Computational Biology and Chemistry

33.8k citations
2.6k papers · · active since 1950

Impact in

    • Computational Drug Discovery Methods
    • Machine Learning in Bioinformatics
    • RNA and protein synthesis mechanisms
    • Protein Structure and Dynamics
    • Bioinformatics and Genomic Networks
    • Genomics and Phylogenetic Studies
    • Gene expression and cancer classification

Papers in

    • Computational Drug Discovery Methods 469
    • Protein Structure and Dynamics 299
    • Machine Learning in Bioinformatics 293
    • RNA and protein synthesis mechanisms 286
    • Bioinformatics and Genomic Networks 224
    • Genomics and Phylogenetic Studies 203
    • Gene expression and cancer classification 157

Computational Biology and Chemistry

2.3k papers receiving 32.7k citations

Peers

Computational Biology and Chemistry
Comparison fields: 5 of 221
  • Computational Theory and Mathematics 5.0k
  • Molecular Biology 17.5k
  • Organic Chemistry 3.7k
  • Cancer Research 1.7k
  • Toxicology 326
Replace Computational and Structural Biotechnology Journal with:
Computational and Structural Biotechnology Journal China
SpringerPlus China
Combinatorial Chemistry & High Throughput Screening China
SLAS DISCOVERY United States
Chemometrics and Intelligent Laboratory Systems China
Journal of Advanced Research China
Journal of Chemometrics United States
SoftwareX United States
Expert Opinion on Drug Discovery United States
Frontiers in Molecular Biosciences China
Computational Biology and Chemistry relative to Computational and Structural Biotechnology Journal China Computational and Structural Biotechnology Journal's profile →
Citations per field
00.5×2.5×
Computational and Structural Biotechnology Journal · 1×
Citations per year

Countries where authors publish in Computational Biology and Chemistry

Since Specialization
Citations

This map shows the geographic impact of research published in Computational Biology and Chemistry. 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 papers published in Computational Biology and Chemistry with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Computational Biology and Chemistry more than expected).

Fields of papers published in Computational Biology and Chemistry

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Computational Biology and Chemistry. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Computational Biology and Chemistry.

About Computational Biology and Chemistry

The 2.6k papers published in Computational Biology and Chemistry in the last decades have received a total of 33.8k indexed citations . Papers published in Computational Biology and Chemistry usually cover Computational Theory and Mathematics (472 papers), Molecular Biology (1.7k papers), Cancer Research (147 papers), Toxicology (30 papers) and Organic Chemistry (241 papers) specifically the topics of Computational Drug Discovery Methods (469 papers), Protein Structure and Dynamics (299 papers), Machine Learning in Bioinformatics (293 papers), RNA and protein synthesis mechanisms (286 papers), Bioinformatics and Genomic Networks (224 papers), Genomics and Phylogenetic Studies (203 papers), Gene expression and cancer classification (157 papers) and Synthesis and biological activity (134 papers). The most active scholars publishing in Computational Biology and Chemistry are Robert E. Ulanowicz, Jan Gorodkin, M. James C. Crabbe, Hervé Seligmann, William R. Taylor, Christian Michel, Li‐Yeh Chuang, Cheng‐Hong Yang, Hsueh‐Wei Chang and Zengyou He.

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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