Daniel Nicorici

1.9k total citations
28 papers, 1.1k citations indexed

About

Daniel Nicorici is a scholar working on Molecular Biology, Cancer Research and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Daniel Nicorici has authored 28 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 11 papers in Cancer Research and 5 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Daniel Nicorici's work include MicroRNA in disease regulation (6 papers), Protein Degradation and Inhibitors (5 papers) and Prostate Cancer Treatment and Research (5 papers). Daniel Nicorici is often cited by papers focused on MicroRNA in disease regulation (6 papers), Protein Degradation and Inhibitors (5 papers) and Prostate Cancer Treatment and Research (5 papers). Daniel Nicorici collaborates with scholars based in Finland, Sweden and United States. Daniel Nicorici's co-authors include Olli Kallioniemi, Henrik Edgren, Sara Kangaspeska, Sampsa Hautaniemi, Astrid Murumägi, Vesa Hongisto, Inga Hansine Rye, A.L. Børresen-Dale, Maija Wolf and Kristine Kleivi Sahlberg and has published in prestigious journals such as SHILAP Revista de lepidopterología, Gastroenterology and PLoS ONE.

In The Last Decade

Daniel Nicorici

26 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Nicorici Finland 14 761 461 187 152 117 28 1.1k
Saori Fujiwara Japan 18 492 0.6× 384 0.8× 268 1.4× 122 0.8× 73 0.6× 34 845
Peiyong Guan Singapore 13 560 0.7× 308 0.7× 167 0.9× 104 0.7× 130 1.1× 26 897
Esther Andion Spain 3 1.1k 1.5× 558 1.2× 238 1.3× 321 2.1× 100 0.9× 3 1.7k
Zibin Jiang United States 11 577 0.8× 358 0.8× 287 1.5× 140 0.9× 68 0.6× 18 937
Hans Kristian Moen Vollan Norway 18 705 0.9× 573 1.2× 466 2.5× 213 1.4× 97 0.8× 25 1.3k
Kyle Furge United States 18 645 0.8× 286 0.6× 224 1.2× 368 2.4× 88 0.8× 20 1.0k
Kristen M. Turner United States 12 582 0.8× 476 1.0× 183 1.0× 61 0.4× 84 0.7× 24 957
Sabine Hellwig United States 10 455 0.6× 516 1.1× 237 1.3× 172 1.1× 100 0.9× 18 800
Atsushi Niida Japan 18 1.0k 1.4× 387 0.8× 361 1.9× 144 0.9× 122 1.0× 42 1.5k
Katharina König Germany 14 564 0.7× 246 0.5× 357 1.9× 231 1.5× 84 0.7× 20 1.0k

Countries citing papers authored by Daniel Nicorici

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Nicorici

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Nicorici

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Nicorici. A scholar is included among the top collaborators of Daniel Nicorici 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 Daniel Nicorici. Daniel Nicorici 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.
2.
Oksala, Riikka, Matias Knuuttila, Arfa Mehmood, et al.. (2018). Adrenals Contribute to Growth of Castration-Resistant VCaP Prostate Cancer Xenografts. American Journal Of Pathology. 188(12). 2890–2901. 18 indexed citations
3.
Björkman, Mari, Reetta Riikonen, Daniel Nicorici, et al.. (2018). Abstract 3970: Therapeutic targeting of estrogen receptor positive breast cancer with the BET bromodomain inhibitor ODM-207. Cancer Research. 78(13_Supplement). 3970–3970. 1 indexed citations
4.
Björkman, Mari, Elina Mattila, Reetta Riikonen, et al.. (2016). Abstract 4649: ODM-207, a novel BET-bromodomain inhibitor as a therapeutic approach for the treatment of prostate and breast cancer. Cancer Research. 76(14_Supplement). 4649–4649. 3 indexed citations
5.
Kangaspeska, Sara, et al.. (2012). Reanalysis of RNA-Sequencing Data Reveals Several Additional Fusion Genes with Multiple Isoforms. PLoS ONE. 7(10). e48745–e48745. 59 indexed citations
6.
Niemelä, Mika, Otto Kauko, Harri Sihto, et al.. (2012). CIP2A signature reveals the MYC dependency of CIP2A-regulated phenotypes and its clinical association with breast cancer subtypes. Oncogene. 31(39). 4266–4278. 63 indexed citations
7.
Östling, Päivi, Suvi‐Katri Leivonen, Anna Aakula, et al.. (2011). Systematic Analysis of MicroRNAs Targeting the Androgen Receptor in Prostate Cancer Cells. Cancer Research. 71(5). 1956–1967. 227 indexed citations
8.
Edgren, Henrik, Astrid Murumägi, Sara Kangaspeska, et al.. (2011). Identification of fusion genes in breast cancer by paired-end RNA-sequencing. Genome biology. 12(1). R6–R6. 226 indexed citations
9.
Juhila, Juuso, Tessa Sipilä, Daniel Nicorici, et al.. (2011). MicroRNA Expression Profiling Reveals MiRNA Families Regulating Specific Biological Pathways in Mouse Frontal Cortex and Hippocampus. PLoS ONE. 6(6). e21495–e21495. 61 indexed citations
10.
Östling, Päivi, Suvi‐Katri Leivonen, Anna Aakula, et al.. (2011). Abstract 3977: Systematic analysis of microRNAs targeting the androgen receptor in prostate cancer cells. Cancer Research. 71(8_Supplement). 3977–3977. 3 indexed citations
11.
Östling, Päivi, Suvi‐Katri Leivonen, Anna Aakula, et al.. (2010). Systematic analysis of microRNAs targeting the androgen receptor in prostate cancer cells. 8 indexed citations
12.
Mattila, Petri S., Jutta Renkonen, Sanna Toppila‐Salmi, et al.. (2009). Time‐series nasal epithelial transcriptomics during natural pollen exposure in healthy subjects and allergic patients. Allergy. 65(2). 175–183. 29 indexed citations
13.
Habermann, Jens K., Sampsa Hautaniemi, Uwe J. Roblick, et al.. (2008). The gene expression signature of genomic instability in breast cancer is an independent predictor of clinical outcome. International Journal of Cancer. 124(7). 1552–1564. 93 indexed citations
14.
Nicorici, Daniel, David Cogdell, Ioan Tăbuş, et al.. (2007). Analysis of Signaling Pathways in 90 Cancer Cell Lines by Protein Lysate Array. Journal of Proteome Research. 6(7). 2753–2767. 26 indexed citations
15.
Hautaniemi, Sampsa, Daniel Nicorici, Jarmo Laine, et al.. (2006). Transcriptional Profiling Reflects Shared and Unique Characters for CD34 + and CD133 + Cells. Stem Cells and Development. 15(6). 839–851. 24 indexed citations
16.
Arango, Diego, Päivi Laiho, Antti Kokko, et al.. (2005). Gene-Expression Profiling Predicts Recurrence in Dukes’ C Colorectal Cancer. Gastroenterology. 129(3). 874–884. 104 indexed citations
17.
Jaatinen, Taina, Sampsa Hautaniemi, Daniel Nicorici, et al.. (2005). Global Gene Expression Profile of Human Cord Blood–Derived CD133+ Cells. Stem Cells. 24(3). 631–641. 88 indexed citations
18.
Nicorici, Daniel & Jaakko Astola. (2004). Segmentation of DNA into Coding and Noncoding Regions Based on Recursive Entropic Segmentation and Stop-Codon Statistics. SHILAP Revista de lepidopterología.
19.
20.
Nicorici, Daniel & Jaakko Astola. (2003). Information divergence measures-for detection of borders between coding and noncoding DNA regions using recursive entropic segmentation. 3 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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