# The longest distance relationship wormhole definition

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“The Longest Distance Relationship” isn't quite on par with last year's Hayley's torn, but when Jeff stumbles upon a wormhole, she makes a. The Longest Distance Relationship Poster . In the wormhole montage, the screen freezes on two actual images of Sinbad and the actual Jeff Fischer the voice. Define wormhole. wormhole synonyms, wormhole pronunciation, wormhole path that is shorter in distance or duration than would otherwise be expected. quantum entanglement links entities that share no obvious relationship. The terrifying incident happened at the renowned Wormhole on Inis Mor, the largest of the.

Wormhole theory Wormholes were first theorized inthough that wasn't what they were called at the time. While reviewing another physicist's solution to the equations in Albert Einstein's theory of general relativity, Austrian physicist Ludwig Flamm realized another solution was possible.

He described a "white hole," a theoretical time reversal of a black hole. Entrances to both black and white holes could be connected by a space-time conduit. InEinstein and physicist Nathan Rosen used the theory of general relativity to elaborate on the idea, proposing the existence of "bridges" through space-time.

These bridges connect two different points in space-time, theoretically creating a shortcut that could reduce travel time and distance. The shortcuts came to be called Einstein-Rosen bridges, or wormholes.

The mouths would most likely be spheroidal. The throat might be a straight stretch, but it could also wind around, taking a longer path than a more conventional route might require. Einstein's theory of general relativity mathematically predicts the existence of wormholes, but none have been discovered to date. A negative mass wormhole might be spotted by the way its gravity affects light that passes by. We start with a special type of vector space, called a manifold, with four dimensions: The space we are all used to is traditional Euclidean flat space in Cartesian coordinates.

These tensors are functions of the metric which measure the amount of curvature present at each point of our spacetime.

This describes the amount, type and distribution of energy and matter in space. In general this is very difficult to do since the equations are highly non-linear.

This is because the matter is telling spacetime how to curve, but this curvature then effects how the matter in our spacetime is moving, so we get lots of complicated feedback effects.

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The Mathematics of Wormholes Model of a two dimensional wormhole. So how do we describe a wormhole using general relativity? Essentially a wormhole is a topological feature of our manifold connecting two completely separate regions of space with a tunnel. To visualise this take a flat sheet of paper and fold it in half smoothly without creasing the fold! You now have a wormhole in two dimensional space. Wormholes were first studied mathematically in relativity as early as by the German mathematician Herman Weyl.

Shortly after, Thorne proposed the idea of a traversable wormhole that would allow an explorer to travel through a wormhole in both directions from one part of the universe to another very quickly.

A whole new area of physics research was spawned.

## The Longest Distance Relationship

This is a much simpler procedure since we no longer need to solve a complicated set of coupled partial differential equations. So what does the metric of a wormhole look like? Wikimedia Commons This metric describes two separate regions of universe, connected by a tube. These different regions can either be interpreted as two separate universes, or the same universe at a different place in time and space. More divergent gene pairs are more likely to have developed novel function, particularly in gene families that have undergone numerous duplication events.

In this study we focused specifically on the identification of LDOs. There has been recent debate surrounding this conjecture. Contrary to the ortholog conjecture, Nehrt et al. However, bias in GO annotations tends to favor functional similarity between paralogs [ 11 ], and subsequent studies using RNA-seq data [ 8 ] or bias-corrected GO annotations [ 9 ] support the ortholog conjecture.

Specifically, Chen and Zhang [ 8 ] found that gene expression similarity between orthologs is significantly higher than between paralogs across multiple tissue types, while Altenhoff et al. Thus, while orthologs and FEPs are conceptually distinct, the preponderance of evidence suggests that they are related, and in particular that identifying an ortholog as a first step toward identifying an FEP is warranted.

Because protein sequence ultimately determines function, the LDO—the ortholog with the least divergence in sequence—is therefore a strong estimate of an FEP. Likewise, observing high functional similarity between genes in different species provides evidence for, but does not guarantee, shared evolutionary history.

The past decade has seen an explosion of new methodologies and tools designed to predict orthologous genes between two or more species. The majority use one of two approaches: Graph-based algorithms begin with pairwise alignments between all protein sequences from two species to estimate evolutionary distance between each protein pair, followed by orthology prediction made using a range of clustering criteria: Roundup [ 15 ]best triangular hit e.

OrthoMCL [ 18 ]. Tree-based systems take advantage of our understanding of evolutionary relationships between species, using simultaneous alignment of sequences from many species to build phylogenetic trees and infer orthology relationships based on tree structure. Variations on this approach are employed by many popular ortholog prediction tools: HomoloGene [ 24 ] and Hieranoid [ 25 ] combine aspects of both graph- and tree-based systems, progressively applying graph-based methods at the nodes of a species tree to generate more accurate ortholog predictions while maintaining the computational efficiency inherent to tree-based methods.

A further alternative strategy is to directly identify genes in a target system that fills a functionally equivalent role. For example, the Isobase algorithm infers FEPs using both sequence information and functional information encoded in protein-protein interaction PPI networks. Each prediction algorithm uses a different methodology, producing overlapping but distinct sets of predicted orthologs or FEPs and displaying different strengths and weaknesses in terms of performance for the particular objective of that algorithm.

Shaye and Greenwald [ 26 ] created OrthoList, a set of human-worm orthology relationships, by simply combining the predictions from four commonly used ortholog prediction tools InParanoid, OrthoMCL, Homologene, and Ensembl Compara to produce a system with high recall i.

In each case, the meta-tool is shown to improve prediction performance when compared to the individual input algorithms.