| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Biology and Biochemistry | 52 | 224 | 411 | 56 |
| Engineering and Technology | 358 | 32 | 65 | 22 |
Briefings in Bioinformatics primarily focuses on research topics in Computational biology, Artificial intelligence, Data science, Genome and Machine learning. While work presented in the journal provided substantial information on Computational biology, it also covered topics in Genetics, In silico, Gene, DNA sequencing and Genomics. Gene research presented is mostly focused on the subject of Gene expression.
Briefings in Bioinformatics explores topics in Artificial intelligence which can be helpful for research in disciplines like Identification (information) and Pattern recognition.
The main points discussed in the published papers deal with Computational biology, Data science, Data mining, Genetics and Bioinformatics. The published articles facilitate discussions on Computational biology that incorporate concepts from other fields like Annotation, Genomics and microRNA, Gene, Sequence analysis. The most cited papers explore research in Data science alongside concepts in Systems biology and other areas of study in Artificial intelligence.
Briefings in Bioinformatics primarily tackles Computational biology, Artificial intelligence, Machine learning, Deep learning and Gene. The research on Computational biology tackled can also make contributions to studies in the areas of Transcriptome, Genome, microRNA, Disease and In silico. Identification (information) and Pattern recognition are some topics wherein Artificial intelligence research discussed in it have an impact.
The journal holds forums on Machine learning that merges themes from other disciplines such as Graph (abstract data type), Field (computer science), Representation (mathematics), Benchmark (computing) and Drug discovery. Specifically, studies on Gene expression are prevalent in the Gene works discussed.
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 Briefings in 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 Briefings in 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, 10.64% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 24.69% were posted by at least one author from the top 10 institutions publishing in the journal. Another 7.39% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 21.18% of all publications and 46.74% 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.
With such an expansive field and promising research topics, there are numerous career opportunities for those interested in bioinformatics. One such career, that combines knowledge of healthcare and computer science, is medical coding. Medical coding is necessary for the categorization and billing of medical procedures and diagnoses. This is an in-demand role especially in the field of bioinformatics where data from genomic sequencing needs careful interpretation.
If you are living in the South Dakota and consider pursuing this career, make sure to check our guide on how to be a medical coder in South Dakota. Through coding the outputs of bioinformatics studies, clinicians can better understand and provide appropriate therapeutic options for patients. The guide provides comprehensive information on how to start your career in medical coding in South Dakota including the skillsets required, the certification process and potential job prospects.
The medical coder role is only one of the many career paths related to bioinformatics. With the constant advancement in this field, a multitude of other emphases like computational biology, machine learning, and genomics can pave the way for numerous career opportunities including research scientists, data scientist, bioinformatics engineer, and many more.
John J. Dziak;Donna L. Coffman;Stephanie T. Lanza;Runze Li
(2020)Xing Chen;Di Xie;Qi Zhao;Zhu-Hong You
(2021)Stefanie Peschel;Christian L Müller;Erika von Mutius;Anne-Laure Boulesteix
(2021)Zhen Chen;Pei Zhao;Fuyi Li;Tatiana T Marquez-Lago
(2020)Mengying Sun;Sendong Zhao;Coryandar Gilvary;Olivier Elemento
(2020)Shan-Shan Dong;Wei-Ming He;Jing-Jing Ji;Chi Zhang
(2021)Fei-Fei Hu;Chun-Jie Liu;Lan-Lan Liu;Qiong Zhang
(2021)Thomas Gaudelet;Ben Day;Arian R Jamasb;Jyothish Soman
(2021)Piyush Agrawal;Dhruv Bhagat;Manish Mahalwal;Neelam Sharma
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