Guy Las

16 papers receiving 3.6k citations

Guy Las's Hit Papers

Fission and selective fusion govern mitochondrial segregation and elimination by autophagy 2008 · 2.4k citations
2.4k0+6+12Years since publication50010001.5k2.0k

Peers

Guy Las
Comparison fields: 5 of 99
  • Clinical Biochemistry 561
  • Aging 90
  • Molecular Biology 2.7k
  • Epidemiology 1.4k
  • Physiology 886
Replace Sarah E. Haigh with:
Sarah E. Haigh United States
Olga Martins de Brito Italy
Julien Prudent United Kingdom
Sumihiro Kawajiri Japan
Gian‐Luca McLelland Canada
Vincent Soubannier Canada
Seok Min Jin United States
Sven Geisler Germany
Scott A. Detmer United States
María Eugenia Soriano Italy
Guy Las relative to Sarah E. Haigh United States Sarah E. Haigh's profile →
Citations per field
00.5×1.5×1.8×
Sarah E. Haigh · 1×
Citations per year

Countries citing papers authored by Guy Las

Since Specialization
Citations

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

Fields of papers citing papers by Guy Las

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1
Fission and selective fusion govern mitochondrial segregation and elimination by autophagy
Hit paper breakdown →
20082432
2 2009312
3 2014201
4 2011173
5 2014103
6 201076
7 201669
8 201055
9 202038
10 202033
11 201731
12 201830
13 201719
14 202013
15 20218
16 20068
17 20110

About Guy Las

Guy Las is a scholar working on Molecular Biology, Epidemiology, Surgery, Physiology and Cell Biology, having authored 17 papers that have together received 3.6k indexed citations. Recurring topics across this work include Mitochondrial Function and Pathology (9 papers), Autophagy in Disease and Therapy (7 papers), Pancreatic function and diabetes (5 papers), Adipose Tissue and Metabolism (4 papers), Endoplasmic Reticulum Stress and Disease (3 papers), Metabolism and Genetic Disorders (2 papers), Neonatal Health and Biochemistry (2 papers) and Calcium signaling and nucleotide metabolism (2 papers). The work is most often cited by research in Clinical Biochemistry (561 citations), Aging (90 citations), Molecular Biology (2.7k citations), Epidemiology (1.4k citations) and Physiology (886 citations). Guy Las has collaborated with scholars based in United States, Israel and Sweden. Frequent co-authors include Orian S. Shirihai, Jakob D. Wikström, Gilad Twig, Barbara E. Corkey, Anthony Molina, Linsey Stiles, Álvaro A. Elorza, Bénédicte F. Py, Min Wu and Jude T. Deeney. Their work appears in journals such as The EMBO Journal, Diabetes, The FASEB Journal, Diabetes Obesity and Metabolism and The Journal of Cell Biology.

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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