Translational Genomics
WHAT IS COMPUTATIONAL BIOLOGICAL SCIENCE?
1. There's vast genomics data generated from sequencing machines
2. Bacteria, Yeast, Insects, Plants, Animals and Humans are being sequenced to understand life at a molecular level
3. The theory of Human and environment well being is more important now than ever before
4. Modern computers can analyze these vast amounts of data in a tangible time
5. Humans have the tools ( well need more efficient tools) to study these complex systems
6. Computational (not bioinformatics) methods have the power to forecast and predict actionable insights about human and environment
7. Applying Mathematics, Statistics and analytics with computing is the key for Translational Medicine
Next generation sequencing ( a big boon for bio-scientists) for studying complex human and environment systems is constantly gaining a lot of momentum and importance in Translational Genomics. The Next Generation Sequencing companies are constantly increasing the speed of sequencing, and at the same time have managed to constantly reduce the cost of sequencing by innovating newer and efficient chemistry. However the value, unfortunately does not lie in sequencing rather it lies in deciphering what these sequencing reads mean to us at large. Thanks to faster and cost-effective sequencing technology which has made study of genomics more feasible, but studying alone does not identify how to interpret and apply these results for having a high nutritional crop or for managing complex diseases such as cancer. Indeed, even if Next Generation Sequencing companies started to offer sequencing for free, the problems of applied genomics in agriculture and disease management would not be solved.
Computational biology is the application of computer algorithms to the field of molecular biology. And Next Generation Sequencing (NGS) technology has reshaped how informatics has to be applied to solve some of the complex biological processes. Developing and applying computationally intensive techniques (e.g., pattern recognition, data mining, machine learning algorithms, and visualization) to perform assembly and analysis has reached a new high with NGS machines producing huge amounts of data (in the order of tera bytes). Major research on better and efficient algorithms need to be carried to address sequence alignment, gene finding, genome assembly, protein structure alignment, protein structure prediction, prediction of gene expression and protein-protein interactions, genome-wide association studies and the modeling of evolution.
At Geschickten we have designed specific NGS data analysis products and for the first time in the industry introduced Cloud based NGS data analysis service (link to www.genomecomputingcenter.com). Integrated with multidisciplinary team we can help you to extract more information from your NGS data.
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