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2019-06-machine-learning-for-biology

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

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).

alloimmunity-kinetics

Code for "Pre-transplant kinetics of anti-HLA antibodies in patients on the kidney transplant waiting list."

arapheno

AraPheno source code for http://arapheno.1001genomes.org

ardiss

Automatic Relevance Determination for Imputation of Summary Statistics

baselepi

SEIR model framework used to describe the spread of the first SARS-CoV-2 wave within Basel-City

batchcorrectionpublicdata

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

biobank_genomics

carpe

casmap

Detection of statistically significant combinations of SNPs in association mapping

ccsvm

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

cofi

Visualization and analysis of data sets containing time series with history information

deepest

dipha

Automatically exported from code.google.com/p/dipha

easygwascore

Computational Framework for Genome-Wide Association Studies and Meta-Studies in C/C++ with Python Interfaces

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

epistasis-lightbulb

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

filtration_curves

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

findcomb

Scientifica app for finding the most significant combinations of features

fisher_information_embedding

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

fmri_cubical_persistence

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

gene-representations-in-networks

A systematic evaluation of gene representations in network based genetic analysis

genetic-heterogeneity-discovery-fais

Genome-wide detection of intervals of genetic heterogeneity (Llinares-Lopez et al., ISMB/Bioinformatics 2015) http://goo.gl/h9gl6K

genetic-heterogeneity-discovery-fastcmh

Genome-wide detection of intervals of genetic heterogeneity while accounting for categorical covariates (Llinares-López et al., Bioinformatics 2017) https://goo.gl/2QN2La

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

glide-scripts

Companion scripts to the GLIDE software

gp-pom

graph-classification-with-tda

graph-kernels

Graph kernels

graphhopper-kernels

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