jakub Paś, Lucjan Wyrwicz, & Leszek Rychlewski. (2004). Ligand.Info Small-Molecule Meta-Database. Combinatorial Chemistry & High Throughput Screening. 7(8). 757–761. 46 indexed citations

Plewczyński, Dariusz, Jakub Paś, Marcin von Grotthuss, & Leszek Rychlewski. (2004). Comparison of proteins based on segments structural similarity.. Acta Biochimica Polonica. 51(1). 161–172. 10 indexed citations

Grotthuss, Marcin von, Jakub Paś, Lucjan Wyrwicz, Krzysztof Ginalski, & Leszek Rychlewski. (2003). Application of 3D-Jury, GRDB, and Verify3D in fold recognition. Proteins Structure Function and Bioinformatics. 53(S6). 418–423. 46 indexed citations

10.

Feder, Marcin, Jakub Paś, Lucjan Wyrwicz, & Janusz M. Bujnicki. (2003). Molecular phylogenetics of the RrmJ/fibrillarin superfamily of ribose 2′-O-methyltransferases. Gene. 302(1-2). 129–138. 84 indexed citations

11.

Grotthuss, Marcin von, Jakub Paś, & Leszek Rychlewski. (2003). Ligand-Info, searching for similar small compounds usingindex profiles. Bioinformatics. 19(8). 1041–1042. 30 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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