Computational Biology and Chemistry

36.6k citations
2.7k papers · · active since 2016

Impact in

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

Papers in

    • Computational Drug Discovery Methods 476
    • Machine Learning in Bioinformatics 303
    • Protein Structure and Dynamics 301
    • RNA and protein synthesis mechanisms 289
    • Bioinformatics and Genomic Networks 231
    • Genomics and Phylogenetic Studies 213
    • Gene expression and cancer classification 162

Computational Biology and Chemistry

2.3k papers receiving 35.2k citations

Peers

Computational Biology and Chemistry
Comparison fields: 5 of 219
  • Computational Theory and Mathematics 5.3k
  • Molecular Biology 18.7k
  • Organic Chemistry 3.8k
  • Cancer Research 1.8k
  • Toxicology 344
Replace Computational and Structural Biotechnology Journal with:
Computational and Structural Biotechnology Journal China
Combinatorial Chemistry & High Throughput Screening China
SpringerPlus China
Journal of Chemometrics United States
SLAS DISCOVERY United States
Chemometrics and Intelligent Laboratory Systems China
ACS Central Science United States
Journal of Advanced Research China
Molecular BioSystems United States
Protein and Peptide Letters China
Computational Biology and Chemistry relative to Computational and Structural Biotechnology Journal China Computational and Structural Biotechnology Journal's profile →
Citations per field
00.5×1.5×2×2.5×
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 2.7k papers published in Computational Biology and Chemistry in the last decades have received a total of 36.6k indexed citations . Papers published in Computational Biology and Chemistry usually cover Computational Theory and Mathematics (479 papers), Molecular Biology (1.8k papers), Cancer Research (154 papers), Toxicology (30 papers) and Organic Chemistry (242 papers) specifically the topics of Computational Drug Discovery Methods (476 papers), Machine Learning in Bioinformatics (303 papers), Protein Structure and Dynamics (301 papers), RNA and protein synthesis mechanisms (289 papers), Bioinformatics and Genomic Networks (231 papers), Genomics and Phylogenetic Studies (213 papers), Gene expression and cancer classification (162 papers) and Synthesis and biological activity (134 papers). The most active scholars publishing in Computational Biology and Chemistry are Robert E. Ulanowicz, Jan Gorodkin, Michael James Cardwell Crabbe, Hervé Seligmann, William Ramsay Taylor, Christian Jean Michel, Zengyou He, Weichuan Yu, Cheng‐Hong Yang and Li‐Yeh Chuang.

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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