Luis R. Soenksen

2.6k citations
16 papers · 1.5k indexed · 2 hit papers · h-index 13
Topics
AI in cancer detection (3 papers)CRISPR and Genetic Engineering (3 papers)Cutaneous Melanoma Detection and Management (3 papers)
Partner nations
United StatesSpainMexico

In The Last Decade

Luis R. Soenksen

16 papers receiving 1.5k citations

Hit Papers

Wearable materials with embedded synthetic biology sensor...202120262022202420212021100200300

Peers

Luis R. Soenksen
Comparison fields: 5 of 147
  • Molecular Biology 760
  • Biomedical Engineering 620
  • Infectious Diseases 188
  • Artificial Intelligence 171
  • Oncology 112
Replace Peiwu Qin with:
Peiwu Qin China
Manoj Kumar Kanakasabapathy United States
Tony Hu United States
Liming Hu China
Hsin‐Yao Wang Taiwan
Waseem Asghar United States
Kyeonghye Guk South Korea
Zhiyi Chen China
Seung‐Woo Lee South Korea
Jin Yuan China
Luis R. Soenksen relative to Peiwu Qin China Peiwu Qin's profile →
Citations per field
00.5×4.9×
Peiwu Qin · 1×
Citations per year

Countries citing papers authored by Luis R. Soenksen

Since Specialization
Citations

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

Fields of papers citing papers by Luis R. Soenksen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Luis R. Soenksen. 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 Luis R. Soenksen. The network helps show where Luis R. Soenksen may publish in the future.

Co-authorship network of co-authors of Luis R. Soenksen

This figure shows the co-authorship network connecting the top 25 collaborators of Luis R. Soenksen. A scholar is included among the top collaborators of Luis R. Soenksen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Luis R. Soenksen. Luis R. Soenksen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
#WorkIndexed citations
1 48
2 19
3 145
4
Minimally instrumented SHERLOCK (miSHERLOCK) for CRISPR-based point-of-care diagnosis of SARS-CoV-2 and emerging variantsbreakdown →
236
5 89
6
Wearable materials with embedded synthetic biology sensors for biomolecule detectionbreakdown →
394
7 61
8 95
9 34
10 289
11 16
12 3
13 26
14 22
15 12
16 9

About Luis R. Soenksen

Luis R. Soenksen is a scholar working on Health Informatics, Health Information Management and Biophysics, having authored 16 papers that have together received 1.5k indexed citations. Recurring topics across this work include AI in cancer detection (3 papers), CRISPR and Genetic Engineering (3 papers) and Cutaneous Melanoma Detection and Management (3 papers). The work is most often cited by research in Health Informatics (64 citations), Biomedical Engineering (620 citations) and Molecular Biology (760 citations). Luis R. Soenksen has collaborated with scholars based in United States, Spain and Mexico. Frequent co-authors include James J. Collins, Nicolaas M. Angenent-Mari, Helena de Puig, Peter Q. Nguyen, Angelo S. Mao, Max A. English, Rose Lee, Nina M. Donghia, James B. Niemi and Hani Sallum. Their work appears in journals such as Science, Nature Medicine 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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