Mirna Jarosz

6.8k total citations
10 papers, 903 citations indexed

About

Mirna Jarosz is a scholar working on Molecular Biology, Cancer Research and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Mirna Jarosz has authored 10 papers receiving a total of 903 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 6 papers in Cancer Research and 2 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Mirna Jarosz's work include Cancer Genomics and Diagnostics (6 papers), Genomics and Phylogenetic Studies (3 papers) and Advanced biosensing and bioanalysis techniques (3 papers). Mirna Jarosz is often cited by papers focused on Cancer Genomics and Diagnostics (6 papers), Genomics and Phylogenetic Studies (3 papers) and Advanced biosensing and bioanalysis techniques (3 papers). Mirna Jarosz collaborates with scholars based in United States. Mirna Jarosz's co-authors include Peter McInerney, Jayson Bowers, Adam Platt, John F. Thompson, Lauryn E. Sass, Daniel Jones, Jeffrey G. Reifenberger, Fatih Ozsolak, Patrice M. Milos and Doron Lipson and has published in prestigious journals such as Nature, Angewandte Chemie International Edition and Journal of Clinical Oncology.

In The Last Decade

Mirna Jarosz

10 papers receiving 865 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mirna Jarosz United States 6 625 272 265 108 105 10 903
Tejal Joshi Denmark 12 761 1.2× 413 1.5× 186 0.7× 61 0.6× 264 2.5× 15 1.1k
Tanxiao Huang China 11 239 0.4× 179 0.7× 126 0.5× 44 0.4× 181 1.7× 33 597
Angel E. Dago United States 9 422 0.7× 157 0.6× 68 0.3× 74 0.7× 148 1.4× 14 598
Marcia Eisenberg United States 13 181 0.3× 97 0.4× 92 0.3× 47 0.4× 138 1.3× 45 483
Christina Beinke Germany 16 314 0.5× 291 1.1× 132 0.5× 27 0.3× 106 1.0× 34 844
Chad A. Malloff Canada 9 493 0.8× 204 0.8× 146 0.6× 26 0.2× 81 0.8× 15 819
Abdellah Belmaaza Canada 16 669 1.1× 187 0.7× 76 0.3× 15 0.1× 205 2.0× 26 886
Kate S. Reid-Bayliss United States 5 315 0.5× 163 0.6× 39 0.1× 42 0.4× 53 0.5× 5 449
Nicola Thelwell United Kingdom 7 273 0.4× 68 0.3× 56 0.2× 42 0.4× 80 0.8× 9 415

Countries citing papers authored by Mirna Jarosz

Since Specialization
Citations

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

Fields of papers citing papers by Mirna Jarosz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mirna Jarosz

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

All Works

10 of 10 papers shown
1.
MacConaill, Laura E., Robert Burns, Anwesha Nag, et al.. (2018). Unique, dual-indexed sequencing adapters with UMIs effectively eliminate index cross-talk and significantly improve sensitivity of massively parallel sequencing. BMC Genomics. 19(1). 30–30. 150 indexed citations
2.
Wang, Jiashi, Kristina Giorda, Zhongwu Lai, Daniel Stetson, & Mirna Jarosz. (2017). Abstract 397: Whole genome copy number variation analysis using a SNP-focused targeted sequencing panel for tumor analysis. Cancer Research. 77(13_Supplement). 397–397. 1 indexed citations
3.
Beltran, Himisha, Roman Yelensky, Garrett M. Frampton, et al.. (2012). Targeted Next-generation Sequencing of Advanced Prostate Cancer Identifies Potential Therapeutic Targets and Disease Heterogeneity. European Urology. 63(5). 920–926. 330 indexed citations
5.
Ross, Jeffrey S., Doron Lipson, Christine E. Sheehan, et al.. (2012). Use of next-generation sequencing (NGS) to detect a novel ALK fusion and a high frequency of other actionable alterations in colorectal cancer (CRC).. Journal of Clinical Oncology. 30(15_suppl). 3533–3533. 2 indexed citations
6.
Ross, Jeffrey S., Doron Lipson, Roman Yelensky, et al.. (2011). Comprehensive next-generation sequencing for clinically actionable mutations from formalin-fixed cancer tissues.. Journal of Clinical Oncology. 29(15_suppl). 10564–10564. 5 indexed citations
7.
Leconte, Aaron M., Lauryn E. Sass, Peter McInerney, et al.. (2010). Directed Evolution of DNA Polymerases for Next‐Generation Sequencing. Angewandte Chemie International Edition. 49(34). 5921–5924. 24 indexed citations
8.
Leconte, Aaron M., Lauryn E. Sass, Peter McInerney, et al.. (2010). Directed Evolution of DNA Polymerases for Next‐Generation Sequencing. Angewandte Chemie. 122(34). 6057–6060. 7 indexed citations
9.
Ozsolak, Fatih, Adam Platt, Daniel Jones, et al.. (2009). Direct RNA sequencing. Nature. 461(7265). 814–818. 302 indexed citations
10.
Bowers, Jayson, J. William Efcavitch, Mirna Jarosz, et al.. (2009). Virtual terminator nucleotides for next-generation DNA sequencing. Nature Methods. 6(8). 593–595. 77 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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