Discover BorgwardtLab/WTK Open Source project

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Python
License
MIT License
Created about 5 years ago
Updated 5 months ago

BorgwardtLab

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A Wasserstein Subsequence Kernel for Time Series.

SAT

Official Pytorch code for Structure-Aware Transformer.

Python

236

topological-autoencoders

Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.

Python

137

Set_Functions_for_Time_Series

Repository of the ICML 2020 paper "Set Functions for Time Series"

Python

120

TOGL

Topological Graph Neural Networks (ICLR 2022)

Python

112

GraphKernels

A package for computing Graph Kernels

C++

100

proteinshake

Protein structure datasets for machine learning.

Python

WWL

Wasserstein Weisfeiler-Lehman Graph Kernels

Python

mgp-tcn

Sepsis Prediction on MIMIC

Python

P-WL

A Persistent Weisfeiler–Lehman Procedure for Graph Classification

Python

graph-kernels

Graph kernels

C++

S3M

A software package for statistically significant shapelet mining

C++

sampling-outlier-detection

Rapid computation of distance-based outlierness scores via sampling

maldi_amr

Code for the paper "Antimicrobial resistance prediction in clinical isolates through machine learning on MALDI-TOF mass spectra"

Jupyter Notebook

PST

Protein Structure Transformer (PST): Endowing pretrained protein language models with structural knowledge

Python

Neural-Persistence

Code for the paper 'Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology'

Python

maldi-learn

Software library for Maldi-Tof preprocessing and machine learning analysis.

Python

PyChange

Multiple change detection with python

C++

JointMDS

Official implementation of Joint Multidimensional Scaling

Python

fMRI_Cubical_Persistence

Code of our NeurIPS 2020 publication 'Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence'

Python

filtration_curves

Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'

Python

fisher_information_embedding

Official code for Fisher information embedding for node and graph learning (ICML 2023)

Python

NeuralWalker

Official Pytorch implementation of NeuralWalker

Python

MvKDR

Multi-view Spectral Clustering on Conflicting Views

Python

Kernelized-Rank-Learning

Kernelized rank learning for personalized drug recommendation

Jupyter Notebook

ggme

Official repository for the ICLR 2022 paper "Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions" https://openreview.net/forum?id=tBtoZYKd9n

Python

HOGImine

Higher-order genetic interaction discovery with network-based biological priors.

C++

MotiFiesta

Approximate subgraph motif mining through learnable edge contraction.

Python

networkGWAS

Method for performing genome-wide association like studies on neighborhoods identified on biological networks relevant for the phenotype of interest.

Python

multicenter-sepsis

Python

MID

MID (Mutual Information Dimension) for measuring statistical dependence between two random variables

graphkernels-review

Code and data sets for the review on graph kernels

Python

reComBat

reComBat package to correct batch effects

Jupyter Notebook

maldi_PIKE

Code for 'Topological and kernel-based microbial phenotype prediction from MALDI-TOF mass spectra'

Python

proteinshake_models

Python

topo-ae-distances

Python

CAsMap

Detection of statistically significant combinations of SNPs in association mapping

C++

significant-subgraph-mining

Finding statistically significant subgraphs while correcting for multiple testing

C++

Kernel-Conditional-Clustering

Kernel Conditional Clustering

MATLAB

ADNI_3DCNNvsTDA

This is a summary of the model code used in "Back to the basics with inclusion of clinical domain knowledge - A simple, scalable and effective model of Alzheimer's Disease classification". It comprised the relevant 3D CNNs for hippocampus, patch and full inner brain image subsets, the TDA 2D CNN with relevant dense models to combine models trained on persistence images from different homological dimensions. Moreover, the models (GNN and LR) to combine multiple image patches are included, as well as the data splits in terms of ADNI database patient IDs (partitions).

Python

2019-06-Machine-Learning-for-Biology

Introduction to Machine Learning for Biology (Workshop @ D-BSSE Retreat 2019)

TeX

SiNIMin

Significant Network Interval Mining

C++

LSH-WTK

Locality-Sensitive Hashing for the Wasserstein Time Series Kernel.

Python

LMM-Lasso

An implementation of the Lasso model for association mapping and phenotype prediction which corrects for population strucure (Rakitsch et al., Bioinformatics 2013): http://goo.gl/FRmXwI

Python

sepsis-prediction-review

Python

uea_ucr_datasets

A small package for loading and handling UEA UCR time series classification datasets.

Python

GP-PoM

TypeScript

graphhopper-kernels

Scalable kernels for graphs with continuous attributes (Feragen et al., NIPS 2013) http://goo.gl/VxSfzZ

MATLAB

ARDISS

Automatic Relevance Determination for Imputation of Summary Statistics

Python

Topf

Topological peak filtering

Python

Epistasis-GLIDE

A C and CUDA implementation of tabulating linear regression for an exhaustive pairwise interaction search on a CUDA enabled GPU (Kam-Thong et al., Human Heredity 2012) http://goo.gl/XE54ir

Cuda

simbsig

The official implementation for the SIMBSIG package

Python

FindComb

Scientifica app for finding the most significant combinations of features

Python

Multi-SConES

Multi-task feature selection coupled with multiple network regularizers

Imputing_Signatures

Python

PheGeMIL

Python

ccSVM

Confounder-corrected Classification with Support Vector Machines (Li et al., Bioinformatics 2011) http://goo.gl/Qz9Ap5

C++

DeepEST

Python

proteinshake_release

Python

MODS-recovery

Codes for prediction of the recovery of pediatric sepsis patients with MODS

Python

GraphMatchingSubstitutionMatrices

Code and Data for the paper: Structure- and Function-Aware Substitution Matrices via Learnable Graph Matching (RECOMB 2024 & ICML 2024 Differentiable Almost Everything Workshop)

Python

SignificantPatternMiningFDR

Code and Data for the paper: FASM and FAST-YB: Significant Pattern Mining with False Discovery Rate Control (ICDM 2023).

sc-autoencoding

student internship of Simon Streib to reduce single cell data

Python

Epistasis-lightbulb

Efficient algorithms and GPU implementations for genome-wide epistasis screens as described in (Achlioptas et al., KDD 2011) http://goo.gl/jX8kPi

Python

batchCorrectionPublicData

Summary of the code published in 'reComBat: Batch effect removal in large-scale, multi-source omics data integration'.

Python

biobank_genomics

Shell

LongCOVID

Prediction of long COVID from proteomic and clinical data

Python

gene-representations-in-networks

A systematic evaluation of gene representations in network based genetic analysis

Python

homebrew-mlcb

Homebrew taps of the Machine Learning and Computational Biology group of Prof. Karsten Borgwardt

Ruby

glide-scripts

Companion scripts to the GLIDE software

Python

SCIRecoveryPredictionPublic

We provide a simple matching algorithm to identify digital twins for spinal cord injury patients in the acute injury phase.

Python

MoProEmbeddings

Implementation of moment propagation embeddings.

Python

BorgwardtLab/WTK

BorgwardtLab

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