BioSystems

BioSystems - ISSN 0303-2647
Source Normalized Impact per Paper (SNIP): 0.839 Source Normalized Impact per Paper (SNIP):
SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
SCImago Journal Rank (SJR): 0.536 SCImago Journal Rank (SJR):
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal’s impact.
Impact Factor: 1.652 (2016) Impact Factor:
The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years.
© 2017 Journal Citation Reports ® (Clarivate Analytics, 2017)
5 Year Impact Factor: 1.491 (2016) Five-Year Impact Factor:
To calculate the five year Impact Factor, citations are counted in 2016 to the previous five years and divided by the source items published in the previous five years.
© 2017 Journal Citation Reports ® (Clarivate Analytics, 2017)
Volumes: Volumes 163-174
Issues: 12 issues
ISSN: 03032647

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Description

BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.

The categories and topics listed below are examples, the editors will be happy to comment on the relevance of other topics:

Molecular Evolution
Self-organizing and self-replicating systems
Origins and evolution of the genetic mechanism

Biological Information Processing
Molecular recognition
Cellular control
Neuromolecular computing
Biological adaptability
Molecular computing technologies

Evolutionary Systems
Stochastic evolutionary algorithms
Evolutionary optimization
Simulation of genetic and ecological systems
Applications (neural nets, machine learning, robotics)



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