| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Chemistry | 753 | 16 | 27 | 9 |
Quantitative structure–activity relationship, Stereochemistry, Artificial intelligence, Computational biology and Biological system are among the topics commonly tackled in Sar and Qsar in Environmental Research. Sar and Qsar in Environmental Research features studies on Quantitative structure–activity relationship, including topics such as Molecular descriptor. Research on Stereochemistry presented in the journal focuses, in particular, on Docking (molecular), Pharmacophore and Steric effects.
The journal holds forums on Artificial intelligence that merges themes from other disciplines such as Machine learning and Pattern recognition. The studies in Computational biology featured incorporate elements of In silico and Bioinformatics. It focuses on Biological system as well as the interrelated topic of Linear regression.
The studies tackled, which mainly focus on Computational chemistry, apply to Molecule as well. The study on Data mining presented in it intersects with the topics under Applicability domain. The in-depth study on Environmental chemistry also explores topics in the intersecting field of Biochemical engineering.
The journal papers mainly tackle studies in Quantitative structure–activity relationship, Artificial intelligence, Molecular descriptor, Biological system and Data mining. The majority of Quantitative structure–activity relationship studies presented in the most cited papers zero in on Applicability domain. The published papers focus on Artificial intelligence but the discussions also offer insight into other areas such as Machine learning and Pattern recognition.
Sar and Qsar in Environmental Research mainly tackles studies in Quantitative structure–activity relationship, Computational biology, Biochemistry, Molecular dynamics and Molecular descriptor. The work on Quantitative structure–activity relationship tackled in Sar and Qsar in Environmental Research brings together disciplines like Biological activity, Computational chemistry, Biological system and Linear regression. Sar and Qsar in Environmental Research focuses on Computational biology but the discussions also offer insight into other areas such as Similarity (network science), In silico, Small molecule and 2019-20 coronavirus outbreak.
In addition to Molecular dynamics research, the journal aims to explore topics under Pharmacophore, Binding protein, Biophysics and Protease. In it, Tetrahymena pyriformis, Applicability domain, Least squares support vector machine and Test set are investigated in conjunction with one another to address concerns in Molecular descriptor research. The Test set research presented in the journal explores the relationship between Identification (information) and the closely related topic of Machine learning and Artificial intelligence.
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 Sar and Qsar in Environmental Research (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 Sar and Qsar in Environmental Research (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, 11.63% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 23.68% were posted by at least one author from the top 10 institutions publishing in the journal. Another 2.63% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 26.32% of all publications and 47.37% 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.
M Marzo;G J Lavado;F Como;A P Toropova
(2020)F. Lunghini;F. Lunghini;G. Marcou;P. Azam;M.H. Enrici
(2020)L F Wang;Y Wang;Z Y Yang;J Zhao
(2020)F. Lunghini;G. Marcou;P. Gantzer;P. Azam
(2020)A. Rakhimbekova;T.N. Akhmetshin;G.I. Minibaeva;R.I. Nugmanov
(2021)A.A. Toropov;A.P. Toropova;G. Selvestrel;D. Baderna
(2020)For students exploring Chemistry in the USA, numerous online degree options complement this field, offering flexibility and specialization. One popular path is pursuing healthcare-related programs like online medical assistant programs fafsa approved, which provide affordable education and financial support opportunities.
Many universities also offer universities with dual degree programs that blend chemistry knowledge with nursing or pharmacy. This can accelerate career growth by combining disciplines.
For those interested in specialized pharmaceutical careers, exploring an online pharmd can be an excellent choice. These programs cater to working professionals and provide in-depth expertise in drug development and patient care.
Additionally, registered nurses seeking advancement often consider rn to bsn online programs for a convenient way to obtain a bachelor's degree while continuing their careers. Overall, combining chemistry studies with healthcare disciplines via online programs opens diverse career pathways with flexible learning options.
