Daniel Grasso

40 papers receiving 3.3k citations

Daniel Grasso's Hit Papers

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition) 1 2021 · 2.1k citations
2.1k0+1+3Years since publication5001k1.5k2k

Peers

Daniel Grasso
Comparison fields: 5 of 118
  • Epidemiology 1.6k
  • Aging 36
  • Cell Biology 198
  • Cancer Research 139
  • Molecular Biology 622
Replace I‐Lun Hsin with:
I‐Lun Hsin Taiwan
Venturina Stagni Italy
Sonia Castillo‐Lluva Spain
Katie Marchbank United States
Tapas Saha United States
Morten Luhr Norway
Hernán Roca United States
Luciana Rodrigues Gomes Brazil
Leopold F. Fröhlich Germany
Daniel Grasso relative to I‐Lun Hsin Taiwan I‐Lun Hsin's profile →
Citations per field
00.5×1.5×2.2×
I‐Lun Hsin · 1×
Citations per year

Countries citing papers authored by Daniel Grasso

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Grasso

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition) 1
Hit paper breakdown →
20212067
2 2007193
3 2010173
4 2017173
5 201271
6 202166
7 200852
8 201845
9 201444
10 201843
11 201439
12 201338
13 200336
14 202230
15 200828
16 201228
17 201528
18 200027
19 202127
20 201224

About Daniel Grasso

Daniel Grasso is a scholar working on Epidemiology, Oncology, Immunology, Virology and Physiology, having authored 42 papers that have together received 3.4k indexed citations. Recurring topics across this work include Autophagy in Disease and Therapy (18 papers), Pancreatic and Hepatic Oncology Research (6 papers), Pancreatitis Pathology and Treatment (5 papers), Telomeres, Telomerase, and Senescence (4 papers), HIV Research and Treatment (2 papers), Cancer-related Molecular Pathways (2 papers), Salmonella and Campylobacter epidemiology (2 papers) and Cell death mechanisms and regulation (2 papers). The work is most often cited by research in Epidemiology (1.6k citations), Aging (36 citations), Cell Biology (198 citations), Cancer Research (139 citations) and Molecular Biology (622 citations). Daniel Grasso has collaborated with scholars based in Argentina, France and United States. Frequent co-authors include María I. Vaccaro, Juan Iovanna, Alejandro Ropolo, Raul A. Urrutia, María Noé Garcia, Claudio Daniel González, Andrea Lo Ré, Gwen Alyce Lomberk, María Inés Molejon and Nicolas Dupont. Their work appears in journals such as Frontiers in Oncology, Autophagy, Frontiers in Cell and Developmental Biology, PLoS ONE and Journal of Biological Chemistry.

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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