Daniel Motola

3.0k citations
18 papers · 1.8k indexed · h-index 14

Impact in

Papers in

    • Genetics, Aging, and Longevity in Model Organisms 3
    • Liver Disease and Transplantation 3

Daniel Motola

18 papers receiving 1.8k citations

Peers

Daniel Motola
Comparison fields: 5 of 99
  • Aging 602
  • Endocrine and Autonomic Systems 311
  • Parasitology 119
  • Endocrinology, Diabetes and Metabolism 268
  • Pathology and Forensic Medicine 260
Replace Matthew R. Gangl with:
Matthew R. Gangl United States
Joseph M. Dhahbi United States
Eek Joong Park United States
Kerstin Bellmann Canada
Sherry F. Grissom United States
Elmus Beale United States
Takamasa Ishii Japan
Hyeog Kang United States
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Citations per field
00.5×7.6×
Matthew R. Gangl · 1×
Citations per year

Countries citing papers authored by Daniel Motola

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Motola

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 20243
2 201719
3 201774
4 201656
5 20165
6 2015224
7 201424
8 20141
9 20131
10 201156
11 201131
12 200933
13 200998
14 2007187
15 2006160
16 2006396
17 2004122
18 2003292

About Daniel Motola

Daniel Motola is a scholar working on Aging, Hepatology, Endocrine and Autonomic Systems, Parasitology and Endocrinology, Diabetes and Metabolism, having authored 18 papers that have together received 1.8k indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (5 papers), Hormonal Regulation and Hypertension (4 papers), Circadian rhythm and melatonin (3 papers), Genetics, Aging, and Longevity in Model Organisms (3 papers), Liver Disease and Transplantation (3 papers), Helminth infection and control (2 papers), Parasites and Host Interactions (2 papers) and Cancer Risks and Factors (1 paper). The work is most often cited by research in Aging (602 citations), Endocrine and Autonomic Systems (311 citations), Parasitology (119 citations), Endocrinology, Diabetes and Metabolism (268 citations) and Pathology and Forensic Medicine (260 citations). Daniel Motola has collaborated with scholars based in United States, Mexico and Germany. Frequent co-authors include David J. Mangelsdorf, Carolyn L. Cummins, Adam Antebi, Veerle Rottiers, David W. Russell, Jeffrey B. Cheng, Kamalesh Kumar Sharma, Richard J. Auchus, Birgit Gerisch and H. Eric Xu. Their work appears in journals such as Journal of Biological Chemistry, Journal of Clinical Oncology, Proceedings of the National Academy of Sciences, Molecular Endocrinology and Scientific Reports.

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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