Maria Li

1.2k citations
15 papers · 906 indexed · h-index 11

Maria Li

15 papers receiving 901 citations

Peers

Maria Li
Comparison fields: 5 of 83
  • Insect Science 449
  • Developmental Neuroscience 96
  • Cellular and Molecular Neuroscience 362
  • Ecology 268
  • Genetics 191
Replace Amelia Younossi‐Hartenstein with:
Amelia Younossi‐Hartenstein United States
Jonathan C. Radford United Kingdom
Hirofumi Noguchi Japan
David A. Willoughby United States
Yukari Komuta Japan
Graham Huesmann United States
Qingzhong Ren United States
Andreas Ratzka Germany
E. Jay Rehm United States
Maria Li relative to Amelia Younossi‐Hartenstein United States Amelia Younossi‐Hartenstein's profile →
Citations per field
00.5×3.4×
Amelia Younossi‐Hartenstein · 1×
Citations per year

Countries citing papers authored by Maria Li

Since Specialization
Citations

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

Fields of papers citing papers by Maria Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

15 of 15 papers shown
#Work
1 20171
2 201648
3 201636
4 2013171
5 201349
6 201328
7 201352
8 2013224
9 201280
10 20112
11 201022
12 200620
13 1996155
14 199610
15 19918

About Maria Li

Maria Li is a scholar working on Insect Science, Developmental Neuroscience, Ecology, Cellular and Molecular Neuroscience and Urban Studies, having authored 15 papers that have together received 906 indexed citations. Recurring topics across this work include Forest Insect Ecology and Management (8 papers), Insect and Pesticide Research (5 papers), Insect-Plant Interactions and Control (3 papers), Plant biochemistry and biosynthesis (3 papers), Entomopathogenic Microorganisms in Pest Control (2 papers), Cerebrospinal fluid and hydrocephalus (2 papers), Nerve injury and regeneration (2 papers) and Neurogenesis and neuroplasticity mechanisms (2 papers). The work is most often cited by research in Insect Science (449 citations), Developmental Neuroscience (96 citations), Cellular and Molecular Neuroscience (362 citations), Ecology (268 citations) and Genetics (191 citations). Maria Li has collaborated with scholars based in Canada, United States and Sweden. Frequent co-authors include Christopher I. Keeling, Macaire M. S. Yuen, Hannah Henderson, Samuel David, Steven J.M. Jones, Peter E. Braun, Roderick Docking, Chumei Li, Annemarie Shibata and Lisa McKerracher. Their work appears in journals such as Insect Biochemistry and Molecular Biology, BMC Genomics, Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques, Energy and Buildings and Neurosurgery.

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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