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SciTech Birth Day: February 11
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02. Alternative Energy
03. Computer Power
04. Nanotechnology
05. Stem Cells
06. Communications
07. Hydrocarbon Use
08. Clean Transportation
09. Online Information
10. DNA Decoding
11. Cell Biology
12. Photonics
13. Proteomics
14. Quantum Physics
15. Genetic Modification
16. Degrading Oceans
17. Robotics
18. Nanomedicine
19. Neuroscience
20. Extending Lifespan
21. Overpopulation
22. Scientific Instruments
23. Synthetic Biology
24. Nuclear Physics
25. Artificial Intelligence
26. Body Implants
27. Major Disease Cures
28. Water Shortage
29. Species Loss
30. Brain Enhancement
31. Origin of Life
32. Sensor Technology
33. Pandemics
34. Exogenous Life
35. Dark Matters
36. Cosmology
37. Energy Storage
38. Virtual/Augmented Reality
39. Space Exploration
40. Impact Event
Impact Areas listed in order of ranking

New study and research tool: DNA mutations and molecular effects
Genetic mutations can cause diseases. That’s been known for many decades. However, there are tens of thousands of known mutations that can happen to the human genome. Not all of them cause diseases. Also, it’s known that mutations that have an impact on biological processes usually rearrange the amino acids that build proteins. However, the actual chain of chemical events that lead from mutation to dysfunctional protein is generally not known at the molecular level. So, wouldn’t it be great if there was a database that catalogued most of the major known mutations, identified the amino acids most likely affected by them, and used computer modeling to make inferences about the kind of protein chemistry that would result? Yes, it would be great, and it has just been done. A massive team of researchers have put together a major reference tool for mutation research.
The research study focused on the ‘out of order’ amino acids, called amino acid substitutes (AAS), comparing the amino acids produced by mutated genes and those from normal genes. They looked for statistical differences between the percentage of mutations that shared a DNA site with both non-disease and disease-associated amino acid substitutes. Then they looked for changes in protein activity (enrichment or depletion) based on the type of AAS. This information was used to generate hypothetical molecular models for the mechanism of genetic disease. Over 40,000 amino acid substitutes were analyzed, the most comprehensive study of mutations to-date.
In today’s scientific world, big projects usually require big teams, often assembled from many institutions. This is clearly the case for the mutations database and statistical modeling – lists like the following are not exciting reading, but this one is instructive:
The information provided by this study, including the on-line reference tool (Mutation Database) are intended to assist further research into the details of molecular changes in disease causing mutations. It will hopefully stimulate ideas and research that no one in the study had even thought about.