Gian Garriga

5.0k citations
70 papers · 4.1k indexed · h-index 35

Impact in

Papers in

Gian Garriga

70 papers receiving 4.0k citations

Peers

Gian Garriga
Comparison fields: 5 of 128
  • Aging 2.1k
  • Endocrine and Autonomic Systems 743
  • Cellular and Molecular Neuroscience 933
  • Cell Biology 795
  • Developmental Neuroscience 191
Replace Keiko Gengyo‐Ando with:
Keiko Gengyo‐Ando Japan
Erika Hartwieg United States
Shai Shaham United States
Yasumi Ohshima Japan
Harald Hutter Canada
Alvaro Sagasti United States
Massimo A. Hilliard Australia
Michael L. Nonet United States
Michael J. Bastiani United States
Lizabeth A. Perkins United States
Gian Garriga relative to Keiko Gengyo‐Ando Japan Keiko Gengyo‐Ando's profile →
Citations per field
00.5×3.5×
Keiko Gengyo‐Ando · 1×
Citations per year

Countries citing papers authored by Gian Garriga

Since Specialization
Citations

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

Fields of papers citing papers by Gian Garriga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 201514
2 201418
3 201237
4 201026
5 200842
6 200728
7 20078
8 200629
9 2006135
10 200514
11 200529
12 200528
13 200531
14 200311
15 1999144
16 199729
17 1997155
18 199068
19 1988412
20 19822

About Gian Garriga

Gian Garriga is a scholar working on Aging, Endocrine and Autonomic Systems, Cellular and Molecular Neuroscience, Cell Biology and Molecular Biology, having authored 70 papers that have together received 4.1k indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (52 papers), Circadian rhythm and melatonin (20 papers), Mitochondrial Function and Pathology (11 papers), Spaceflight effects on biology (11 papers), Axon Guidance and Neuronal Signaling (10 papers), RNA and protein synthesis mechanisms (9 papers), Pluripotent Stem Cells Research (8 papers) and RNA Research and Splicing (8 papers). The work is most often cited by research in Aging (2.1k citations), Endocrine and Autonomic Systems (743 citations), Cellular and Molecular Neuroscience (933 citations), Cell Biology (795 citations) and Developmental Neuroscience (191 citations). Gian Garriga has collaborated with scholars based in United States, Canada and Belgium. Frequent co-authors include Alan M. Lambowitz, Wayne C. Forrester, Chand Desai, Paul Baum, H. Robert Horvitz, H. Robert Horvitz, Nancy Hawkins, David Weinshenker, Catherine Guenther and Scott G. Clark. Their work appears in journals such as Development, Genetics, Cell, Developmental Biology and Neuron.

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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