Idit Maya

1.5k citations
60 papers · 826 · h-index 16

Impact in

Papers in

Idit Maya

51 papers receiving 786 citations

Peers

Idit Maya
Comparison fields: 5 of 66
  • Pediatrics, Perinatology and Child Health 489
  • Genetics 371
  • Developmental Biology 15
  • Infectious Diseases 93
  • Molecular Biology 258
Replace Malgorzata I. Srebniak with:
Malgorzata I. Srebniak Netherlands
Fang Fu China
Amihood Singer Israel
Emilia K. Bijlsma Netherlands
Chen‐Chi Lee Taiwan
Lutgarde Govaerts Netherlands
Anna Cereda Italy
Melissa Maisenbacher United States
Alida C. Knegt Netherlands
Robert Saura France
Idit Maya relative to Malgorzata I. Srebniak Netherlands Malgorzata I. Srebniak's profile →
Citations per field
00.5×1.5×
Malgorzata I. Srebniak · 1×
Citations per year

Countries citing papers authored by Idit Maya

Since Specialization
Citations

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

Fields of papers citing papers by Idit Maya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Idit Maya, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Idit Maya Line = papers co-authored together Idit Maya links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011112
2 201061
3 201953
4 201746
5 201746
6 201438
7 201636
8 201527
9 201826
10 201323
11 201423
12
Chromosomal Microarray Analysis (CMA) a Clinical Diagnostic Tool in the Prenatal and Postnatal Settings.
201522
13 202019
14 201818
15 201816
16 202115
17 201715
18 201814
19 202014
20 201913

About Idit Maya

Idit Maya is a scholar working on Pediatrics, Perinatology and Child Health, Genetics, Molecular Biology, Surgery and Epidemiology, having authored 60 papers that have together received 826 indexed citations. Recurring topics across this work include Prenatal Screening and Diagnostics (40 papers), Genomic variations and chromosomal abnormalities (30 papers), Fetal and Pediatric Neurological Disorders (19 papers), Congenital Anomalies and Fetal Surgery (8 papers), Genomics and Rare Diseases (8 papers), Parvovirus B19 Infection Studies (5 papers), Congenital heart defects research (5 papers) and Congenital Heart Disease Studies (5 papers). The work is most often cited by research in Pediatrics, Perinatology and Child Health (489 citations), Genetics (371 citations), Developmental Biology (15 citations), Infectious Diseases (93 citations) and Molecular Biology (258 citations). Idit Maya has collaborated with scholars based in Israel, United States and United Kingdom. Frequent co-authors include Lena Sagi‐Dain, Sarit Kahana, Lina Basel‐Vanagaite, Mordechai Shohat, Amihood Singer, Tamar Tenne, Josepha Yeshaya, Shiri Yacobson, Lina Basel‐Salmon and Reuven Sharony. Their work appears in journals such as Genetics in Medicine, Journal of Perinatal Medicine, Ultrasound in Obstetrics and Gynecology, American Journal of Obstetrics and Gynecology and Archives of Gynecology and Obstetrics.

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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