Raili Ermel

4.8k total citations · 1 hit paper
7 papers, 668 citations indexed

About

Raili Ermel is a scholar working on Molecular Biology, Genetics and Surgery. According to data from OpenAlex, Raili Ermel has authored 7 papers receiving a total of 668 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 4 papers in Genetics and 1 paper in Surgery. Recurrent topics in Raili Ermel's work include RNA modifications and cancer (5 papers), Genetic Associations and Epidemiology (4 papers) and Bioinformatics and Genomic Networks (4 papers). Raili Ermel is often cited by papers focused on RNA modifications and cancer (5 papers), Genetic Associations and Epidemiology (4 papers) and Bioinformatics and Genomic Networks (4 papers). Raili Ermel collaborates with scholars based in Estonia, United States and Sweden. Raili Ermel's co-authors include Johan Björkegren, Arno Ruusalepp, Ke Hao, Michael Wainberg, Thomas Quertermous, David E. Golan, Nasa Sinnott-Armstrong, Anshul Kundaje, Alvaro Barbeira and Manuel A. Rivas and has published in prestigious journals such as Nature Genetics, PLoS Genetics and Atherosclerosis.

In The Last Decade

Raili Ermel

7 papers receiving 664 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Opportunities and challenges for transcriptome-wide association studies

2019 506 citations Michael Wainberg, Nasa Sinnott-Armstrong et al. Nature Genetics profile →

Peers

Raili Ermel

MB

GENET

CR

IMMUN

PHYSI

Luciana Ribeiro Montenegro Brazil

Jai Rup Singh India

Sailaja Vedantam United States

Klea Lamnissou Greece

Matthew A. Lines Canada

Chupong Ittiwut Thailand

Chee‐Seng Ku Singapore

Shelly G. Smith United States

Yucheng Liao China

André Stutz Switzerland

Luciana Ribeiro Montenegro Brazil

Raili Ermel

512 ×1.2

MB

483 ×1.4

GENET

43 ×0.6

CR

29 ×0.5

IMMUN

39 ×0.9

PHYSI

Citations per year, relative to Raili Ermel Raili Ermel (= 1×) peers Luciana Ribeiro Montenegro

Countries citing papers authored by Raili Ermel

Since Specialization

Citations

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

Fields of papers citing papers by Raili Ermel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Raili Ermel

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

All Works

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7 of 7 papers shown

1.

Ma, Lijiang, Nicole S. Bryce, Adam W. Turner, et al.. (2022). The HDAC9-associated risk locus promotes coronary artery disease by governing TWIST1. PLoS Genetics. 18(6). e1010261–e1010261. 2 indexed citations

2.

Ma, Lijiang, Nirupama Chandel, Raili Ermel, et al.. (2020). Multiple independent mechanisms link gene polymorphisms in the region of ZEB2 with risk of coronary artery disease. Atherosclerosis. 311. 20–29. 8 indexed citations

3.

Brida, Margarita, Iveta Šimková, Ljiljana Jovović, et al.. (2020). European Society of Cardiology Working Group on Adult Congenital Heart Disease and Study Group for Adult Congenital Heart Care in Central and South Eastern European Countries consensus paper: current status, provision gaps and investment required. European Journal of Heart Failure. 23(3). 445–453. 8 indexed citations

4.

Wainberg, Michael, Nasa Sinnott-Armstrong, Nicholas Mancuso, et al.. (2019). Opportunities and challenges for transcriptome-wide association studies. Nature Genetics. 51(4). 592–599. 506 indexed citations breakdown →

5.

Franzén, Oscar, Raili Ermel, Katyayani Sukhavasi, et al.. (2018). Global analysis of A-to-I RNA editing reveals association with common disease variants. PeerJ. 6. e4466–e4466. 19 indexed citations

6.

Talukdar, Husain A., Hassan Foroughi Asl, Rajeev Jain, et al.. (2016). Cross-Tissue Regulatory Gene Networks in Coronary Artery Disease. Cell Systems. 2(3). 196–208. 96 indexed citations

7.

Asl, Hassan Foroughi, Husain A. Talukdar, Alida Kindt, et al.. (2015). Expression Quantitative Trait Loci Acting Across Multiple Tissues Are Enriched in Inherited Risk for Coronary Artery Disease. Circulation Cardiovascular Genetics. 8(2). 305–315. 29 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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