The putative fossils formed just a few hundred million years after Earth itself
But a new report says females are catching up
Anesthesia induces unconsciousness by changing the function of proteins that reside on the surface of a thin membrane that forms a barrier around all cells, according to new research from Weill Cornell Medicine scientists. The findings challenge a century-old concept of how anesthetics work and may help guide the development of new agents associated with fewer side effects.
An endless world map: Viewing the world through "Authagraph"
"Mr. Narukawa is the inventor of Authagraph, a world map designed to fit the world into a rectangle while almost perfectly maintaining the continents' relative size. It is mathematically impossible to precisely project the earth's sphere onto a rectangle. As such, previous methods would succeed in either taking on a rectangular shape or being true to the size ratio and shape of each continent, but never in both. Authagraph is groundbreaking in that it takes on both of those qualities, making it applicable to various themes such as sea routes, geology, meteorology and world history in ways never thought possible.
Instead of abstracting the globe into a cylinder, then a plane, as the more common Mercator projection map does, the AuthaGraph turns the Earth into a tetrahedron, which then unfolds in any number of ways. The map can then be tessellated similar to the way that we can traverse the planet–without ever coming to an end.
Rather than having just one focal point—the North Atlantic in Mercator’s case—nearly any place around the Earth can be at the center. The effect also means that the relative sizes of countries and their locations are much more representative than prior maps.
For more details, see also Japanese Designers May Have Created the Most Accurate Map of Our World: See the AuthaGraph | Open CultureSyndicated copies to:
One of the most important use cases of ontologies is the calculation of similarity scores between a query and items annotated with classes of an ontology. The hierarchical structure of an ontology does not necessarily reflect all relevant aspects of the domain it is modelling, and this can reduce the performance of ontology-based search algorithms. For instance, the classes of phenotype ontologies may be arranged according to anatomical criteria, but individual phenotypic features may affect anatomic entities in opposite ways. Thus, "opposite" classes may be located in close proximity in an ontology; for example enlarged liver and small liver are grouped under abnormal liver size. Using standard similarity measures, these would be scored as being similar, despite in fact being opposites. In this paper, we use information about opposite ontology classes to extend two large phenotype ontologies, the human and the mammalian phenotype ontology. We also show that this information can be used to improve rankings based on similarity measures that incorporate this information. In particular, cosine similarity based measures show large improvements. We hypothesize this is due to the natural embedding of opposite phenotypes in vector space. We support the idea that the expressivity of semantic web technologies should be explored more extensively in biomedical ontologies and that similarity measures should be extended to incorporate more than the pure graph structure defined by the subclass or part-of relationships of the underlying ontologies.
@lpachter Your cup of tea over at UCLA next week? Regulatory & Epigenetic Stochasticity in Development & Disease http://www.ipam.ucla.edu/programs/workshops/regulatory-and-epigenetic-stochasticity-in-development-and-disease
Pachter, a computational biologist, returns to CalTech to study the role and function of RNA.
Pachter, a computational biologist and Caltech alumnus, returns to the Institute to study the role and function of RNA.
Lior Pachter (BS ’94) is Caltech’s new Bren Professor of Computational Biology. Recently, he was elected a fellow of the International Society for Computational Biology, one of the highest honors in the field. We sat down with him to discuss the emerging field of applying computational methods to biology problems, the transition from mathematics to biology, and his return to Pasadena. Continue reading “👓 A Conversation with @LPachter (BS ’94) | Caltech”
New discoveries about the human mind show the limitations of reason.
A decades-old method called the “bootstrap” is enabling new discoveries about the geometry underlying all quantum theories.
In the 1960s, the charismatic physicist Geoffrey Chew espoused a radical vision of the universe, and with it, a new way of doing physics. Theorists of the era were struggling to find order in an unruly zoo of newfound particles. They wanted to know which ones were the fundamental building blocks of nature and which were composites. But Chew, a professor at the University of California, Berkeley, argued against such a distinction. “Nature is as it is because this is the only possible nature consistent with itself,” he wrote at the time. He believed he could deduce nature’s laws solely from the demand that they be self-consistent. Continue reading “👓 Physicists Uncover Geometric ‘Theory Space’ | Quanta Magazine”Syndicated copies to:
Seymour Papert’s Mindstorms was published by Basic Books in 1980, and outlines his vision of children using computers as instruments for learning. A second edition, with new Forewords by John Sculley and Carol Sperry, was published in 1993. The book remains as relevant now as when first published almost forty years ago.
The Media Lab is grateful to Seymour Papert’s family for allowing us to post the text here. We invite you to add your comments and reflections.
If you are interested in purchasing the print edition of Mindstorms, please visit Basic Books.
from the MIT Media Lab.
A country's mix of products predicts its subsequent pattern of diversification and economic growth. But does this product mix also predict income inequality? Here we combine methods from econometrics, network science, and economic complexity to show that countries exporting complex products (as measured by the Economic Complexity Index) have lower levels of income inequality than countries exporting simpler products. Using multivariate regression analysis, we show that economic complexity is a significant and negative predictor of income inequality and that this relationship is robust to controlling for aggregate measures of income, institutions, export concentration, and human capital. Moreover, we introduce a measure that associates a product to a level of income inequality equal to the average GINI of the countries exporting that product (weighted by the share the product represents in that country's export basket). We use this measure together with the network of related products (or product space) to illustrate how the development of new products is associated with changes in income inequality. These findings show that economic complexity captures information about an economy's level of development that is relevant to the ways an economy generates and distributes its income. Moreover, these findings suggest that a country's productive structure may limit its range of income inequality. Finally, we make our results available through an online resource that allows for its users to visualize the structural transformation of over 150 countries and their associated changes in income inequality between 1963 and 2008.
Syndicated copies to:
The mix of products that countries export is a good predictor of income distribution, study finds.
The interplay between structural connections and emerging information flow in the human brain remains an open research problem. A recent study observed global patterns of directional information flow in empirical data using the measure of transfer entropy. For higher frequency bands, the overall direction of information flow was from posterior to anterior regions whereas an anterior-to-posterior pattern was observed in lower frequency bands. In this study, we applied a simple Susceptible-Infected-Susceptible (SIS) epidemic spreading model on the human connectome with the aim to reveal the topological properties of the structural network that give rise to these global patterns. We found that direct structural connections induced higher transfer entropy between two brain regions and that transfer entropy decreased with increasing distance between nodes (in terms of hops in the structural network). Applying the SIS model, we were able to confirm the empirically observed opposite information flow patterns and posterior hubs in the structural network seem to play a dominant role in the network dynamics. For small time scales, when these hubs acted as strong receivers of information, the global pattern of information flow was in the posterior-to-anterior direction and in the opposite direction when they were strong senders. Our analysis suggests that these global patterns of directional information flow are the result of an unequal spatial distribution of the structural degree between posterior and anterior regions and their directions seem to be linked to different time scales of the spreading process.
One of America’s foremost philosophers offers a major new account of the origins of the conscious mind.
How did we come to have minds?
For centuries, this question has intrigued psychologists, physicists, poets, and philosophers, who have wondered how the human mind developed its unrivaled ability to create, imagine, and explain. Disciples of Darwin have long aspired to explain how consciousness, language, and culture could have appeared through natural selection, blazing promising trails that tend, however, to end in confusion and controversy. Even though our understanding of the inner workings of proteins, neurons, and DNA is deeper than ever before, the matter of how our minds came to be has largely remained a mystery.
That is now changing, says Daniel C. Dennett. In From Bacteria to Bach and Back, his most comprehensive exploration of evolutionary thinking yet, he builds on ideas from computer science and biology to show how a comprehending mind could in fact have arisen from a mindless process of natural selection. Part philosophical whodunit, part bold scientific conjecture, this landmark work enlarges themes that have sustained Dennett’s legendary career at the forefront of philosophical thought.
In his inimitable style―laced with wit and arresting thought experiments―Dennett explains that a crucial shift occurred when humans developed the ability to share memes, or ways of doing things not based in genetic instinct. Language, itself composed of memes, turbocharged this interplay. Competition among memes―a form of natural selection―produced thinking tools so well-designed that they gave us the power to design our own memes. The result, a mind that not only perceives and controls but can create and comprehend, was thus largely shaped by the process of cultural evolution.
An agenda-setting book for a new generation of philosophers, scientists, and thinkers, From Bacteria to Bach and Back will delight and entertain anyone eager to make sense of how the mind works and how it came about.
4 color, 18 black-and-white illustrations
Syndicated copies to:
Epigenetics refers to information transmitted during cell division other than the DNA sequence per se, and it is the language that distinguishes stem cells from somatic cells, one organ from another, and even identical twins from each other. In contrast to the DNA sequence, the epigenome is relatively susceptible to modification by the environment as well as stochastic perturbations over time, adding to phenotypic diversity in the population. Despite its strong ties to the environment, epigenetics has never been well reconciled to evolutionary thinking, and in fact there is now strong evidence against the transmission of so-called “epi-alleles,” i.e. epigenetic modifications that pass through the germline.
However, genetic variants that regulate stochastic fluctuation of gene expression and phenotypes in the offspring appear to be transmitted as an epigenetic or even Lamarckian trait. Furthermore, even the normal process of cellular differentiation from a single cell to a complex organism is not understood well from a mathematical point of view. There is increasingly strong evidence that stem cells are highly heterogeneous and in fact stochasticity is necessary for pluripotency. This process appears to be tightly regulated through the epigenome in development. Moreover, in these biological contexts, “stochasticity” is hardly synonymous with “noise”, which often refers to variation which obscures a “true signal” (e.g., measurement error) or which is structural, as in physics (e.g., quantum noise). In contrast, “stochastic regulation” refers to purposeful, programmed variation; the fluctuations are random but there is no true signal to mask.
This workshop will serve as a forum for scientists and engineers with an interest in computational biology to explore the role of stochasticity in regulation, development and evolution, and its epigenetic basis. Just as thinking about stochasticity was transformative in physics and in some areas of biology, it promises to fundamentally transform modern genetics and help to explain phase transitions such as differentiation and cancer.
This workshop will include a poster session; a request for poster titles will be sent to registered participants in advance of the workshop.
Adam Arkin (Lawrence Berkeley Laboratory)
Gábor Balázsi (SUNY Stony Brook)
Domitilla Del Vecchio (Massachusetts Institute of Technology)
Michael Elowitz (California Institute of Technology)
Andrew Feinberg (Johns Hopkins University)
Don Geman (Johns Hopkins University)
Anita Göndör (Karolinska Institutet)
John Goutsias (Johns Hopkins University)
Garrett Jenkinson (Johns Hopkins University)
Andre Levchenko (Yale University)
Olgica Milenkovic (University of Illinois)
Johan Paulsson (Harvard University)
Leor Weinberger (University of California, San Francisco (UCSF))