Daniel Osorio

1.4k citations
30 papers · 748 · h-index 13

Impact in

Papers in

    • Single-cell and spatial transcriptomics 12
    • Gene Regulatory Network Analysis 6
    • CRISPR and Genetic Engineering 2
    • RNA regulation and disease 2
    • Machine Learning in Bioinformatics 2
    • T-cell and B-cell Immunology 4
    • Atherosclerosis and Cardiovascular Diseases 2

Daniel Osorio

29 papers receiving 745 citations

Peers

Daniel Osorio
Comparison fields: 5 of 106
  • Microbiology 74
  • Sensory Systems 40
  • Molecular Biology 527
  • Immunology 112
  • Cancer Research 68
Replace John Klimek with:
John Klimek United States
Ronald W. Raab United States
Nissan Yissachar Israel
Victor Chi United States
Oishee Chakrabarti India
Neha Patel United States
Youtian Hu China
Gil Kanfer Switzerland
Xingwen Su China
Alberto Bresciani Italy
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Citations per field
00.5×5.3×
John Klimek · 1×
Citations per year

Countries citing papers authored by Daniel Osorio

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Osorio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015272
2 2020113
3 202237
4 201637
5 202333
6 201931
7 202226
8 202025
9 201921
10 202021
11 202020
12 202015
13 202213
14 202112
15 202311
16 202010
17 20219
18 20227
19 20227
20 20227

About Daniel Osorio

Daniel Osorio is a scholar working on Molecular Biology, Immunology, Cancer Research, Genetics and Oncology, having authored 30 papers that have together received 748 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (12 papers), Gene Regulatory Network Analysis (6 papers), T-cell and B-cell Immunology (4 papers), CRISPR and Genetic Engineering (2 papers), RNA regulation and disease (2 papers), Atherosclerosis and Cardiovascular Diseases (2 papers), Cancer Genomics and Diagnostics (2 papers) and Machine Learning in Bioinformatics (2 papers). The work is most often cited by research in Microbiology (74 citations), Sensory Systems (40 citations), Molecular Biology (527 citations), Immunology (112 citations) and Cancer Research (68 citations). Daniel Osorio has collaborated with scholars based in United States, China and Netherlands. Frequent co-authors include Paola Rondón-Villarreal, Rodrigo Torres, James J. Cai, Yan Zhong, Janneth González, Erchin Serpedin, George E. Barreto, Xue Yu, Jianhua Z. Huang and Yanan Tian. Their work appears in journals such as The R Journal, Bioinformatics, Nature Computational Science, Patterns and Development.

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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