E M Pietilä

416 total citations
10 papers, 340 citations indexed

About

E M Pietilä is a scholar working on Molecular Biology, Reproductive Medicine and Agronomy and Crop Science. According to data from OpenAlex, E M Pietilä has authored 10 papers receiving a total of 340 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 3 papers in Reproductive Medicine and 2 papers in Agronomy and Crop Science. Recurrent topics in E M Pietilä's work include Hypothalamic control of reproductive hormones (2 papers), Receptor Mechanisms and Signaling (2 papers) and Reproductive Physiology in Livestock (2 papers). E M Pietilä is often cited by papers focused on Hypothalamic control of reproductive hormones (2 papers), Receptor Mechanisms and Signaling (2 papers) and Reproductive Physiology in Livestock (2 papers). E M Pietilä collaborates with scholars based in Finland, Sweden and Poland. E M Pietilä's co-authors include Hannu Rajaniemi, Jouni Lakkakorpi, Ulla E. Petäjä‐Repo, Jussi Tuusa, Pirjo M. Apaja, Kimmo Kontula, Y. Antero Kesäniemi, Heikki Swan, Markku J. Savolainen and Heikki V. Huikuri and has published in prestigious journals such as Journal of Biological Chemistry, Journal of the American College of Cardiology and Molecular Biology of the Cell.

In The Last Decade

E M Pietilä

10 papers receiving 335 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
E M Pietilä Finland 8 208 104 80 55 49 10 340
Tomislav Modric United States 8 150 0.7× 20 0.2× 45 0.6× 75 1.4× 34 0.7× 11 382
Adam J. Koch United States 10 350 1.7× 97 0.9× 20 0.3× 70 1.3× 12 0.2× 10 466
Kemian Gou China 12 211 1.0× 40 0.4× 10 0.1× 74 1.3× 13 0.3× 37 398
Ida Björkgren Finland 11 195 0.9× 213 2.0× 12 0.1× 87 1.6× 23 0.5× 18 435
Masaaki Hattori Japan 11 129 0.6× 143 1.4× 8 0.1× 92 1.7× 14 0.3× 23 394
Edmir Nicola Canada 8 175 0.8× 99 1.0× 18 0.2× 91 1.7× 6 0.1× 10 370
M Noe United States 6 175 0.8× 30 0.3× 31 0.4× 24 0.4× 144 2.9× 7 343
A. Guzmán Mexico 10 108 0.5× 96 0.9× 8 0.1× 47 0.9× 9 0.2× 26 265
Marion Spitschak Germany 12 113 0.5× 70 0.7× 12 0.1× 107 1.9× 6 0.1× 20 372
Mathias Rouard United States 10 149 0.7× 24 0.2× 9 0.1× 120 2.2× 12 0.2× 10 356

Countries citing papers authored by E M Pietilä

Since Specialization
Citations

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

Fields of papers citing papers by E M Pietilä

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of E M Pietilä

This figure shows the co-authorship network connecting the top 25 collaborators of E M Pietilä. A scholar is included among the top collaborators of E M Pietilä 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 E M Pietilä. E M Pietilä 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.
Pietilä, E M, Eliisa Löyttyniemi, Seppo Koskinen, et al.. (2025). Enhancing dementia prediction: A 19-year validation of the CAIDE risk score with insulin resistance and APOE ε4 integration in a population-based cohort. The Journal of Prevention of Alzheimer s Disease. 12(2). 100034–100034. 1 indexed citations
2.
Apaja, Pirjo M., Jussi Tuusa, E M Pietilä, Hannu Rajaniemi, & Ulla E. Petäjä‐Repo. (2006). Luteinizing Hormone Receptor Ectodomain Splice Variant Misroutes the Full-Length Receptor into a Subcompartment of the Endoplasmic Reticulum. Molecular Biology of the Cell. 17(5). 2243–2255. 43 indexed citations
3.
Pietilä, E M, et al.. (2005). Inefficient Maturation of the Rat Luteinizing Hormone Receptor. Journal of Biological Chemistry. 280(28). 26622–26629. 67 indexed citations
4.
Pietilä, E M, Heidi Fodstad, Heikki Swan, et al.. (2002). association between HERG K897T polymorphism and QT interval in middle-aged finnish women. Journal of the American College of Cardiology. 40(3). 511–514. 78 indexed citations
5.
Pietilä, E M, et al.. (1996). Expression of the LH-CG receptor gene in various rat tissues. 47(1). 2 indexed citations
6.
Rajaniemi, Hannu, Ulla E. Petäjä‐Repo, & E M Pietilä. (1996). Structure and functional significance of the carbohydrates of the LH/CG receptor. Molecular and Cellular Endocrinology. 125(1-2). 101–105. 8 indexed citations
7.
Derecka, K., E M Pietilä, Hannu Rajaniemi, & Adam J. Ziȩcik. (1995). Cycle dependent LH/hCG receptor gene expression in porcine nongonadal reproductive tissues.. PubMed. 46(1). 77–85. 23 indexed citations
8.
Lakkakorpi, Jouni, et al.. (1994). A coupled one-step reverse transcription PCR procedure for generation of full-length open reading frames.. PubMed. 16(2). 282–4, 286. 37 indexed citations
10.
Pietilä, E M, et al.. (1992). Expression of the LH/CG receptor gene in rat ovarian tissue is regulated by an extensive alternative splicing of the primary transcript. Molecular and Cellular Endocrinology. 84(1-2). 127–135. 60 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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