Catherine M. Grgicak

974 total citations
40 papers, 756 citations indexed

About

Catherine M. Grgicak is a scholar working on Molecular Biology, Genetics and Biomedical Engineering. According to data from OpenAlex, Catherine M. Grgicak has authored 40 papers receiving a total of 756 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Molecular Biology, 19 papers in Genetics and 10 papers in Biomedical Engineering. Recurrent topics in Catherine M. Grgicak's work include Forensic and Genetic Research (18 papers), Molecular Biology Techniques and Applications (16 papers) and Gene expression and cancer classification (11 papers). Catherine M. Grgicak is often cited by papers focused on Forensic and Genetic Research (18 papers), Molecular Biology Techniques and Applications (16 papers) and Gene expression and cancer classification (11 papers). Catherine M. Grgicak collaborates with scholars based in United States, Ireland and Netherlands. Catherine M. Grgicak's co-authors include Javier B. Giorgi, Desmond S. Lun, Richard G. Green, Malgosia M. Pakulska, Ken R. Duffy, Harish Swaminathan, Lauren E. Alfonse, Muriel Médard, Robin W. Cotton and Julie S. O’Brien and has published in prestigious journals such as PLoS ONE, Journal of Power Sources and Journal of Materials Chemistry.

In The Last Decade

Catherine M. Grgicak

38 papers receiving 746 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Catherine M. Grgicak United States 16 313 283 282 110 102 40 756
Yufei Yang China 17 209 0.7× 39 0.1× 238 0.8× 23 0.2× 165 1.6× 38 935
Yonggan Wu China 13 431 1.4× 45 0.2× 152 0.5× 31 0.3× 19 0.2× 22 993
Zhifei Zhu China 9 86 0.3× 77 0.3× 82 0.3× 15 0.1× 15 0.1× 29 378
Ishtiaq Saaem United States 13 640 2.0× 60 0.2× 31 0.1× 13 0.1× 310 3.0× 18 839
Chengyin Li China 11 40 0.1× 21 0.1× 214 0.8× 23 0.2× 46 0.5× 28 528
Kai Cui China 12 115 0.4× 13 0.0× 136 0.5× 31 0.3× 58 0.6× 48 533
Ren Chong Lim Brunei 10 132 0.4× 62 0.2× 122 0.4× 5 0.0× 115 1.1× 22 405
Ravinash Krishna Kumar United Kingdom 13 170 0.5× 17 0.1× 129 0.5× 5 0.0× 240 2.4× 18 560
Harsh Sharma India 10 254 0.8× 68 0.2× 36 0.1× 2 0.0× 251 2.5× 32 528

Countries citing papers authored by Catherine M. Grgicak

Since Specialization
Citations

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

Fields of papers citing papers by Catherine M. Grgicak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Catherine M. Grgicak. 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 Catherine M. Grgicak. The network helps show where Catherine M. Grgicak may publish in the future.

Co-authorship network of co-authors of Catherine M. Grgicak

This figure shows the co-authorship network connecting the top 25 collaborators of Catherine M. Grgicak. A scholar is included among the top collaborators of Catherine M. Grgicak 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 Catherine M. Grgicak. Catherine M. Grgicak 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.
Grgicak, Catherine M., et al.. (2025). The (in)dependence of single-cell data inferences on model constructs. Forensic Science International Genetics. 76. 103220–103220.
2.
Lun, Desmond S. & Catherine M. Grgicak. (2024). Calculation of the Weight of Evidence for Combined Single-Cell and Extracellular Forensic DNA. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 21(6). 2587–2591.
3.
Bar, Omri, et al.. (2022). Rapid Nucleic Acid Reaction Circuits for Point-of-care Diagnosis ofDiseases. Current Topics in Medicinal Chemistry. 22(8). 686–698. 1 indexed citations
4.
Mönich, Ullrich J., et al.. (2021). A series of developmental validation tests for Number of Contributors platforms: Exemplars using NOCIt and a neural network. Forensic Science International Genetics. 54. 102556–102556. 4 indexed citations
5.
Grgicak, Catherine M., Ken R. Duffy, & Desmond S. Lun. (2021). The a posteriori probability of the number of contributors when conditioned on an assumed contributor. Forensic Science International Genetics. 54. 102563–102563. 4 indexed citations
6.
Grgicak, Catherine M., et al.. (2020). A large-scale validation of NOCIt’s a posteriori probability of the number of contributors and its integration into forensic interpretation pipelines. Forensic Science International Genetics. 47. 102296–102296. 17 indexed citations
7.
Alfonse, Lauren E., et al.. (2019). Statistical modeling of STR capillary electrophoresis signal. BMC Bioinformatics. 20(S16). 584–584. 12 indexed citations
8.
Swaminathan, Harish, et al.. (2018). Four model variants within a continuous forensic DNA mixture interpretation framework: Effects on evidential inference and reporting. PLoS ONE. 13(11). e0207599–e0207599. 13 indexed citations
9.
10.
Swaminathan, Harish, et al.. (2017). Production of high-fidelity electropherograms results in improved and consistent DNA interpretation: Standardizing the forensic validation process. Forensic Science International Genetics. 31. 160–170. 9 indexed citations
11.
Swaminathan, Harish, Abhishek Garg, Catherine M. Grgicak, Muriel Médard, & Desmond S. Lun. (2016). CEESIt: A computational tool for the interpretation of STR mixtures. Forensic Science International Genetics. 22. 149–160. 31 indexed citations
12.
Alfonse, Lauren E., et al.. (2016). Inferring the Number of Contributors to Complex DNA Mixtures Using Three Methods: Exploring the Limits of Low‐Template DNA Interpretation. Journal of Forensic Sciences. 62(2). 308–316. 14 indexed citations
13.
Mönich, Ullrich J., Ken R. Duffy, Muriel Médard, et al.. (2015). Probabilistic characterisation of baseline noise in STR profiles. Forensic Science International Genetics. 19. 107–122. 18 indexed citations
14.
Grgicak, Catherine M., et al.. (2015). Exploring the Impacts of Ordinary Laboratory Alterations During Forensic DNA Processing on Peak Height Variation, Thresholds, and Probability of Dropout,. Journal of Forensic Sciences. 61(1). 177–185. 3 indexed citations
15.
Swaminathan, Harish, Catherine M. Grgicak, Muriel Médard, & Desmond S. Lun. (2014). NOCIt: A computational method to infer the number of contributors to DNA samples analyzed by STR genotyping. Forensic Science International Genetics. 16. 172–180. 53 indexed citations
16.
Grgicak, Catherine M., et al.. (2014). The Effect of Repeated Activation on Screen-Printed Carbon Electrode Cards. ECS Transactions. 61(26). 1–8. 10 indexed citations
17.
Mönich, Ullrich J., et al.. (2014). A signal model for forensic DNA mixtures. 2014 48th Asilomar Conference on Signals, Systems and Computers. 429–433. 2 indexed citations
18.
Cotton, Robin W., et al.. (2013). The Effects of Differential Extraction Conditions on the Premature Lysis of Spermatozoa,. Journal of Forensic Sciences. 58(3). 744–752. 14 indexed citations
19.
Brown, Matthew, et al.. (2006). Reactivity of mesoporous palladium yttria-stablilized zirconia for solution phase reactions. Canadian Journal of Chemistry. 84(11). 1520–1528. 1 indexed citations
20.
Grgicak, Catherine M., et al.. (2005). Discovery and identification of new D13S317 primer binding site mutations. Forensic Science International. 157(1). 36–39. 6 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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