Andrew E. Blanchard

738 citations
21 papers · 502 · h-index 14

Impact in

    • Gene Regulatory Network Analysis
    • Microbial Metabolic Engineering and Bioproduction
    • CRISPR and Genetic Engineering
    • Evolution and Genetic Dynamics
    • Bacterial Genetics and Biotechnology

Papers in

Andrew E. Blanchard

20 papers receiving 495 citations

Peers

Andrew E. Blanchard
Comparison fields: 5 of 90
  • Molecular Biology 302
  • Genetics 120
  • Computational Theory and Mathematics 67
  • Health Informatics 5
  • Biophysics 16
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Citations per year

Countries citing papers authored by Andrew E. Blanchard

Since Specialization
Citations

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

Fields of papers citing papers by Andrew E. Blanchard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew E. Blanchard. 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 Andrew E. Blanchard. The network helps show where Andrew E. Blanchard may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201776
2 201566
3 202153
4 201640
5 201840
6 201432
7 201625
8 201323
9 202221
10 201420
11 202220
12 201416
13 201816
14 202213
15 202210
16 202310
17 20226
18 20225
19 20215
20 20225

About Andrew E. Blanchard

Andrew E. Blanchard is a scholar working on Molecular Biology, Computational Theory and Mathematics, Artificial Intelligence, Biomedical Engineering and Materials Chemistry, having authored 21 papers that have together received 502 indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (6 papers), Computational Drug Discovery Methods (5 papers), Machine Learning in Materials Science (3 papers), Single-cell and spatial transcriptomics (2 papers), Chemical Synthesis and Analysis (2 papers), Machine Learning in Bioinformatics (2 papers), Evolutionary Game Theory and Cooperation (2 papers) and Mathematical Biology Tumor Growth (1 paper). The work is most often cited by research in Molecular Biology (302 citations), Genetics (120 citations), Computational Theory and Mathematics (67 citations), Health Informatics (5 citations) and Biophysics (16 citations). Andrew E. Blanchard has collaborated with scholars based in United States, China and Türkiye. Frequent co-authors include Ting Lu, Chen Liao, Debsindhu Bhowmik, Christopher B. Stanley, Wentao Kong, Klaus Schulten, Emad Tajkhorshid, Mark J. Arcario, Feng Liu and Hao Qi. Their work appears in journals such as Journal of Cheminformatics, Biophysical Journal, BMC Systems Biology, Cellular and Molecular Bioengineering and ACS Synthetic Biology.

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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