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Until recently, the wet lab has been a crucial component of every biologist. Today's advances in the production of massive amounts of data and the creation of machine-learning algorithms for processing that data are changing the face of biological science—making it possible to do real science without a wet lab. David Heckerman shares several examples of how this transformation in the area of genomics is changing the pace of scientific breakthroughs. Via Szabolcs Kósa 
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Researchers at Harvard University and the California Institute of Technology (Caltech) looking to gain a better understanding of how biological pumps such as the heart work, have created an artificial jellyfish from rat heart muscle and silicon.
This is just neat biological science...
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"A succinct, yet powerful animation titled “Synthetic Biology Explained” shows the incredible potential of this emergent field and how engineering will transform the field of genetics to produce some truly amazing technology.
With the sequencing of the human genome and the increased understanding of genes that have followed..."
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From
ieet
Is policy behind science? This opinion piece explores politics and their potential limitations on science-based change.
“Increasingly, scientific consensus is failing to influence public policy. Facts, statistics and data appear insufficient to change highly politicized minds… and science has started scrutinizing why.
Alas now, this topic inevitably devolves down to our screwy American politics….”
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Genome-sequencing studies indicate that all humans carry many genetic variants predicted to cause loss of function (LoF) of protein-coding genes, suggesting unexpected redundancy in the human genome. It is estimated that human genomes typically contain ~100 genuine LoF variants with ~20 genes completely inactivated. A recent paper in Science describes some of these rare and likely deleterious LoF alleles, including 26 known and 21 predicted severe disease–causing variants, as well as common LoF variants in nonessential genes. Via Dr. Stefan Gruenwald
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The following topics are covered:
Aerospace, Anthropology, Astrobiology, Astronomy, Astrophysics, Biochemistry, Bioengineering, Biology, Biotechnology, Chemistry, Civil Engineering, Cognitive Science, Computers, Cosmology, Dentistry, Electrical Engineering, Engineering, Environment, Future, General Science, Geoscience, Machine Learning, Material Science, Mathematics, Mechanical Engineering, Medicine, Metallurgy, Mining, Nanotechnology, Oceanography, Philosophy, Physics, Physiology, Robotics, and Sociology.
Lectures are in Playlists and are alphabetically sorted with thumbnail pictures. No fee, no registration required - learn at your own pace. Certificates can be arranged with presenting universities. Via Dr. Stefan Gruenwald
Saberes Sin Fronteras OVS's curator insight,
November 30, 2014 5:33 PM
Acceso gratuito a documentos de las mejores universidades del mundo 
♥ princess leia ♥'s curator insight,
December 28, 2014 11:58 AM
WoW .. Expand your mind!! It has room to grow!!!
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A team led by Stanford bioengineering Professor Markus Covert used data from more than 900 scientific papers to account for every molecular interaction that takes place in the life cycle of Mycoplasma genitalium — the world’s smallest free-living bacterium.
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Have you watched the accelerated tech news? It's a quick and easy way to get tech news into your head.
This edition: iPads as a medical manager, retinal implants and more: video tech news
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Could Science Exchange become the Ebay of scientific research? This new marketplace helps to accelerate scientific studies by supporting collaboration and allowing researchers to share, buy and sell resources.
They vet providers, handle the monetary transactions, curate a rating system for each provider (and researcher), help providers publicize availability, and can sometimes track down exact providers...
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This 36 min video is well worth the time spent - to get an idea (hopefully a transferrable one) about Big Data and the frontiers of science. In this case both "wet lab" (test tubes microscopes) and "dry lab" (computer modeling with machine learning) and needed and so is content as well as computational literacy.