Daniel N. Conrad

7 papers receiving 484 citations

Daniel N. Conrad's Hit Papers

MULTI-seq: sample multiplexing for single-cell RNA sequencing using lipid-tagged indices 2019 · 340 citations
3400+2+4Years since publication100200300

Peers

Daniel N. Conrad
Comparison fields: 5 of 78
  • Biophysics 42
  • Cancer Research 101
  • Molecular Biology 356
  • Immunology 78
  • Oncology 87
Replace Michael Thomaschewski with:
Michael Thomaschewski Germany
Despina Soteriou Germany
Carlos Luzzani Argentina
Tai‐I Hsu Taiwan
Nir Neumark United States
Aline Roch Switzerland
Ajit J. Nirmal United States
Mika Kaakinen Finland
Vignesh Shanmugam United States
Elena Denisenko Australia
Daniel N. Conrad relative to Michael Thomaschewski Germany Michael Thomaschewski's profile →
Citations per field
00.5×3.6×
Michael Thomaschewski · 1×
Citations per year

Countries citing papers authored by Daniel N. Conrad

Since Specialization
Citations

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

Fields of papers citing papers by Daniel N. Conrad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel N. Conrad. 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 Daniel N. Conrad. The network helps show where Daniel N. Conrad may publish in the future.

Co-authors

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

All Works

8 of 8 papers shown
#Work
1
MULTI-seq: sample multiplexing for single-cell RNA sequencing using lipid-tagged indices
Hit paper breakdown →
2019340
2 202173
3 202135
4 201031
5 20135
6 20245
7 20111
8 20250

About Daniel N. Conrad

Daniel N. Conrad is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Cancer Research, Infectious Diseases and Surgery, having authored 8 papers that have together received 490 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (3 papers), Advanced biosensing and bioanalysis techniques (2 papers), Cancer Genomics and Diagnostics (1 paper), Pancreatic function and diabetes (1 paper), Metabolism and Genetic Disorders (1 paper), MicroRNA in disease regulation (1 paper), Animal Virus Infections Studies (1 paper) and Robotics and Sensor-Based Localization (1 paper). The work is most often cited by research in Biophysics (42 citations), Cancer Research (101 citations), Molecular Biology (356 citations), Immunology (78 citations) and Oncology (87 citations). Daniel N. Conrad has collaborated with scholars based in United States, United Kingdom and Türkiye. Frequent co-authors include Zev J. Gartner, Christopher S. McGinnis, David M. Patterson, Juliane Winkler, Eric D. Chow, Jonathan S. Weissman, Marco Y. Hein, Vasudha Srivastava, Jennifer L. Hu and Zena Werb. Their work appears in journals such as Genome biology, Nature Methods, Cell stem cell, Nature Communications and Public Health.

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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