Tyler Reddy

15.9k citations
25 papers · 1.7k indexed · 1 hit paper · h-index 14

Impact in

Papers in

Tyler Reddy

25 papers receiving 1.7k citations

Hit Papers

MDAnalysis: A Python Package for the Rapid Analysis of Molecular Dynamics Simulations 2016 · 1.1k citations
1.1k20162026201920222505007501000

Peers

Tyler Reddy
Comparison fields: 5 of 136
  • Molecular Biology 1.1k
  • Cellular and Molecular Neuroscience 144
  • Virology 37
  • Cell Biology 123
  • Spectroscopy 104
Replace Jan Domański with:
Jan Domański United States
Jonathan Barnoud Netherlands
N. Krawetz United States
Naveen Michaud‐Agrawal United States
Tod D. Romo United States
Joseph B. Lim United States
Sébastien Buchoux France
Carlos X. Hernández United States
David Dotson United States
Michał J. Gajda Germany
Tyler Reddy relative to Jan Domański United States Jan Domański's profile →
Citations per field
00.5×1.5×2.1×
Jan Domański · 1×
Citations per year

Countries citing papers authored by Tyler Reddy

Since Specialization
Citations

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

Fields of papers citing papers by Tyler Reddy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20235
2 20231
3 20234
4 202232
5 202212
6 20208
7 20191
8 201844
9 201763
10
MDAnalysis: A Python Package for the Rapid Analysis of Molecular Dynamics Simulations
Hit paper breakdown →
20161133
11 201641
12 201673
13 201578
14 20142
15 201419
16 201334
17 20111
18 201011
19 200910
20 200834

About Tyler Reddy

Tyler Reddy is a scholar working on Information Systems and Management, Virology, Hardware and Architecture, Molecular Biology and Modeling and Simulation, having authored 25 papers that have together received 1.7k indexed citations. Recurring topics across this work include Lipid Membrane Structure and Behavior (7 papers), Protein Structure and Dynamics (6 papers), Scientific Computing and Data Management (4 papers), RNA Interference and Gene Delivery (3 papers), RNA and protein synthesis mechanisms (3 papers), Bacteriophages and microbial interactions (2 papers), Fibroblast Growth Factor Research (2 papers) and Machine Learning in Materials Science (2 papers). The work is most often cited by research in Molecular Biology (1.1k citations), Cellular and Molecular Neuroscience (144 citations), Virology (37 citations), Cell Biology (123 citations) and Spectroscopy (104 citations). Tyler Reddy has collaborated with scholars based in United Kingdom, United States and France. Frequent co-authors include Jonathan Barnoud, Richard Gowers, Oliver Beckstein, Manuel N. Melo, Sébastien Buchoux, David Dotson, Ian M. Kenney, Max Linke, Sean L. Seyler and Jan Domański. Their work appears in journals such as Biophysical Journal, The Journal of Physical Chemistry B, Biochimica et Biophysica Acta (BBA) - Biomembranes, Structure and Scientific Reports.

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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