Non-coding RNA Research

429 papers and 5.4k indexed citations

About

The 429 papers published in Non-coding RNA Research in the last decades have received a total of 5.4k indexed citations. Papers published in Non-coding RNA Research usually cover Cancer Research (353 papers), Molecular Biology (349 papers) and Immunology (28 papers) specifically the topics of Cancer-related molecular mechanisms research (279 papers), MicroRNA in disease regulation (214 papers) and Circular RNAs in diseases (182 papers). The most active scholars publishing in Non-coding RNA Research are Aaron M. Johnson, Maggie M. Balas, Ozal Beylerli, Tatiana Ilyasova, Bernhard Biersack, R.A. Youness, Albert Sufianov, Mohamed Z. Gad, Ilgiz Gareev and Johanna K. DiStefano.

In The Last Decade

Non-coding RNA Research

384 papers receiving 5.4k citations

Countries where authors publish in Non-coding RNA Research

Since Specialization
Citations

This map shows the geographic impact of research published in Non-coding RNA 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 papers published in Non-coding RNA Research with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Non-coding RNA Research more than expected).

Fields of papers published in Non-coding RNA Research

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Non-coding RNA Research. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Non-coding RNA Research.

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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