Daniel K. Putnam

608 citations
11 papers · 325 · h-index 8

Impact in

Papers in

    • Protein Structure and Dynamics 2
    • Retinal Development and Disorders 2
    • Machine Learning in Bioinformatics 1
    • Cancer Genomics and Diagnostics 3

Daniel K. Putnam

11 papers receiving 319 citations

Peers

Daniel K. Putnam
Comparison fields: 5 of 73
  • Biomaterials 61
  • Cancer Research 54
  • Molecular Biology 205
  • Plant Science 82
  • Biophysics 10
Replace Maximilian Hörner with:
Maximilian Hörner Germany
Xingqiao Xie China
А. В. Ромащенко Russia
Sibyll Pollok Germany
Elise Delage France
Jakob Regberg Sweden
Takahiro Otabe Japan
Mackenzie T. Walls United States
Avi Jacob Israel
Amit Thakar United States
Daniel K. Putnam relative to Maximilian Hörner Germany Maximilian Hörner's profile →
Citations per field
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Maximilian Hörner · 1×
Citations per year

Countries citing papers authored by Daniel K. Putnam

Since Specialization
Citations

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

Fields of papers citing papers by Daniel K. Putnam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

11 of 11 papers shown
#Work
1 201588
2 202187
3 201962
4 201331
5
Exploring schizophrenia drug-gene interactions through molecular network and pathway modeling.
201116
6 201611
7 201511
8 20217
9 20155
10 20254
11 20193

About Daniel K. Putnam

Daniel K. Putnam is a scholar working on Molecular Biology, Cancer Research, Materials Chemistry, Spectroscopy and Genetics, having authored 11 papers that have together received 325 indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (3 papers), Enzyme Structure and Function (3 papers), Protein Structure and Dynamics (2 papers), Retinal Development and Disorders (2 papers), Neuroblastoma Research and Treatments (1 paper), Machine Learning in Bioinformatics (1 paper), Crystallography and Radiation Phenomena (1 paper) and Neuroinflammation and Neurodegeneration Mechanisms (1 paper). The work is most often cited by research in Biomaterials (61 citations), Cancer Research (54 citations), Molecular Biology (205 citations), Plant Science (82 citations) and Biophysics (10 citations). Daniel K. Putnam has collaborated with scholars based in United States, Poland and Germany. Frequent co-authors include Jens Meiler, Edward W. Lowe, Xiang Chen, John Easton, Udaya C. Kalluri, Loukas Petridis, B. Tracy Nixon, Venu Gopal Vandavasi, Qiu Zhang and Leighton Coates. Their work appears in journals such as Proteins Structure Function and Bioinformatics, Scientific Reports, PLANT PHYSIOLOGY, Computational and Structural Biotechnology Journal and Developmental Cell.

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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