| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Chemistry | 500 | 41 | 62 | 16 |
| Computer Science | 695 | 11 | 17 | 8 |
The journal tackles a plethora of topics, such as Stereochemistry, Docking (molecular), Computational chemistry, Quantitative structure–activity relationship and Molecule. The research on Stereochemistry featured in the journal combines topics in other fields like Protein structure, Hydrogen bond, Binding site and Active site. The work on Binding site tackled in the journal brings together disciplines like Plasma protein binding and Ligand.
Research in Computational biology and the interrelating topic of Drug discovery were among the subjects of interest in the Docking (molecular) studies discussed in the journal. The presented Computational chemistry research focuses mostly on Solvation and, on occasion, topics in Thermodynamics. Topics in Quantitative structure–activity relationship were tackled in line with various other fields like Biological system and Artificial intelligence.
While Journal of Computer-aided Molecular Design focused on Artificial intelligence, it was also able to explore topics like Data mining and Pattern recognition. It dives deep in exploring the relationship between the study of Molecule and Crystallography. The Virtual screening study tackled is a key component of adjacent topics in the area of Combinatorial chemistry.
The most cited papers primarily focus on research topics in Docking (molecular), Computational chemistry, Virtual screening, Stereochemistry and Molecule. Issues in Docking (molecular) were discussed in the most cited papers, taking into consideration concepts from other disciplines like Protein structure, Computational biology and Ligand (biochemistry). Binding site and Active site are some topics wherein Stereochemistry research discussed in the most cited publications has an impact.
The concepts of Molecular dynamics, Artificial intelligence, Molecule, Small molecule and Virtual screening are tackled in the journal. Some problems in Artificial intelligence that were presented in Journal of Computer-aided Molecular Design overlapped with concepts under Machine learning, Pattern recognition and Identification (information). Topics in Molecule explored in Journal of Computer-aided Molecular Design were investigated in conjunction with research in Chemical physics, Molecular physics, Quantum and Tautomer.
Biological system, In silico, Computational biology and Ligand (biochemistry) are some topics wherein Small molecule research discussed in the journal have an impact. Journal of Computer-aided Molecular Design explores research in Computational biology alongside concepts in Protein structure and other areas of study in Drug discovery. It tackled Virtual screening research as part of investigation of Biochemistry and Docking (molecular).
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-aided Molecular Design (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-aided Molecular Design (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, 7.69% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 19.44% were posted by at least one author from the top 10 institutions publishing in the journal. Another 2.78% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 13.89% of all publications and 63.89% 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.
Andrea Rizzi;Travis Jensen;David R. Slochower;Matteo Aldeghi
(2020)Conor D. Parks;Zied Gaieb;Michael Chiu;Huanwang Yang;Huanwang Yang
(2020)Phasit Charoenkwan;Chanin Nantasenamat;Md. Mehedi Hasan;Watshara Shoombuatong
(2020)Muhammad Arif;Saeed Ahmad;Farman Ali;Ge Fang
(2020)Teresa Danielle Bergazin;Nicolas Tielker;Yingying Zhang;Junjun Mao
(2021)Mehtap Işık;Teresa Danielle Bergazin;Thomas Fox;Andrea Rizzi
(2020)Mehtap Işık;Dorothy Levorse;David L. Mobley;Timothy Rhodes
(2020)José L. Medina-Franco;Norberto Sánchez-Cruz;Edgar López-López;Edgar López-López;Bárbara I. Díaz-Eufracio
(2021)Darren V. S. Green;Stephen D. Pickett;Christopher N. Luscombe;Stefan Senger
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