| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 546 | 13 | 41 | 11 |
The main points discussed in Journal of Integrative Bioinformatics deals with Computational biology, Data mining, Artificial intelligence, Software and Genetics. While work presented in the journal provided substantial information on Computational biology, it also covered topics in Genome, Gene, Bioinformatics and Gene regulatory network. In particular, the Gene works presented emphasize discussions on Gene expression.
It explores themes in Data mining like Data integration and links them with other fields of study like Context (language use). Artificial intelligence research presented in Journal of Integrative Bioinformatics encompasses a variety of subjects, including Natural language processing, Machine learning and Pattern recognition. Topics in Software explored in Journal of Integrative Bioinformatics were investigated in conjunction with research in Visualization, Theoretical computer science, SBML and Data science.
The study on Programming language presented in Journal of Integrative Bioinformatics intersects with the topics under Markup language.
The most cited publications facilitate discussions on Data mining, Artificial intelligence, SBML, Theoretical computer science and Software. The most cited publications focus on Data mining but the discussions also offer insight into other areas such as Database and Systems biology. The journal articles explore issues in Artificial intelligence which can be linked to other research areas like Machine learning and Natural language processing.
The primary areas of discussion in Journal of Integrative Bioinformatics are Computational biology, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), 2019-20 coronavirus outbreak, Artificial intelligence and Markup language. Genome browser, Annotation, Biological database, Genome and Protein sequencing are some topics wherein Computational biology research discussed in Journal of Integrative Bioinformatics have an impact. The concepts on Artificial intelligence presented in it can also apply to other research fields, including Machine learning and Sequence.
Markup language research in it involves the investigation of Integrative bioinformatics studies, all of which are linked to disciplines such as Metadata and Synthetic biology. While Metadata is the key highlight in the journal, it also covered some subjects on Software and Set (abstract data type). The studies in Programming language featured incorporate elements of Visualization, Structure (mathematical logic) and Natural language processing.
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 Integrative Bioinformatics (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 Integrative Bioinformatics (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, 13.64% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 31.58% were posted by at least one author from the top 10 institutions publishing in the journal. Another 5.26% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 5.26% of all publications and 57.89% 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.
The Journal of Integrative Bioinformatics is indeed a valuable resource for anyone interested in the fields of Computational biology, Data mining, Artificial intelligence, and Genetics. However, its utilization is not solely confined to those in research and academia. Practical applications of the knowledge and insights presented within these studies could also be indispensable for educators in fields related to computational sciences. It's fundamentally important for those engaged in education to be cognizant and well-experienced in the use of innovative technologies within their teaching methodology. Especially for subjects like math and science where the integration of computational techniques can significantly enhance learning outcomes. Teachers who stay updated with current research in Computational Biology, for example, are in a better position to create engaging, relevant curriculum and effectively impart it to their students. For aspiring teachers in computational or mathematical sciences, it becomes especially critical to acquaint themselves with latest research and applications. A basic understanding of computational biology could be a valuable asset for those considering careers in education. For instance, a comprehensive guide on how to become a middle school math teacher in Arkansas emphasizes the importance of being equipped with the latest educational and technological tools pertaining to computational sciences. In conclusion, having access to cutting-edge research such as the kind presented in the Journal of Integrative Bioinformatics is of paramount importance. It equips educators with the knowledge needed to prepare the future generation of scientists and teachers who will go on to make transformative contributions to fields like Computational Biology, Artificial Intelligence and more.
Robert Sidney Cox;Curtis Madsen;James Alastair McLaughlin;Tramy Nguyen
(2021)Hasan Baig;Pedro Fontanarrosa;Vishwesh Kulkarni;James Alastair McLaughlin
(2020)Dagmar Waltemath;Martin Golebiewski;Michael L. Blinov;Padraig Gleeson
(2020)Falk Schreiber;Falk Schreiber;Björn Sommer;Tobias Czauderna;Martin Golebiewski
(2020)Lucian P. Smith;Frank T. Bergmann;Alan Garny;Tomás Helikar
(2021)Fengkai Zhang;Lucian P. Smith;Michael L. Blinov;James R. Faeder
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