Nathan LaPierre

1.1k citations
17 papers · 241 · h-index 8

Impact in

    • Gut microbiota and health
    • Genomics and Phylogenetic Studies
    • Bioinformatics and Genomic Networks
    • Metabolomics and Mass Spectrometry Studies
    • Machine Learning in Bioinformatics
    • Gene expression and cancer classification
    • Genetic Associations and Epidemiology

Papers in

    • Genomics and Phylogenetic Studies 7
    • Machine Learning in Bioinformatics 3
    • Bioinformatics and Genomic Networks 3
    • Gene expression and cancer classification 3
    • Genetic Mapping and Diversity in Plants and Animals 5
    • Genetic Associations and Epidemiology 4
    • Genetic and phenotypic traits in livestock 3

Nathan LaPierre

16 papers receiving 241 citations

Peers

Nathan LaPierre
Comparison fields: 5 of 77
  • Molecular Biology 140
  • Genetics 49
  • Ophthalmology 15
  • Health Information Management 5
  • Neurology 16
Replace Qiaoxing Liang with:
Qiaoxing Liang China
Sameer Paithankar United States
Matthew Greenberg Canada
Carlos Loucera Spain
Karin Schwarzbauer Austria
Bo Lei China
Pascal Notin United Kingdom
Erola Pairo‐Castineira United Kingdom
Robert Binna Austria
Dimitri Guala Sweden
Nathan LaPierre relative to Qiaoxing Liang China Qiaoxing Liang's profile →
Citations per field
00.5×4.1×
Qiaoxing Liang · 1×
Citations per year

Countries citing papers authored by Nathan LaPierre

Since Specialization
Citations

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

Fields of papers citing papers by Nathan LaPierre

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 201964
2 202137
3 202035
4 202225
5 201925
6 202219
7 201910
8 20247
9 20235
10 20174
11 20173
12 20232
13 20242
14 20161
15 20201
16 20151
17 20240

About Nathan LaPierre

Nathan LaPierre is a scholar working on Molecular Biology, Genetics, Ecology, Pathology and Forensic Medicine and Cellular and Molecular Neuroscience, having authored 17 papers that have together received 241 indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (7 papers), Genetic Mapping and Diversity in Plants and Animals (5 papers), Genetic Associations and Epidemiology (4 papers), Machine Learning in Bioinformatics (3 papers), Genetic and phenotypic traits in livestock (3 papers), Bioinformatics and Genomic Networks (3 papers), Gene expression and cancer classification (3 papers) and Microbial Community Ecology and Physiology (2 papers). The work is most often cited by research in Molecular Biology (140 citations), Genetics (49 citations), Ophthalmology (15 citations), Health Information Management (5 citations) and Neurology (16 citations). Nathan LaPierre has collaborated with scholars based in United States, Switzerland and Saudi Arabia. Frequent co-authors include Eleazar Eskin, Wei Wang, Guangyu Zhou, Chelsea J.‐T. Ju, Serghei Mangul, Mohammed Alser, David Koslicki, Farhad Hormozdiari, Helen J. Huang and Brian L. Hill. Their work appears in journals such as Cell Genomics, PLoS Genetics, BMC Bioinformatics, Cell Reports and Nature Communications.

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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