Predicting environments and host phenotypes from 16S rRNA gene sequencing using a k-mer based representation of shallow sub-samples MicroPheno is a reference- and alignment-free approach for predicting the environment or host phenotype from microbial community samples based on k-mer distributions in shallow sub-samples of 16S rRNA data. MicroPheno’s Project page
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Continuous Vector Representation of Biological Sequences
We introduce a new representation and feature extraction method for biological sequences. Named bio-vectors (BioVec) to refer to biological sequences in general with protein-vectors (ProtVec) for proteins (amino-acid sequences) and gene-vectors (GeneVec) for gene sequences, this representation can be widely used in applications of deep learning in proteomics and genomics.