BioSystems

Top Research Topics at BioSystems?

The discussions in the journal mainly cover the fields of Artificial intelligence, Biochemistry, Genetics, Biological system and Theoretical computer science. The journal explores topics in Artificial intelligence which can be helpful for research in disciplines like Machine learning and Pattern recognition. Biochemistry and Biophysics are closely related fields of research discussed in BioSystems.

BioSystems investigates Genetics research which frequently intersects with Computational biology.

• Artificial intelligence (12.66%)
• Biochemistry (8.69%)
• Genetics (6.93%)

What are the most cited papers published in the journal?

• Ant colonies for the travelling salesman problem (1676 citations)
• Coevolutionary games--a mini review. (1401 citations)
• Autopoiesis: The Organization of Living Systems, Its Characterization and a Model (1254 citations)

Research areas of the most cited articles at BioSystems:

The journal papers focus largely on the fields of Artificial intelligence, Theoretical computer science, Genetics, Biochemistry and Biological system. While the most cited papers focused on Artificial intelligence, they were also able to explore topics like Machine learning and Pattern recognition. The published papers concentrate on Genetics topics that focus on Gene, Genome, Codon usage bias, Transfer RNA and Genetic code.

What topics the last edition of the journal is best known for?

• Gene
• Enzyme
• Quantum mechanics

The previous edition focused in particular on these issues:

The main research concerns discussed in BioSystems are Context (language use), Computational biology, Epistemology, Evolutionary biology and Theoretical computer science. The work on Context (language use) tackled in it brings together disciplines like Cognitive science and Abiogenesis. The studies in Computational biology featured incorporate elements of RNA, Gene and DNA.

The Epistemology study featured in it draws parallels with the field of Natural selection. While the journal focused on Evolutionary biology, it was also able to explore topics like Last universal ancestor and Mechanism (biology). BioSystems addresses concerns in Theoretical computer science which are intertwined with other disciplines, such as Structure (mathematical logic), Representation (mathematics) and Living systems.

The most cited articles from the last journal are:

• The origin of symbiogenesis: An annotated English translation of Mereschkowsky's 1910 paper on the theory of two plasma lineages. (9 citations)
• Reactive fungal wearable (8 citations)
• Voevodsky's unfinished project: Filling the gap between pure and applied mathematics. (7 citations)

Papers citation over time

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.

Top authors and change over time

The top authors publishing in BioSystems (based on the number of publications) are:

• Yukio Pegio Gunji (38 papers) absent at the last edition,
• Michael Conrad (36 papers) absent at the last edition,
• Andrew Adamatzky (32 papers) published 6 papers at the last edition, 3 more than at the previous edition,
• Abir U. Igamberdiev (31 papers) published 5 papers at the last edition, 2 more than at the previous edition,
• Sidney W. Fox (23 papers) absent at the last edition.

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.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in BioSystems (based on the number of publications) are:

• Russian Academy of Sciences (85 papers) published 7 papers at the last edition, 2 more than at the previous edition,
• Wayne State University (63 papers) published 5 papers at the last edition, 3 more than at the previous edition,
• Moscow State University (54 papers) published 2 papers at the last edition, 1 less than at the previous edition,
• Osaka University (50 papers) absent at the last edition,
• Max Planck Society (47 papers) absent at the last edition.

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.

Publication chance based on affiliation

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, 12.42% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 20.90% were posted by at least one author from the top 10 institutions publishing in the journal. Another 4.48% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 2.99% of all publications and 71.64% were from other institutions.

Returning Authors Index

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.

Returning Institution Index

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.

The experience to innovation index

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:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Partnerships and Collaborations in BioSystems

Navigating the realm of scientific research can often be complex and overwhelming. The same is true for researchers in BioSystems, as they frequently collaborate with university programs and institutes globally to ensure diversified viewpoints and a rich exchange of information. Notably, these partnerships become instrumental in further enhancing the quality and impact of research.

One of our consistent partners that has significantly contributed to our research and findings are the accredited medical assistant programs in Minnesota. Their insightful contributions on topics like Genetics, Biochemistry and Biological system have been invaluable in pushing the research agenda of BioSystems.

These partnerships and collaborations have not only broadened our research scope but have allowed us to stay on the cutting edge of scientific exploration. This synergy creates a stimulating environment that fosters vitality and dynamism in journal discussions and contributes collectively to the overall development in the Artificial intelligence, Biochemistry, Genetics and Biological systems research.