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Find video protocols related to scientific articles indexed in Pubmed.
The dispanins: a novel gene family of ancient origin that contains 14 human members.
PLoS ONE
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The Interferon induced transmembrane proteins (IFITM) are a family of transmembrane proteins that is known to inhibit cell invasion of viruses such as HIV-1 and influenza. We show that the IFITM genes are a subfamily in a larger family of transmembrane (TM) proteins that we call Dispanins, which refers to a common 2TM structure. We mined the Dispanins in 36 eukaryotic species, covering all major eukaryotic groups, and investigated their evolutionary history using Bayesian and maximum likelihood approaches to infer a phylogenetic tree. We identified ten human genes that together with the known IFITM genes form the Dispanin family. We show that the Dispanins first emerged in eukaryotes in a common ancestor of choanoflagellates and metazoa, and that the family later expanded in vertebrates where it forms four subfamilies (A-D). Interestingly, we also find that the family is found in several different phyla of bacteria and propose that it was horizontally transferred to eukaryotes from bacteria in the common ancestor of choanoflagellates and metazoa. The bacterial and eukaryotic sequences have a considerably conserved protein structure. In conclusion, we introduce a novel family, the Dispanins, together with a nomenclature based on the evolutionary origin.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.