Abstract
Large datasets are frequently gathered, stored and analysed in the big data age with the goal of guiding biological discoveries and validating hypotheses. There is no question that the introduction of new technologies and open data initiatives has significantly enhanced the volume and diversity of data. The whole drug development process uses big data, from identifying targets and mechanisms of action to finding new leads and therapeutic candidates. With the intention of giving readers a broad overview of the computing resources and databases accessible, these approaches are shown and explored. We believe that big data leveraging should prioritize personalized care and be cost-effective. On the basis of their synergy, we suggest combining information technologies with (chemo) informatics tools to accomplish this.
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Shinde, S.S., Padule, K.B., Sawant, S.L., Sarkate, A.P. (2024). Systems Approach for Identifying Drug Targets by Computational Approaches. In: Joshi, S., Ray, R.R., Nag, M., Lahiri, D. (eds) Systems Biology Approaches: Prevention, Diagnosis, and Understanding Mechanisms of Complex Diseases. Springer, Singapore. https://doi.org/10.1007/978-981-99-9462-5_10
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