Frontiers of Systems Biology in Bioinformatics

Systems biology includes the study of systems of biological components, which may be molecules, cells, organisms or entire species. Systems Biology deals with data and models at many different scales, from individual molecules through to whole organisms. Computational systems biology addresses questions fundamental to our understanding of life and progress here will lead to practical innovations in medicine, drug discovery and engineering. It aims to develop and use efficient algorithms, data structures, visualization and communication tools with the goal of computer modelling of biological systems. Systems Biology approach harnesses the power of computation and systems-level analyses to formulate and solve critical biological problems. This integrative approach of systems biology will close the loop from individual genetics to populations, and constitute the strongest asset for the successful translation of systems biology findings to clinical applications.

Relevant Conferences:

6th International Conference on Computational Systems Biology during August 22-23, 2016 at Philadelphia, USA; International Conference on Next Generation Sequencing amid July 21-22, 2016 at BERLIN, GERMANY; International Conference on Biochemistry amid October 10-12, 2016 at KUALA LUMPUR, MALAYSIA; 2nd International Conference on  Protein Engineering amid November 14-16, 2016 Atlanta, USA; 18th International Conference on Systems Biology amid January 12-13, 2016 Zurich, Switzerland; Systems Immunology 2016: From Molecular Networks to Human Biology amid January 10-14 2016 Big Sky, USA; 2nd Conference on Computational Systems Biology March 2-4, 2016 Beijing, China; Southern California Systems Biology Conference 2016 amid January 29, 2016 at Irvine, USA; International Conference on Bioinformatics amid March 4-6 2016 Allahabad, India.

Dynamical systems theory is used to describe the behaviour of complex dynamical systems by using differential equations. It deals with the long-term qualitative behaviour of dynamical systems, and studies the nature and finds the solutions of the systems which are often mechanical or physical in nature. Cancer systems biology is the application of systems biology approach to the research in cancer. Systems biology approaches will be important for developing and implementing effective strategies to deliver personalized cancer therapy. Machine learning involves the study and construction of algorithms that can learn from data and make predictions on it. It focuses on the development of computer programs that can teach themselves to grow and change when exposed to new data.

  • Cancer systems biology
  • Systems theory for complex dynamical systems
  • Machine learning algorithms

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