What does CCBL mean in LABORATORY

Motivation

The CAPS Computational Biology Laboratory recognizes that data-driven approaches in life sciences lead to improved understanding, prediction, and control of biological processes. Using data-driven research strategies helps uncover new knowledge which leads to improvements in our ability to diagnose diseases, design drugs, and optimize medical treatments. In addition, the use of computational tools enables organisms to better respond to their environment through more accurate predictions of environmental changes or emerging threats. As such, computational biology has become an essential tool for addressing complex challenges within today's rapidly changing healthcare system.

Goals

The goal of the CAPS Computational Biology Laboratory is to develop cutting-edge techniques and algorithms that leverage big data analytics and machine learning technologies in order to make sense out of large amounts of data produced by sequencing and imaging techniques. The lab's focus is on understanding how living systems work by utilizing predictive models generated from experimental data as well as gene expression networks analysis tools used for advanced drug discovery and therapeutic interventions for various diseases. Taking into consideration the tremendous diversity of biological data sources available today, CAPS aims at developing reliable methods that are applicable across different species. The core mission is thus making a difference by creating software tools which affordably enable real-time monitoring as well as intervention planning from a single source application platform capable of handling genetic/epigenetic information from any type of organism.