Alex Appert

1.5k citations
17 papers · 689 · h-index 12

Impact in

  • Aging top 1%
    • Genetics, Aging, and Longevity in Model Organisms
    • NF-κB Signaling Pathways

Papers in

    • Genomics and Chromatin Dynamics 4
    • Epigenetics and DNA Methylation 3
    • CRISPR and Genetic Engineering 3
    • Genetics, Aging, and Longevity in Model Organisms 7

Alex Appert

17 papers receiving 686 citations

Peers

Alex Appert
Comparison fields: 5 of 77
  • Aging 175
  • Cancer Research 165
  • Immunology 152
  • Molecular Biology 444
  • Pathology and Forensic Medicine 97
Replace Jennifer L. Schutzman with:
Jennifer L. Schutzman United States
Daniel Fitzsimmons United States
Meta W. Djojosubroto Germany
Sarantis Gagos Greece
Pınar Akçakaya Sweden
İlgen Mender United States
Rachel Litman Flynn United States
Klaus Fortschegger Austria
Marcin M. Gorski Italy
Alex Appert relative to Jennifer L. Schutzman United States Jennifer L. Schutzman's profile →
Citations per field
00.5×3.7×
Jennifer L. Schutzman · 1×
Citations per year

Countries citing papers authored by Alex Appert

Since Specialization
Citations

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

Fields of papers citing papers by Alex Appert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 2011120
2 201089
3 201782
4 201862
5 201262
6 201150
7 201547
8 200936
9 200836
10 201935
11 201325
12 202013
13 202110
14
Factors X Nice I and II: two novel missense mutations (Met-40Val and Pro304Ser) in patient with coagulation factor X deficiency.
19987
15 20226
16 20216
17 20253

About Alex Appert

Alex Appert is a scholar working on Molecular Biology, Aging, Oncology, Plant Science and Cancer Research, having authored 17 papers that have together received 689 indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (7 papers), Genomics and Chromatin Dynamics (4 papers), NF-κB Signaling Pathways (4 papers), Lymphoma Diagnosis and Treatment (3 papers), Epigenetics and DNA Methylation (3 papers), CRISPR and Genetic Engineering (3 papers), Plant Molecular Biology Research (2 papers) and Cytokine Signaling Pathways and Interactions (2 papers). The work is most often cited by research in Aging (175 citations), Cancer Research (165 citations), Immunology (152 citations), Molecular Biology (444 citations) and Pathology and Forensic Medicine (97 citations). Alex Appert has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Julie Ahringer, Przemysław Stempor, Dong Yan, Rifat Hamoudi, Ni Huang, Ming‐Qing Du, Ingrid J. Apel, Peter C. Lucas, Linda M. McAllister‐Lucas and Shaun Rosebeck. Their work appears in journals such as PLoS Genetics, eLife, Oncogene, Genes & Development and Clinical Cancer Research.

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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