Iris Soveral

925 citations
18 papers · 736 · h-index 10

Impact in

  • Aging top 10%
    • Genetics, Aging, and Longevity in Model Organisms
  • Epidemiology top 10%
    • Cervical Cancer and HPV Research
    • Congenital Heart Disease Studies

Papers in

    • Congenital Heart Disease Studies 13
    • Cervical Cancer and HPV Research 1
    • Genetics, Aging, and Longevity in Model Organisms 1

Iris Soveral

18 papers receiving 711 citations

Peers

Iris Soveral
Comparison fields: 5 of 93
  • Aging 30
  • Epidemiology 277
  • Obstetrics and Gynecology 67
  • Biological Psychiatry 5
  • Immunology 61
Replace Hong Lv with:
Hong Lv China
Milica Stojković Lalošević Serbia
Matias Epifânio Brazil
Charalampos Siristatidis Greece
Danielle J. Borg Australia
Björn Roelstraete Sweden
Tahir Saghir Pakistan
Binghua Zhu China
Cilmery Suemi Kurokawa Brazil
Helga Toenhake-Dijkstra Netherlands
Iris Soveral relative to Hong Lv China Hong Lv's profile →
Citations per field
00.5×2×4×5.2×
Hong Lv · 1×
Citations per year

Countries citing papers authored by Iris Soveral

Since Specialization
Citations

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

Fields of papers citing papers by Iris Soveral

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Iris Soveral, 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 Iris Soveral Line = papers co-authored together Iris Soveral links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 2013358
2 2014178
3 201939
4 202030
5 201324
6 201524
7 202020
8 201912
9 202010
10 202010
11 20189
12 20209
13 20145
14 20173
15 20232
16 20221
17 20231
18 20251

About Iris Soveral

Iris Soveral is a scholar working on Epidemiology, Aging, Cardiology and Cardiovascular Medicine, Pediatrics, Perinatology and Child Health and Cancer Research, having authored 18 papers that have together received 736 indexed citations. Recurring topics across this work include Congenital Heart Disease Studies (13 papers), Cardiovascular Function and Risk Factors (2 papers), Cervical Cancer and HPV Research (1 paper), Prenatal Screening and Diagnostics (1 paper), Genetics, Aging, and Longevity in Model Organisms (1 paper), Menopause: Health Impacts and Treatments (1 paper), T-cell and B-cell Immunology (1 paper) and Breast Cancer Treatment Studies (1 paper). The work is most often cited by research in Aging (30 citations), Epidemiology (277 citations), Obstetrics and Gynecology (67 citations), Biological Psychiatry (5 citations) and Immunology (61 citations). Iris Soveral has collaborated with scholars based in Spain, Chile and Colombia. Frequent co-authors include Camil Castelo‐Branco, Jaume Ordï, Aureli Torné, Lorena Marimón, Jaume Pahisa, Renske D.M. Steenbergen, Leonardo Rodríguez‐Carunchio, Pere Fusté, Marta l De Pino and O. Gómez. Their work appears in journals such as Fetal Diagnosis and Therapy, Ultrasound in Obstetrics and Gynecology, PLoS Computational Biology, BJOG An International Journal of Obstetrics & Gynaecology and Journal of Clinical Medicine.

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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