BMC Systems Biology has now closed. BMC will continue to host an archive of all articles published in BMC Systems Biology and it will remain fully searchable via the BMC website. Please consider submitting to BMC Bioinformatics.
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Precision targeting offers hope after a life-changing cancer diagnosis. However, some cancers that initially respond to targeted chemotherapy become treatment-resistant — and this may have nothing to do with the drug itself. This blog describes new research helps explain how therapy-resistant cancers arise — findings with important implications for the future of cancer therapy.
BMC Systems Biology is delighted to announce the launch of a thematic series focused on highlighting original research on the emerging field of 'Systems Medicine', which will review and feature applied translational research on biological mechanisms, including the tailoring of diagnosis, prevention and treatment of disease via a multitude of methods.
BMC Series blog
Aims and scope
- Alison Cuff, BioMed Central
- Nitin Baliga, Institute for Systems Biology
- Christina Chan, Michigan State University
- Luonan Chen, Chinese Academy of Sciences
- Sang Yup Lee, Korea Advanced Institute of Science and Technology
- Pedro Mendes, Univ. of Manchester/Univ. Connecticut Health Center
- Matteo Pellegrini, University of California, Los Angeles
Nitin Baliga serves as Professor at the Institute for Systems Biology, where he was one of the founding members, and currently serves as the Director and Senior Vice President. He leads a cross-disciplinary team of scientists to address complex problems relevant to global health, personalized medicine, energy, and environment.
Model of the month
Proctor (2016) created a model to see the effect ageing and PTH hormone has on the signalling pathways that maintain the bone remodelling process. The authors ran simulations to identify possible treatments to prevent bone loss.
2017 Journal Metrics
2.05 - 2-year Impact Factor
2.505 - 5-year Impact Factor
0.689 - Source Normalized Impact per Paper (SNIP)
1.109 - SCImago Journal Rank (SJR)
Social Media Impact