1347-1767
Published by: Society of Computer Chemistry, Japan
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Chemistry | 1123 | 13 | 27 | 1 |
Journal of Computer Chemistry, Japan primarily tackles Molecular dynamics, Chemical physics, Computational chemistry, Crystallography and Development (topology).
The most cited publications explore disciplines such as Combinatorial chemistry, Software, Combinatorics, Maple and GAMESS. The works on Combinatorial chemistry tackled in the journal articles bring together disciplines like Molecule, Interaction energy, Protein ligand, Molecular model and Structure space. The most cited publications explore topics in Software which can be helpful for research in disciplines like Chemical physics, Theoretical computer science and Group (mathematics).
Molecular physics, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), 2019-20 coronavirus outbreak, Engineering ethics and Classics are among the topics commonly tackled in Journal of Computer Chemistry, Japan. Molecular physics research presented in the journal encompasses a variety of subjects, including Nucleus, Ring (chemistry), Buffer (optical fiber) and Quantum chemical. The journal served as a forum through which researchers explored works on Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in conjunction with disciplines such as World Wide Web, Virology and Support vector machine.
Studies on Classics discussed in Journal of Computer Chemistry, Japan link to the field of Chemistry (relationship).
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Journal of Computer Chemistry, Japan (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Journal of Computer Chemistry, Japan (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 43.75% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 33.33% were posted by at least one author from the top 10 institutions publishing in the journal. Another 33.33% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 22.22% of all publications and 11.11% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Chinami Takashima;Junji Seino;Junji Seino;Junji Seino;Hiromi Nakai;Hiromi Nakai
(2020)Kazuki K. Takahashi;Yoshifumi Amamoto;Hiroteru Kikutake;Mariko I. Ito
(2021)Masato Kobayashi;Toshikazu Fujimori;Tetsuya Taketsugu
(2021)Momoji Kubo
(2020)M. Hiraishi;K. M. Kojima;H. Okabe;A. Koda
(2020)Hiromi Nakai
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