Daniela Grasso

671 citations
17 papers · 390 · h-index 10

Impact in

  • Neurology top 5%
    • Amyotrophic Lateral Sclerosis Research
    • Parkinson's Disease Mechanisms and Treatments
    • Neurological diseases and metabolism
  • Genetics top 10%
    • Neurogenetic and Muscular Disorders Research

Papers in

Daniela Grasso

16 papers receiving 377 citations

Peers

Daniela Grasso
Comparison fields: 5 of 95
  • Neurology 199
  • Genetics 124
  • Neurology 26
  • Biological Psychiatry 5
  • Pharmacology 32
Replace Bo Cui with:
Bo Cui China
Fangfang Hu China
Ryan J. Smart United States
Laura Moreno‐Martínez Spain
Bo Cui China
Chuan Shao China
Mohammed Alshareef United States
Lorenzo Peverelli Italy
A. Lilja Sweden
Yukiko Ozawa Japan
Daniela Grasso relative to Bo Cui China Bo Cui's profile →
Citations per field
00.5×1.5×2.5×
Bo Cui · 1×
Citations per year

Countries citing papers authored by Daniela Grasso

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Grasso

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 200879
2 201075
3 201247
4 201337
5 201835
6 200323
7 200621
8 202411
9 200511
10 201010
11 20229
12 20228
13 20238
14 20076
15 20225
16 20155
17 20250

About Daniela Grasso

Daniela Grasso is a scholar working on Molecular Biology, Neurology, Surgery, Pulmonary and Respiratory Medicine and Genetics, having authored 17 papers that have together received 390 indexed citations. Recurring topics across this work include Amyotrophic Lateral Sclerosis Research (5 papers), Metabolomics and Mass Spectrometry Studies (2 papers), Sarcoma Diagnosis and Treatment (2 papers), Mechanical Circulatory Support Devices (2 papers), Metabolism and Genetic Disorders (1 paper), Computational Drug Discovery Methods (1 paper), Vascular Tumors and Angiosarcomas (1 paper) and Cancer, Lipids, and Metabolism (1 paper). The work is most often cited by research in Neurology (199 citations), Genetics (124 citations), Neurology (26 citations), Biological Psychiatry (5 citations) and Pharmacology (32 citations). Daniela Grasso has collaborated with scholars based in Italy and United States. Frequent co-authors include Merit Cudkowicz, Jeremy M. Shefner, Elizabeth Simpson, Carmen Castrillo‐Viguera, Hong Yu, Amy M. Shui, Robert H. Brown, Jack R. Barber, David Schoenfeld and Hui Zhang. Their work appears in journals such as International Journal of Molecular Sciences, Cancers, Artificial Organs, Annals of Clinical and Translational Neurology and Muscle & Nerve.

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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