borgwardtlab Goto Github PK

homebrew-mlcb

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

imputing_signatures

indel-prediction-sv-m

Structural Variant Machine (SV-M) to accurately predict InDels from NGS paired-end short reads (Grimm et al., BMC Bioinformatics 2013) http://goo.gl/M526Av

jointmds

Official implementation of Joint Multidimensional Scaling

kernel-conditional-clustering

Kernel Conditional Clustering

kernelized-rank-learning

Kernelized rank learning for personalized drug recommendation

libtlda

Library of transfer learners and domain-adaptive classifiers.

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

longcovid

Prediction of long COVID from proteomic and clinical data

lsh-wtk

Locality-Sensitive Hashing for the Wasserstein Time Series Kernel.

maldi-learn

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

maldi_amr

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

maldi_pike

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

medical_ts_datasets

message_passing_graph_kernels

mgp-tcn

Sepsis Prediction on MIMIC

mid

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

mlgkernel

Implementation of the Multiscale Laplacian Graph Kernel

mods-recovery

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

moproembeddings

Implementation of moment propagation embeddings.

motifiesta

Approximate subgraph motif mining through learnable edge contraction.

multi-scones

Multi-task feature selection coupled with multiple network regularizers

mvkdr

Multi-view Spectral Clustering on Conflicting Views

networkgwas

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

neural-persistence

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

p-wl

A Persistent Weisfeiler–Lehman Procedure for Graph Classification

pathogenicity

The evaluation of tools used to predict the impact of missense mutations is hindered by two types of circularity (Grimm et al., Human Mutation 2015) http://goo.gl/VSosV5

persim

Distances and representations of persistence diagrams

proteinshake

Protein structure datasets for machine learning.

proteinshake_release