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abstractions blog

Abstractions blog

For Fluid Equations, a Steady Flow of Progress

January 13, 2020

A startling experimental discovery about how fluids behave started a wave of important mathematical proofs.

Photo of the female penis structure of the cave insect Neotrogla aurora.
Abstractions blog

Why Evolution Reversed These Insects’ Sex Organs

January 30, 2019

Among these cave insects, the females evolved to have penises — twice. The reasons challenge common assumptions about sex.

Abstractions blog

Gene Drives Work in Mice (if They’re Female)

January 23, 2019

Biologists have demonstrated for the first time that a controversial genetic engineering technology works, with caveats, in mammals.

Abstractions blog

Jellyfish Genome Hints That Complexity Isn’t Genetically Complex

January 8, 2019

Jellyfish didn’t need novel genes to take an evolutionary leap in complexity.

Abstractions blog

Ancient Turing Pattern Builds Feathers, Hair — and Now, Shark Skin

January 2, 2019

A primordial developmental toolkit shared by all vertebrates, and described by a theory of the mathematician Alan Turing, sets the growth pattern for all types of skin structures.

Abstractions blog

What a Newfound Kingdom Means for the Tree of Life

December 11, 2018

Neither animal, plant, fungus nor familiar protozoan, a strange microbe that sits in its own “supra-kingdom” of life foretells incredible biodiversity yet to be discovered by new sequencing technologies.

Abstractions blog

Why Black Hole Interiors Grow (Almost) Forever

December 6, 2018

The renowned physicist Leonard Susskind has identified a possible quantum origin for the ever-growing volume of black holes.

Photo of mice
Abstractions blog

Unexpected Diversity Found in 16 New Lab Mouse Genomes

October 1, 2018

The availability of 16 new mouse genomes will help accelerate research into the genetic underpinnings of human traits and diseases.

Diagram showing show the hierarchy of different classes.
Abstractions blog

A Short Guide to Hard Problems

July 16, 2018

What’s easy for a computer to do, and what’s almost impossible? Those questions form the core of computational complexity. We present a map of the landscape.