Life Sciences Research

Life Sciences Research


 


pics-blog-mngins-4Revolutionary information flow finding in the common squid

posted by Mosaic Data Science

In June of 2000, with much fanfare, the Human Genome Project completed the initial draft of the human genome. President Bill Clinton, with British PM Tony Blair and Francis Collins, then director of the National Human Genome Research Institute, announced that the newly decoded human genome would “revolutionize the diagnosis, prevention and treatment of most, if not all, human diseases.” Collins forecasted a grand vision of “personalized medicine” by 2010. The molecular biology revolution was producing an exponentially growing volume of data and expectations were high. But ten years later, in an article entitled “Revolution Postponed,” Scientific American conceded that the Human Genome Project had “failed so far to produce the medical miracles that scientists had promised.” Much excellent research work had been accomplished, but in the age of Big Data, the Human Genome Project is an example of how complex problems are not always solved merely with more data. Big Data sometimes needs Big Analysis. Consider the recent findings that the common squid, Doryteuthis pealeiirecodes, massively reprograms its own genetic data in real time.

 

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pics-blog-mngins-5New Healthcare Study on Survivability Yields Some Surprises

posted by Mosaic Data Science

Fitness trainers have long since debated the virtues of volume versus intensity. Should I do 50 pushups or a dozen bench presses? Now a new data analysis study of 58,000 heart stress tests suggests that when it comes to survivability, high stress exercise may be more important than high-repetitions. That may come as a surprise to those who like to take long walks.

The first lesson healthcare researchers learn is to expect the unexpected. Any new data set usually has a few surprises and so it is important to impose a minimum of structure while analyzing the data. It is important to let the data speak for itself. In this study, demographic, clinical, exercise, and mortality data were collected for 58,020 participants from the Detroit, Michigan area. Participants were almost evenly split between male and female and the median age was 53 years. The data run from 1991-2009 with a 10-year median span for each participant.

 

 

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pics-blog-mngins-5A Light Regulatory Touch Helps the NGS Data Revolution

posted by Mosaic Data Science

About twenty years ago the post-genomic era began to emerge in computation biology disciplines. Rather than information flowing from DNA to RNA to protein sequences, a new central dogma, much broader in scope, began to take shape. Genomes led to gene products, which implied structures and functions, which led to pathways and physiology. In the post-genomic era computational biology would move from single genes and single functions to systems of genes, structures, functions, pathways and behaviors. And when this new approach was applied to the new genomics data the result would be, as Francis Collins put it, personalized medicine. That day is now soon approaching with…

 

 

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pics-blog-mngins-5The Next Revolution: noninvasive and global visualization of protein metabolism

posted by Mosaic Data Science

Fifty years ago the data revolution in molecular biology was beginning as Max Perutz had shown how to map protein tertiary structure using X-ray crystallography and Pehr Edman was learning to read the primary structure amino acid sequence using degradation. Since then, ever-improving methods have led to a data explosion, requiring new and better methods for analyzing and modeling the plethora of data in both research and in healthcare. Bioinformatics, computational biology, healthcare data analysis, and healthcare predictive modeling are working to keep pace with the enormous wealth of information, and now…

 

 

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