WHAT IS COMPUTATIONAL GENOMICS?
In science, we know WHY we need to discover new things. Thanks to the efforts of experimentation and our advance knowledge of scientific principles, we know WHAT we need to do. We know WHERE and WHEN we need to save lives. Computational Genomics is the question of HOW.
Using complex computer algorithms and technological processes, computational genomics is the process of deciphering and analyzing genetic data. Computational genomics is the study of how scientists seek to understand the vast and complex world of human genomics. Using increasingly intelligent technology, computational genomics analyzes, annotates, and deciphers the information gathered in research. 
In an increasingly technological world, scientists waste so much time performing genomic sequence analysis by hand. Computational genomics looks to provide the technology that can perform these analyzations and annotations manually, giving researchers the time and energy they need to solve the world's next problems. Advances made in the field of computational genomics look to make genomic analysis easier and more efficient through the use of computation and algorithmic tools.
Without the field of bioinformatics, under which computational genomics stems, data discovered (no matter how ground-breaking it is) has no way to be understood and shared. Computational genomics bridges that gap between the gathering and comprehension of data. Complex algorithms, computer codes, and software all put meaning to the raw DNA and RNA sequences generated in the lab. Computational genomics, therefore, is the science of putting the results of experiments into an analyzed language that is comprehensible, accessible, and insightful. With the help of computational genomics and bioinformatics as a whole, this information can change the world .
This video advertises the computational genomics department of Queen's University School of Medicine. It contains enlightening insight on the role and value of computational genomics in today's word of research and discovery. 
HOW IS COMPUTATIONAL
There are thousands of applications of computational genomics in the rapidly-evolving world of biotechnology. The software and algorithms that are integral to the field of computational genomics are applied to many fields of scientific research, discovery, and treatment.
One of the most timely examples of the applications of computational genomics is in the field of personalized medicine.
Personalized medicine is an approach to treating a disease that focuses on how every person has a unique risk and reaction to a specific disease. Personalized medicine acknowledges that each person has different disease risks based on their genome.
When a person gets sick, a doctor needs to analyze their genome in order to determine the best possible treatment. For this reason, personalized medicine requires a technological process called a genome-wide association study.
The use of the analysis technique of a genome-wide association study (GWAS) is critical to the success of the personalized medicine treatment effort. This whole process would not be possible without the use of the computational software developed through computational genomics .
WHO HAS CHANGED THE ANALYSIS
The field of computational genomics has seen many innovators who have changed the way the world analyzed data. Companies like 23andMe, MediSapiens, and uBiome have changed the way personalized genomic information is available to the general public. Through advanced algorithms and patented software, these companies are able to generate insightful conclusions about the results of various genetic tests that have been performed.
Similarly, companies like BioBam, Computonomics, and NeoTechnology have all developed software programs that can automatically perform analytical tasks such as organizing and graphing data, annotating gene sequences, and genotyping. These programs revolutionized the way time and energy is spent in a lab setting.
In addition, companies like Skyline Diagnostics, Biognosys, and Cofactor Genomics have all significantly changed the processes by which diseases are diagnosed and discovered. These companies all developed products that specifically and personally investigate the correlation of risk factors for disease and genetic variations.
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