Maya Ghoussaini

14.7k citations
16 papers · 932 indexed · 1 hit paper · h-index 15
Topics
Genetic Associations and Epidemiology (9 papers)Bioinformatics and Genomic Networks (3 papers)Adipose Tissue and Metabolism (3 papers)

In The Last Decade

Maya Ghoussaini

15 papers receiving 918 citations

Hit Papers

An open approach to systematically prioritize causal vari...2021202620222024202150100150200

Peers

Maya Ghoussaini
Comparison fields: 5 of 90
  • Molecular Biology 565
  • Genetics 363
  • Cancer Research 146
  • Physiology 106
  • Epidemiology 83
Replace Ioannis M. Stylianou with:
Ioannis M. Stylianou United States
Ramu Elango Saudi Arabia
Jiuyong Xie Canada
Zoë May Pendlington United Kingdom
Emily Bowler-Barnett United Kingdom
Sylvie Giroux Canada
Jannel Liu United States
Anuar Konkashbaev United States
Cankut Çubuk United Kingdom
Isabel Sousa Portugal
Maya Ghoussaini relative to Ioannis M. Stylianou United States Ioannis M. Stylianou's profile →
Citations per field
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Ioannis M. Stylianou · 1×
Citations per year

Countries citing papers authored by Maya Ghoussaini

Since Specialization
Citations

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

Fields of papers citing papers by Maya Ghoussaini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maya Ghoussaini

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

All Works

16 of 16 papers shown
#WorkIndexed citations
1 0
2 42
3 14
4 14
5 95
6
An open approach to systematically prioritize causal variants and genes at all published human GWAS trait-associated locibreakdown →
223
7 127
8 21
9 61
10 123
11 14
12 36
13 29
14 25
15 17
16 91

About Maya Ghoussaini

Maya Ghoussaini is a scholar working on Genetics, Endocrine and Autonomic Systems and Molecular Biology, having authored 16 papers that have together received 932 indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (9 papers), Bioinformatics and Genomic Networks (3 papers) and Adipose Tissue and Metabolism (3 papers). The work is most often cited by research in Genetics (363 citations), Cancer Research (146 citations) and Molecular Biology (565 citations). Maya Ghoussaini has collaborated with scholars based in United Kingdom, United States and France. Frequent co-authors include Ian Dunham, Paul D.P. Pharoah, David Ochoa, Mohd Anisul Karim, Edward Mountjoy, Douglas F. Easton, Philippe Froguel, Ellen M. McDonagh, David G. Hulcoop and Jeremy Schwartzentruber. Their work appears in journals such as Nature Genetics, The Journal of Clinical Endocrinology & Metabolism and Nature Reviews Drug Discovery.

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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