STUMPY is a powerful and scalable Python library for modern time series analysis

A Python library for detecting patterns and anomalies in massive datasets using the Matrix Profile

A Python 3 library making time series data mining tasks, utilizing matrix profile algorithms, accessible to everyone.

A performant, powerful query framework to search for network motifs

pyJASPAR: A Pythonic interface to JASPAR transcription factor motifs

Time Series Motif Detection in Python

A motif discovery tool to detect the occurrences of known motifs

Variational Auto Encoders for learning binding signatures of transcription factors

Classify time series data using motifs discovered from Sequitur processing of SAX discretized data.

Yet Another Model Using Neural Networks for Predicting Binding Preferences of for Test DNA Sequences

Motif discovery for DNA sequences using multiobjective optimization and genetic programming.

Motif discovery done by AI algorithms and python.

Scalable mining of multidimensional time series motifs.

Yet Another Motif Discovery Algorithm

Gibby is a Python package designed to find the motif of a transcription factor de novo based on ChIP-seq data.

DeepASMM (Deep Learning Driven Autonomous and Synergic Motif Mining Framework) is a neural network–based approach that quantifies both autonomous functionality and sequence context synergy of motifs through forward-propagation perturbation analysis.

A project to generate models of regulated bacterial promoters using genetic programming

KNN based term discovery algorithm

Motif Finding through Gibbs Sampling