Dan DeBlasio

586 citations
25 papers · 283 · h-index 8

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
    • Genomics and Phylogenetic Studies
    • Circular RNAs in diseases
    • Epigenetics and DNA Methylation
    • RNA modifications and cancer
    • Machine Learning in Bioinformatics

Papers in

    • Genomics and Phylogenetic Studies 13
    • Genetics, Bioinformatics, and Biomedical Research 4
    • RNA and protein synthesis mechanisms 4
    • Machine Learning in Bioinformatics 3
    • Genomics and Chromatin Dynamics 3
    • Gene expression and cancer classification 2
    • Algorithms and Data Compression 8
    • Machine Learning and Algorithms 2

Dan DeBlasio

22 papers receiving 281 citations

Peers

Dan DeBlasio
Comparison fields: 5 of 54
  • Cancer Research 85
  • Molecular Biology 200
  • Artificial Intelligence 45
  • Information Systems and Management 5
  • Virology 3
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Markus Hsi-Yang Fritz Germany
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Mikaël Salson France
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Zhihan Zhou China
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Citations per field
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Citations per year

Countries citing papers authored by Dan DeBlasio

Since Specialization
Citations

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

Fields of papers citing papers by Dan DeBlasio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201171
2 201157
3 201940
4 201835
5 201315
6 201910
7 20159
8 20178
9 20155
10 20155
11 20184
12 20143
13 20203
14 20163
15 20153
16 20173
17 20242
18 20242
19 20112
20 20241

About Dan DeBlasio

Dan DeBlasio is a scholar working on Molecular Biology, Artificial Intelligence, Information Systems and Management, Aerospace Engineering and Cancer Research, having authored 25 papers that have together received 283 indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (13 papers), Algorithms and Data Compression (8 papers), Genetics, Bioinformatics, and Biomedical Research (4 papers), RNA and protein synthesis mechanisms (4 papers), Machine Learning in Bioinformatics (3 papers), Genomics and Chromatin Dynamics (3 papers), Gene expression and cancer classification (2 papers) and Machine Learning and Algorithms (2 papers). The work is most often cited by research in Cancer Research (85 citations), Molecular Biology (200 citations), Artificial Intelligence (45 citations), Information Systems and Management (5 citations) and Virology (3 citations). Dan DeBlasio has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Carl Kingsford, Guillaume Marçais, Joseph Mazar, Subramaniam S. Govindarajan, Ranjan J. Perera, Shaojie Zhang, John Kececioglu, Prashant Pandey, Divya Khaitan and Animesh Ray. Their work appears in journals such as Journal of Computational Biology, Bioinformatics, BMC Bioinformatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics and Journal of the ACM.

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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