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Username    jmschreiber
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19 projects

tangermeme

Last released

Biological sequence analysis for the modern age.

bam2bw

Last released

A command-line tool for converting SAM/BAM files into stranded bp resolution BigWig files.

pomegranate

Last released

A PyTorch implementation of probabilistic models.

modisco-lite

Last released

Transcription Factor MOtif Discovery from Importance SCOres - lite

bpnet-lite

Last released

bpnet-lite is a minimal implementation of BPNet, a neural network aimed at interpreting regulatory activity of the genome.

modisco

Last released

TF MOtif Discovery from Importance SCOres

dragonnfruit

Last released

dragonnfruit is a method for analyzing scATAC-seq experiments.

ledidi

Last released

Ledidi is an optimization approach for designing edits to biological sequences.

torchegranate

Last released

A rewrite of pomegranate using PyTorch.

yuzu-ism

Last released

yuzu implements a compressed-sensing based approach for speeding up saliency calculations.

avocado-epigenome

Last released

Avocado is a package for learning a latent representation of the human epigenome.

apricot-select

Last released

apricot is a package for submodular selection of representative sets for machine learning models.

kiwano

Last released

Kiwano is an implementation of an approach for prioritizing epigenomic and transcriptomic experiments.

rambutan

Last released

rambutan is a python wrapper for caffe, aiming to provide a simpler way to define, train, and evaluate models.

pythonic-porin

Last released

Nanopore Data Analysis package. Provides tools for reading data, performing event detection, segmentation, visualization, and analysis using hidden Markov models, and other tools. Designed for the UCSC Nanopore Group.

yahmm

Last released

YAHMM is a HMM package for Python, implemented in Cython for speed.

antz

Last released

antz is a bioinformatics package written for python.

yabn

Last released

YABN is a Bayesian Network package for Python, implemented in Cython for speed.

discern

Last released

DISCERN is a method for identifying perturbations between two similar graphs. It takes in samples from two networks, and identifies which features are conditionally dependent on different features between the two

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