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.

Fast motif matching in R

A performant, powerful query framework to search for network motifs

golang library for computing matrix profiles along with other time series analysis features

Motiflets

Time-series analysis using the Matrix profile in Julia

Bayesian Markov Model motif discovery tool version 2 - An expectation maximization algorithm for the de novo discovery of enriched motifs as modelled by higher-order Markov models.

Estimating Phylogenetic trees using six microorganisms 16S rRNA gene with Unsupervised Learning, web based tools and Molecular Evolutionary Genetics Analysis MEGA7

LoCoMotif is a time series motif discovery method that discovers variable-length motif sets in multivariate time series using time warping

R package for the RNA Centric Annotation System (RCAS)

Variational Auto Encoders for learning binding signatures of transcription factors

Time Series Motif Detection in Python

PEnG-motif is an open-source software package for searching statistically overrepresented motifs (position specific weight matrices, PWMs) in a set of DNA sequences.

The TSMD project brings together Motif Discovery methods for Time Series, aiming to compare their performance through well-defined research questions and to simplify their practical use. It provides both guidelines for selecting the most suitable methods based on the data, and accessible implementations of the most relevant approaches.

pyJASPAR: A Pythonic interface to JASPAR transcription factor motifs

Webserver for motif discovery with higher-order Bayesian Markov Models (BaMMs)

An R package for de novo discovery of enriched DNA motifs (e.g. TFBS)

Classify transcriptional factor motifs into true motifs and false motifs