Laura Day

628 citations
6 papers · 317 · h-index 6

Impact in

    • Genetic Mapping and Diversity in Plants and Animals
    • Evolution and Genetic Dynamics
    • Genetic Associations and Epidemiology

Papers in

    • Fungal and yeast genetics research 3
    • CRISPR and Genetic Engineering 3
    • Genomics and Chromatin Dynamics 2
    • Genomics and Phylogenetic Studies 2
    • Microbial Metabolic Engineering and Bioproduction 1
    • Genetic Mapping and Diversity in Plants and Animals 3
    • Genetic Associations and Epidemiology 1

Laura Day

6 papers receiving 315 citations

Peers

Laura Day
Comparison fields: 5 of 45
  • Aging 15
  • Genetics 139
  • Molecular Biology 235
  • Business and International Management 4
  • Plant Science 62
Replace Likun Long with:
Likun Long China
Alexander E. Ferrazzoli United States
Peter Kalds China
Christelle Chanez Switzerland
Yangyun Zou China
Mark Spensley Canada
Guanghai Xiang China
Michelle Déquard-Chablat France
Zoltán Bódi Hungary
Amal Zine El Aabidine France
Laura Day relative to Likun Long China Likun Long's profile →
Citations per field
00.5×
Likun Long · 1×
Citations per year

Countries citing papers authored by Laura Day

Since Specialization
Citations

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

Fields of papers citing papers by Laura Day

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Laura Day, 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 Laura Day Line = papers co-authored together Laura Day links everyone, so they are left out of the graph.

All Works

About Laura Day

Laura Day is a scholar working on Molecular Biology, Genetics, Insect Science, Infectious Diseases and Organic Chemistry, having authored 6 papers that have together received 317 indexed citations. Recurring topics across this work include Genetic Mapping and Diversity in Plants and Animals (3 papers), Fungal and yeast genetics research (3 papers), CRISPR and Genetic Engineering (3 papers), Genomics and Chromatin Dynamics (2 papers), Genomics and Phylogenetic Studies (2 papers), Insect symbiosis and bacterial influences (1 paper), Microbial Metabolic Engineering and Bioproduction (1 paper) and Genetic Associations and Epidemiology (1 paper). The work is most often cited by research in Aging (15 citations), Genetics (139 citations), Molecular Biology (235 citations), Business and International Management (4 citations) and Plant Science (62 citations). Laura Day has collaborated with scholars based in United States. Frequent co-authors include Leonid Kruglyak, Joshua S. Bloom, Meru J. Sadhu, Jake J. Siegel, Frank W. Albert, Sriram Kosuri, James Boocock, Sebastian Treusch, Rockie Chong and Helen Barnes. Their work appears in journals such as eLife, Science, Nature Genetics and PLoS ONE.

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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