Maria Karaleftheri

3.0k total citations
9 papers, 178 citations indexed

About

Maria Karaleftheri is a scholar working on Genetics, Molecular Biology and Cancer Research. According to data from OpenAlex, Maria Karaleftheri has authored 9 papers receiving a total of 178 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Genetics, 5 papers in Molecular Biology and 3 papers in Cancer Research. Recurrent topics in Maria Karaleftheri's work include Genetic Associations and Epidemiology (7 papers), Bioinformatics and Genomic Networks (4 papers) and Advanced Proteomics Techniques and Applications (2 papers). Maria Karaleftheri is often cited by papers focused on Genetic Associations and Epidemiology (7 papers), Bioinformatics and Genomic Networks (4 papers) and Advanced Proteomics Techniques and Applications (2 papers). Maria Karaleftheri collaborates with scholars based in Greece, United Kingdom and Germany. Maria Karaleftheri's co-authors include Arthur Gilly, George Dedoussis, Emmanouil Tsafantakis, Eleftheria Zeggini, Nigel W. Rayner, Dániel Süveges, Lorraine Southam, Andrei Barysenka, Angela Matchan and Aliki‐Eleni Farmaki and has published in prestigious journals such as Nature Communications, Scientific Reports and Human Molecular Genetics.

In The Last Decade

Maria Karaleftheri

9 papers receiving 177 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Maria Karaleftheri Greece	5	92	74	26	25	12	9	178
Mine Koprulu United Kingdom	7	81 0.9×	102 1.4×	15 0.6×	14 0.6×	11 0.9×	13	193
Sofia Bosdotter Enroth Sweden	6	62 0.7×	86 1.2×	45 1.7×	36 1.4×	7 0.6×	6	217
Rungnapa Ittiwut Thailand	10	83 0.9×	85 1.1×	10 0.4×	17 0.7×	11 0.9×	26	213
Evelina Mocci United States	8	98 1.1×	63 0.9×	45 1.7×	13 0.5×	8 0.7×	18	204
Ji Hee Oh South Korea	11	95 1.0×	96 1.3×	13 0.5×	13 0.5×	18 1.5×	15	213
Kazuhiko Yamamoto Japan	3	119 1.3×	82 1.1×	24 0.9×	47 1.9×	16 1.3×	3	226
Lea Velsher Canada	8	91 1.0×	61 0.8×	22 0.8×	20 0.8×	16 1.3×	18	181
Christina Willenborg Germany	7	49 0.5×	85 1.1×	11 0.4×	16 0.6×	14 1.2×	11	182
Ping Mayo United States	8	74 0.8×	78 1.1×	20 0.8×	8 0.3×	21 1.8×	8	195
Vinh Trương France	6	61 0.7×	87 1.2×	21 0.8×	31 1.2×	7 0.6×	9	177

Countries citing papers authored by Maria Karaleftheri

Since Specialization

Citations

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

Fields of papers citing papers by Maria Karaleftheri

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maria Karaleftheri

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

All Works

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9 of 9 papers shown

Gilly, Arthur, et al.. (2023). Genome-wide meta-analysis of 92 cardiometabolic protein serum levels. Molecular Metabolism. 78. 101810–101810. 2 indexed citations

Gerlini, Raffaele, Konstantinos Hatzikotoulas, Andrei Barysenka, et al.. (2022). Identifying causal serum protein–cardiometabolic trait relationships using whole genome sequencing. Human Molecular Genetics. 32(8). 1266–1275. 8 indexed citations

Gilly, Arthur, Lucija Klarić, Andrei Barysenka, et al.. (2022). Gene-based whole genome sequencing meta-analysis of 250 circulating proteins in three isolated European populations. Molecular Metabolism. 61. 101509–101509. 4 indexed citations

Kuchenbaecker, Karoline, Arthur Gilly, Dániel Süveges, et al.. (2022). Insights into the genetic architecture of haematological traits from deep phenotyping and whole-genome sequencing for two Mediterranean isolated populations. Scientific Reports. 12(1). 1131–1131. 2 indexed citations

Barysenka, Andrei, Pau Navarro, Xia Shen, et al.. (2021). Mapping the serum proteome to neurological diseases using whole genome sequencing. Nature Communications. 12(1). 7042–7042. 34 indexed citations

Gilly, Arthur, Andrei Barysenka, Iris Fischer, et al.. (2020). Whole-genome sequencing analysis of the cardiometabolic proteome. Nature Communications. 11(1). 6336–6336. 61 indexed citations

Farmaki, Aliki‐Eleni, Nigel W. Rayner, Angela Matchan, et al.. (2019). A Dietary Pattern with High Sugar Content Is Associated with Cardiometabolic Risk Factors in the Pomak Population. Nutrients. 11(12). 3043–3043. 12 indexed citations

Süveges, Dániel, Klaudia Walter, Kousik Kundu, et al.. (2019). Population‐wide copy number variation calling using variant call format files from 6,898 individuals. Genetic Epidemiology. 44(1). 79–89. 3 indexed citations

Southam, Lorraine, Arthur Gilly, Dániel Süveges, et al.. (2017). Whole genome sequencing and imputation in isolated populations identify genetic associations with medically-relevant complex traits. Nature Communications. 8(1). 15606–15606. 52 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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