Alignment-free method to identify viral reads in RNAseq datasets based on a deep learning model and to assemble predicted viral contigs.
Ultrafast metagenomic read assignment to protein clusters by hashing of amino-acid k-mer frequencies.
ERVmancer is a bioconda package that quantifies Human Endogenous Retrovirus (HERV) short read RNA sequencing expression data by aligning short reads to a curated subset of HERVs and then resolving ambiguity in alignment using a pre-computed HERV phylogenetic tree (in prep)
CLICnet is a Python library for clustering cancer patients by survival rates, based on their somatic mutation data. CLICnet is based on a trained Restricted Boltzmann machinel.
Seeker is an alignment-free discrimination between Bacterial vs. phages DNA sequences, based on a deep learning framework. This package can call classifiers that were trained with (a) either Python Keras LSTM with embedding layer, or (b) Matlab trained LSTM with a sequence imput layer, which was converted to a Keras model.