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The unprecedented development in novel and high throughput techniques to understand biology at multiple dimensions has opened unique challenges and opportunities for computational methodologies to harness “big data in biology” and extract actionable insights. New models and methodologies are need for systems biology-based approaches to reconcile data from different spatio-temporal scales, connecting diverse set of computational techniques towards a systems-level understand of living organisms. Current tools and techniques in computational systems biology have demonstrated their usage in various application areas. At the same time, paradigm shifts in experimental techniques, powerful data analytics, modeling and visualization methodologies, have resulted in empowering computational systems biology models and methodologies. These developments will leverage on the advancements in machine learning models, big data management and analysis as well as large scale modeling and simulations. This topic article endeavors to provide key areas of modeling and methodologies– highlighting new directions and developments, to enable computational systems biology to address the new challenges in biology and medicine. |
