Gene Expression Patterns

1.3k papers and 28.6k indexed citations
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About

The 1.3k papers published in Gene Expression Patterns in the last decades have received a total of 28.6k indexed citations. Papers published in Gene Expression Patterns usually cover Molecular Biology (1.0k papers), Genetics (286 papers) and Cell Biology (245 papers) specifically the topics of Developmental Biology and Gene Regulation (313 papers), Congenital heart defects research (190 papers) and Genetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities (97 papers). The most active scholars publishing in Gene Expression Patterns are Pamela A. Raymond, Rebecca Bernardos, Hermann Aberle, Subhabrata Sanyal, Eric H. Davidson, Paul M. Salvaterra, Toshihiro Kitamoto, John H. Postlethwait, Dong‐Hua Yang and Eric G. Moss.

In The Last Decade

Gene Expression Patterns

1.3k papers receiving 27.5k citations

Fields of papers published in Gene Expression Patterns

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Gene Expression Patterns. 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 Gene Expression Patterns.

Countries where authors publish in Gene Expression Patterns

Since Specialization
Citations

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

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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