Pawel Bialk

525 total citations
15 papers, 360 citations indexed

About

Pawel Bialk is a scholar working on Molecular Biology, Genetics and Plant Science. According to data from OpenAlex, Pawel Bialk has authored 15 papers receiving a total of 360 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 5 papers in Genetics and 2 papers in Plant Science. Recurrent topics in Pawel Bialk's work include CRISPR and Genetic Engineering (15 papers), RNA Interference and Gene Delivery (5 papers) and Virus-based gene therapy research (5 papers). Pawel Bialk is often cited by papers focused on CRISPR and Genetic Engineering (15 papers), RNA Interference and Gene Delivery (5 papers) and Virus-based gene therapy research (5 papers). Pawel Bialk collaborates with scholars based in United States. Pawel Bialk's co-authors include Eric B. Kmiec, Bryan Strouse, Byung-Chun Yoo, Yichen Wang, Zugui Zhang, Jingwei Xie, E. Anders Kolb, Haley E. Perry, Anilkumar Gopalakrishnapillai and Mona Batish and has published in prestigious journals such as Blood, PLoS ONE and Scientific Reports.

In The Last Decade

Pawel Bialk

15 papers receiving 351 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pawel Bialk United States 10 320 86 48 27 24 15 360
Wenxing You Hong Kong 7 403 1.3× 121 1.4× 26 0.5× 35 1.3× 24 1.0× 8 483
K. R. Valetdinova Russia 6 217 0.7× 55 0.6× 43 0.9× 10 0.4× 17 0.7× 18 266
Elodie Dardillac France 10 346 1.1× 84 1.0× 52 1.1× 24 0.9× 18 0.8× 17 433
Charles A. Gersbach United States 5 343 1.1× 94 1.1× 18 0.4× 36 1.3× 26 1.1× 6 370
Pablo Reyes‐Gutierrez United States 8 534 1.7× 58 0.7× 80 1.7× 35 1.3× 27 1.1× 10 627
Tyler S. Klann United States 7 420 1.3× 74 0.9× 25 0.5× 28 1.0× 18 0.8× 9 464
Mahalakshmi Sridharan United States 2 535 1.7× 149 1.7× 24 0.5× 29 1.1× 50 2.1× 3 571
Chunlai Tan Hong Kong 7 259 0.8× 80 0.9× 22 0.5× 17 0.6× 16 0.7× 7 377
Marena Trinidad United States 11 381 1.2× 92 1.1× 23 0.5× 14 0.5× 31 1.3× 21 457

Countries citing papers authored by Pawel Bialk

Since Specialization
Citations

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

Fields of papers citing papers by Pawel Bialk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pawel Bialk

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

All Works

15 of 15 papers shown
1.
Bialk, Pawel, et al.. (2023). CRISPR-Directed Gene Editing as a Method to Reduce Chemoresistance in Lung Cancer Cells. Methods in molecular biology. 2660. 263–271. 2 indexed citations
2.
Yoo, Byung-Chun, et al.. (2022). Exon skipping induced by CRISPR-directed gene editing regulates the response to chemotherapy in non-small cell lung carcinoma cells. Gene Therapy. 29(6). 357–367. 11 indexed citations
3.
4.
Bialk, Pawel, et al.. (2020). Kinetics of Nuclear Uptake and Site-Specific DNA Cleavage during CRISPR-Directed Gene Editing in Solid Tumor Cells. Molecular Cancer Research. 18(6). 891–902. 8 indexed citations
5.
Bialk, Pawel, et al.. (2018). Efficient Delivery and Nuclear Uptake Is Not Sufficient to Detect Gene Editing in CD34+ Cells Directed by a Ribonucleoprotein Complex. Molecular Therapy — Nucleic Acids. 11. 116–129. 11 indexed citations
6.
Bialk, Pawel, et al.. (2018). Functional Gene Knockout of NRF2 Increases Chemosensitivity of Human Lung Cancer A549 Cells In Vitro and in a Xenograft Mouse Model. Molecular Therapy — Oncolytics. 11. 75–89. 51 indexed citations
7.
Bialk, Pawel, et al.. (2017). CRISPR/Cas9-Directed Reassignment of the GATA1 Initiation Codon in K562 Cells to Recapitulate AML in Down Syndrome. Molecular Therapy — Nucleic Acids. 7. 288–298. 7 indexed citations
8.
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10.
Bialk, Pawel, et al.. (2016). Analyses of point mutation repair and allelic heterogeneity generated by CRISPR/Cas9 and single-stranded DNA oligonucleotides. Scientific Reports. 6(1). 32681–32681. 23 indexed citations
11.
Bialk, Pawel, et al.. (2015). Regulation of Gene Editing Activity Directed by Single-Stranded Oligonucleotides and CRISPR/Cas9 Systems. PLoS ONE. 10(6). e0129308–e0129308. 57 indexed citations
12.
Strouse, Bryan, et al.. (2014). Combinatorial gene editing in mammalian cells using ssODNs and TALENs. Scientific Reports. 4(1). 3791–3791. 23 indexed citations
13.
14.
Strouse, Bryan, et al.. (2012). Oligonucleotide Delivery by Nucleofection Does Not Rescue the Reduced Proliferation Phenotype of Gene-Edited Cells. Nucleic Acid Therapeutics. 22(6). 405–413. 3 indexed citations
15.
Strouse, Bryan, et al.. (2012). Proliferation of Genetically Modified Human Cells on Electrospun Nanofiber Scaffolds. Molecular Therapy — Nucleic Acids. 1. e59–e59. 22 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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