Frontiers in Systems Biology is an interdisciplinary, PubMed Central, DOAJ, Scopus and WoS ESCI-indexed journal that breaks down the individualistic silos of modern-day research and promotes integration and systems thinking across scientific fields to achieve answers to life’s biggest questions.

With an international editorial board led by Field Chief Editor Prof Yoram Vodovotz (University of Pittsburgh, USA), Frontiers in Systems Biology explores the complexities of biology at a systems level and welcomes submissions that integrate theory, experimentation, and practical application, and that which helps to address fundamental questions that bridge the gap between different disciplines and methods.

The journal covers the following subject areas:

data and model integration
integrative genetics and genomics
integrative systems microbiology
integrative systems neuroscience
Evolutionary Systems Biology
multiscale mechanistic modeling
systems concepts, theory and policy in biology and medicine
systems and synthetic immunology
translational systems biology and In Silico trials.

Manuscripts that use a reductionist approach for genetic and genomic research, studies that focus solely on pre-clinical models or descriptive network models without dynamic representation of biological mechanisms, and machine learning/AI models that focus solely on diagnosis without potential interventions are not suitable for publication in this journal. Please note this journal does not accept mendelian randomization or bibliometric studies.

Frontiers in Systems Biology is committed to advancing developments in the field of systems biology research by communicating scientific knowledge to researchers and the public alike, to enable the scientific breakthroughs of the future.

As part of our commitment to promoting Systems Thinking, we have undertaken a number of webinar events within the journal which can be viewed on the Frontiers in Systems Biology Playlist on YouTube.

Impact

Frontiers in Systems Biology

Integrative Systems Neuroscience

Data and Model Integration

Multiscale Mechanistic Modeling