There are 0 repository under biclustering topic.
EBIC - AI-based parallel biclustering algorithm
Subspace clustering and coclustering course at the School of Electrical and Computer Engineering (FEEC-UNICAMP)
A biclustering library with datasets, evaluation measures and a benchmarking framework
Comparison of clustering methods for determining the operational states of a wastewater treatment plant (BSc project in Statistics) :wrench: :potable_water: :arrows_counterclockwise: :recycle: :sweat_drops:
A multiobjective framework for biclustering of gene expression data. NSGA - 2 is used, for achieving multi-objective optimization of the biclusters. Biclusters are optimized on 3 objective functions: MSR, Row Variance, Area.
gBiBit: A multi-GPU biclustering algorithm for binary datasets
Used generalized Bayesian and EM algorithms combined with a priori information for data biclustering.
Implementation of the sparse singular value decomposition algorithm (Lee et al., 2010) to be used for Biclustering; Duke STA663 Final Project
gMSR: A multi-GPU algorithm to accelerate a massive validation of biclusters
UG Final Year Project based on Suffix Forest Based Tri-clustering
This repository contains code base of my Master Thesis work named under "Pattern Detection in Tabular Data with shallow hierarchy: A Visual Analytics Case Study for Narrative Visualization"
Secured Cheng and Church Algorithm performs encrypted computations such as sum, or matrix multiplication in Python for biclustering algorithm
Multi-algorithm Ensemble Biclustering Method MoSBi | Publication: https://doi.org/10.1073/pnas.2118210119
Project for master thesis. It contain developed biclustering algorithm of gene expression data.
Clustering exploration using the authors dataset
hacked code to bicluster molecules using rdkit and scikitlearn
Python tool to generate biclustering and triclustering datasets programmatically.
SecBic-CCA: Secured Biclusterings - Cheng and Church Algorithm using CKKS scheme with Pyfhel Libary over gene expression data sets.
Co-clustering, also known as biclustering or block clustering, is a powerful data analysis technique that uncovers hidden structures in complex datasets.
Applying unsupervised learning methods to cereal nutritional data