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Shannon's diagram of a general communications system, showing the process by which a message sent becomes the message received (possibly corrupted by noise). seq2seq is an approach to machine translation (or more generally, sequence transduction) with roots in information theory, where communication is understood as an encode-transmit-decode process, and machine translation can be studied as a ...
2 Base Encoding, also called SOLiD (sequencing by oligonucleotide ligation and detection), is a next-generation sequencing technology developed by Applied Biosystems and has been commercially available since 2008. These technologies generate hundreds of thousands of small sequence reads at one time.
Keras is an open-source library that provides a Python interface for artificial neural networks. Keras was first independent software, then integrated into the TensorFlow library , and later supporting more.
Peak calling is a computational method used to identify areas in a genome that have been enriched with aligned reads as a consequence of performing a ChIP-sequencing or MeDIP-seq experiment. These areas are those where a protein interacts with DNA . [ 1 ]
If you've been having trouble with any of the connections or words in Friday's puzzle, you're not alone and these hints should definitely help you out. Plus, I'll reveal the answers further down ...
A recursive neural network is a kind of deep neural network created by applying the same set of weights recursively over a structured input, to produce a structured prediction over variable-size input structures, or a scalar prediction on it, by traversing a given structure in topological order.
A video of Joe Alwyn's red carpet interview with Amelia Dimoldenberg at the GQ Men of the Year Awards has received more than 1.5 million views on TikTok
For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...