Computational Biology; Help Understand & Simulate Biological Structures & Processes of Life

 

Computational Biology

Computational Biology is a field of science that uses computers, databases, statistics, and math to collect, store, organize, and analyze large amounts of biological, medical, and health info. Computational Biology and bioinformatics is an interdisciplinary field that develops & applies computational methods to analyses large amounts of biological, medical, and health info/data. The field focuses on the development and application of data-analytical/theoretical methods, computational simulation techniques, and mathematical modeling in life sciences. It is likely to become the part of routine health care in the future. Applications are not limited to research and drug discovery but are already being adapted for clinical use.

Employed by pharmaceutical companies, private research institutes, nonprofits, universities, and governments, computational biologists can help doctors discover genetic causes of cancer one day and biochemists develop treatments for Alzheimer's disease. Cancer Computational Biology also focuses on analyzing molecules & processes that play an important role in cancer. Cancer bioinformatics plays an important role in monitoring and predicting the efficiency and effectiveness of the precision medicine, which provides safest and most effective therapeutic strategy based on the gene and protein variations of each subject. It is an interdisciplinary field, which harnesses computer science, mathematics, physics, and Biology.

The field of Computational Biology uses math, data analysis, and computational simulations to understand biological systems. This field draws inspiration from areas as diverse as applied mathematics, genetics, chemistry, and Biology. Ultimately, the goal of computational Biology is to develop better ways to understand the biological processes that control our lives. To design and create a new medication, scientists have turned to computational Biology. It makes use of databases containing amino-acid sequences, nucleotides, and macromolecular structures. The human brain is an excellent model for this type of research, and many robotic systems are based on its structure. These images are also used to train algorithms for computational Biology.

Scientists can also use biomedical images to model the functioning of metabolic networks and identify disease-causing genes. Because these complex pathways are dynamic, interleaved, and branched, biochemical and regulatory pathways require computing tools to both understand and model their behavior. New technologies allow scientists to explore large datasets and to perform computational experiments on genome-wide databases. Without computational tools, many aspects of Biology would be impossible to study. With advanced tools, computational biologists can generate novel hypotheses that will eventually be tested in independent data sets. Therefore, the use of computational tools has increased worldwide.

In addition to helping sequence the human genome, computational Biology has helped create accurate models of the human brain, map the 3D structure of genomes, and model biological systems. Bioinformatics applies principles of information sciences and technologies to make vast, diverse, and complex life sciences data more understandable and useful. Computational Biology uses mathematical and computational approaches to address theoretical/experimental questions in Biology. Computational Biology makes biological concepts rigorous and testable, and it provides a reference map that holds together individual insights. It is the science that answers the question “How can we learn and use models of biological systems constructed from experimental measurements?”