TRAVIS - A Free Analyzer and Visualizer for Monte Carlo and Molecular Dynamics Trajectories

1.1k indexed citations
published 2011

Countries where authors are citing TRAVIS - A Free Analyzer and Visualizer for Monte Carlo and Molecular Dynamics Trajectories

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Citations

This map shows the geographic impact of TRAVIS - A Free Analyzer and Visualizer for Monte Carlo and Molecular Dynamics Trajectories. 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 TRAVIS - A Free Analyzer and Visualizer for Monte Carlo and Molecular Dynamics Trajectories with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites TRAVIS - A Free Analyzer and Visualizer for Monte Carlo and Molecular Dynamics Trajectories more than expected).

Fields of papers citing TRAVIS - A Free Analyzer and Visualizer for Monte Carlo and Molecular Dynamics Trajectories

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of TRAVIS - A Free Analyzer and Visualizer for Monte Carlo and Molecular Dynamics Trajectories. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the TRAVIS - A Free Analyzer and Visualizer for Monte Carlo and Molecular Dynamics Trajectories.

About TRAVIS - A Free Analyzer and Visualizer for Monte Carlo and Molecular Dynamics Trajectories

This paper, published in 2011, received 1.1k indexed citations . Written by Martin Brehm and Barbara Kirchner covering the research area of Atomic and Molecular Physics, and Optics and Spectroscopy. It is primarily cited by scholars working on Catalysis (543 citations), Materials Chemistry (286 citations), Atomic and Molecular Physics, and Optics (236 citations), Biomedical Engineering (210 citations) and Spectroscopy (168 citations). Published in Journal of Chemical Information and Modeling.

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.

This paper is also available at doi.org/10.1021/ci200217w.

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