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Big Data for Life Science

Discover how preclinical imaging supports drug development, cancer studies, and more at the molecular level. From animal investigation to data interpretation, our cutting-edge technology leads the way. Explore next-generation sequencing and bioinformatics for precision medicine. Join us in advancing scientific research for better health outcomes.

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Big Data for Life Science

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  1. Big Data for Life Science

  2. Advanced Molecualer Vision Ltd at Stoke Rochford Pre-Clinical division Distribution k Structure in Turkey and Sales Activities for 2014/15

  3. Pre Clinical Research Definition: • Preclinical imaging is the visualization of living animals for research purposes: Drug development,, Cancer studies, Toxicology and so forth. using variety of Modalities the reachers observe changes either at organ level, Cell or molecular level. • Translational research is changing the practice of modern medicine and the way in which health problems are approached and solved. The use of small-animal models in basic and preclinical sciences is a major keystone for these kinds of research and development strategies, representing a bridge between discoveries at the molecular level and clinical implementation in diagnostics and/or therapeutics.

  4. Pre Clinical in vivo imaging modalities

  5. Animal under investigation

  6. Animal under investigation Algorithm (using the software for any of these modalities and interpretation of data) Background (noise) Signal (spectral imaging) Image format, data output

  7. From lab to bed: personalised medicine Next Generation Sequencing: Modern term in defining the sequencing Technology: Illumina (Solexa: inventions of S Balasubramanian and D Klenerman of Cambridge University) sequencing. Roche 454 sequencing. Ion torrent: Proton / PGM sequencing. SOLiDsequencing. Pre clinical Clinical : Sequencing Run, Sequencing data Human genome seq. is about 9TB, Rare disease studies Bio-informatic

  8. Conclusion To improve the scientific research Modern science seems to have data coming out of its ears. From genome sequencing machines capable of reading a human’s chromosomal DNA (about 1.5 gigabytes of data) in half an hour to particle accelerators like the Large Hadron Collider at CERN (which generates close to 100 terabytes of data a day), researchers are awash with information. Yet in this age of big data, science has a big problem: it is not doing nearly enough to encourage and enable the sharing, analysis and interpretation of the vast swatches of data that researchers are collecting. Close collaboration between all research scientist and A must investment by the government for now the next generation to come Accuracy, Precision for better Health

  9. Thank you, Ardy Arjomandi 19/05/2016

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