Kevin T. Love

5.8k citations
17 papers · 3.5k indexed · 2 hit papers · h-index 17

Kevin T. Love

17 papers receiving 3.5k citations

Hit Papers

Molecularly self-assembled nucleic acid nanoparticles for...1.0k20102026201520202505007501000

Peers

Kevin T. Love
Comparison fields: 5 of 109
  • Molecular Biology 3.0k
  • Biomaterials 527
  • Cancer Research 399
  • Biomedical Engineering 636
  • Immunology 305
Replace William Querbes with:
William Querbes United States
Ahmed A. Eltoukhy United States
Mattias Hällbrink Sweden
Klaus Charissé United States
Rosemary Kanasty United States
Satoshi Uchida Japan
Ismail M. Hafez Canada
Shaohui Cui China
Ikramy A. Khalil Japan
Anders Wittrup Sweden
Kevin T. Love relative to William Querbes United States William Querbes's profile →
Citations per field
00.5×1.5×
William Querbes · 1×
Citations per year

Countries citing papers authored by Kevin T. Love

Since Specialization
Citations

This map shows the geographic impact of Kevin T. Love'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 Kevin T. Love with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin T. Love more than expected).

Fields of papers citing papers by Kevin T. Love

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kevin T. Love. 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 Kevin T. Love. The network helps show where Kevin T. Love may publish in the future.

Co-authorship network

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

All Works

17 of 17 papers shown
#Work
1 2016138
2 201422
3 201324
4 2013148
5 2013169
6 2013186
7
YY1 regulates melanocyte development and function by cooperating with MITF
201237
8
Molecularly self-assembled nucleic acid nanoparticles for targeted in vivo siRNA deliverybreakdown →
20121005
9 201283
10 2012333
11 201256
12 201154
13 201146
14
Lipid-like materials for low-dose, in vivo gene silencingbreakdown →
2010792
15 201064
16 2009243
17 2009111

About Kevin T. Love

Kevin T. Love is a scholar working on Cell Biology, Molecular Biology and Cancer Research, having authored 17 papers that have together received 3.5k indexed citations. Recurring topics across this work include RNA Interference and Gene Delivery (14 papers), Advanced biosensing and bioanalysis techniques (11 papers), Nanopore and Nanochannel Transport Studies (4 papers), Virus-based gene therapy research (3 papers), CRISPR and Genetic Engineering (2 papers), MicroRNA in disease regulation (2 papers), Barrier Structure and Function Studies (1 paper) and Nanoparticle-Based Drug Delivery (1 paper). The work is most often cited by research in Molecular Biology (3.0k citations), Biomaterials (527 citations) and Cancer Research (399 citations). Kevin T. Love has collaborated with scholars based in United States, Japan and Switzerland. Frequent co-authors include Daniel G. Anderson, Róbert Langer, William Querbes, Yi Chen, Kathryn A. Whitehead, Ahmed A. Eltoukhy, Gaurav Sahay, Christopher Zurenko, Emmanouil D. Karagiannis and Chang G. Peng. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Nano Letters.

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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