1066-5277
Published by: Mary Ann Liebert, Inc. Publishers
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 358 | 68 | 108 | 16 |
| Biology and Biochemistry | 729 | 18 | 27 | 6 |
Journal of Computational Biology explores disciplines such as Computational biology, Algorithm, Genetics, Artificial intelligence and Combinatorics. Computational biology research presented in the journal encompasses a variety of subjects, including Genome, Gene and DNA sequencing. Gene expression is a major topic of Gene research.
The Algorithm works featured in Journal of Computational Biology incorporate elements from Sequence, Theoretical computer science and Set (abstract data type). Topics in Artificial intelligence explored in the journal were investigated in conjunction with research in Machine learning, Data mining and Pattern recognition. The research on Combinatorics discussed in Journal of Computational Biology draws on the closely related field of Discrete mathematics.
The most cited publications focus on Algorithm, Genetics, Artificial intelligence, Computational biology and Data mining. The journal publications hold forums on Algorithm that merge themes from other disciplines such as Sequence, Theoretical computer science and Sequence assembly. Machine learning and Pattern recognition are some topics wherein Artificial intelligence research discussed in the published papers has an impact.
The journal primarily tackles Computational biology, Artificial intelligence, Gene, Genome and Internal medicine. The research on Computational biology tackled can also make contributions to studies in the areas of Genome-wide association study, Identification (biology), Cluster analysis, Genomics and microRNA. The research on Artificial intelligence featured in Journal of Computational Biology combines topics in other fields like Machine learning and Pattern recognition.
The field of Genetics is the anchor for the Gene studies presented in the journal. The work on Genome tackled in it brings together disciplines like Set (abstract data type) and Inference. Internal medicine research featured in it incorporates concerns from various other topics such as Endocrinology and Oncology.
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 Computational Biology (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 Computational Biology (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, 2.08% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 12.77% were posted by at least one author from the top 10 institutions publishing in the journal. Another 9.57% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 6.38% of all publications and 71.28% 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.
Wutao Yin;Sakib Mostafa;Fang-Xiang Wu
(2021)Unknown
(2022)Alan Kuhnle;Alan Kuhnle;Taher Mun;Christina Boucher;Travis Gagie;Travis Gagie
(2020)Tongchuan Zhang;Guodong Hu;Yuedong Yang;Jihua Wang
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