CLOUDS OF UNRELATED CRIMINALS ATTACKING PLANET EARTH

Theseus - Life-sized magnetic mouse

Year: 1950 Creator: Claude Shannon Video: AT&T Website - (Original Bell Labs) "one of the world’s first examples of machine learning: a robotic maze-solving mouse known as Theseus. The Theseus of ancient Greek mythology navigated a minotaur’s labyrinth and escaped by following a thread he’d used to mark his path. But Shannon’s electromechanical toy was able to “remember” its path with the help of telephone relay switches.

As the film begins, Shannon’s wheeled mouse methodically explores its surroundings—a 25-square maze. Shannon tells viewers that the maze’s metal walls can be freely rearranged, so Theseus must use a small computing machine to learn the layout anew each time. But the mouse, a tiny wooden device containing a bar magnet and adorned with wire whiskers, is “far too small” to contain a computing machine, he says. Instead, the machinery is hidden beneath the floor of the maze, a series of telephone relay circuits he has repurposed to do something that they had never done before: learn." - MIT Technology Review

Revolutionizing Protein Function Prediction from Sequence with Statistics-Informed Graph Networks

PhiGnet predicts protein functions using sequence data, closing gaps in annotations without structural information.

Understanding the complex mechanisms behind many essential biological activities is essential for developing new drugs and has broad ramifications in the disciplines of biotechnology, medicine, and drug development. Still, about 200 million proteins are uncharacterized, and computational attempts foresee annotations of different quality, mostly depending on protein structural information. Here, scientists describe a method for predicting protein activities just based on the sequence by using graph networks informed by statistics. PhiGnet is a quantitative evaluation technique that allows for the quantitative evaluation of particular functions by characterizing evolutionary signatures. Even in the absence of structural information, it reduces the sequence-function gap. In research and biology, this approach identifies functional sites at the residue level, offering significant assistance in the interpretation of the characteristics and novel functions of proteins.

The prediction of protein structure has benefited greatly from the evolutionary knowledge found in protein sequences that have been obtained through genome sequencing. Protein functional sites have been characterized by the couplings between paired residues, which capture interactions between residues that support particular functionalities. 

The identification of disease variations, allosteric mechanisms in proteins, and metamorphism in proteins—reversible transitions between distinct folds, frequently accompanied by diverse functions—have all been made possible by this data. Comprehending the molecular functioning of living creatures, health, sickness, and evolution requires an understanding of protein function.

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CRIMINALS WITH POOR INFORMATION SOURCES BEHAVING ERRATICALLY (NOT TRYING TO REMAIN UNDETECTED OR BASICALLY TOTALLY INSUFFICIENT KNOWLEDGE) CONTROLLED OR GUIDED VARIOUS WAYS TO MINIMIZE TERROR. IF YOU'RE ARGUING TERROR SHOULD INCREASE OR EVEN BE ALLOWED ANYWHERE YOU ARE WRONG. STRAIGHT UP OPENLY BEING CRIMINAL IS WRONG AND NEVER ALLOWED OR ENCOURAGED.

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CRIMINALS SIGNING INDIVIDUALS UP FOR LIFE SUPPORT AND DEFENSIVE SYSTEMS FRAUDULENTLY TO MANIPULATE THOSE SYSTEMS USING THEIR ACCESS CREDENTIALS.

SELL ACCESS TO EARTH TO SELL ACCESS TO BROWN TOWN