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Name: Machine Learning and Systems Biology Research Department
Type: Organization
Bio: MLSB Department at the MPI of Biochemistry, Martinsried, Germany
Location: Germany
Name: Machine Learning and Systems Biology Research Department
Type: Organization
Bio: MLSB Department at the MPI of Biochemistry, Martinsried, Germany
Location: Germany
Introduction to Machine Learning for Biology (Workshop @ D-BSSE Retreat 2019)
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).
Code for "Pre-transplant kinetics of anti-HLA antibodies in patients on the kidney transplant waiting list."
AraPheno source code for http://arapheno.1001genomes.org
Automatic Relevance Determination for Imputation of Summary Statistics
SEIR model framework used to describe the spread of the first SARS-CoV-2 wave within Basel-City
Summary of the code published in 'reComBat: Batch effect removal in large-scale, multi-source omics data integration'.
Detection of statistically significant combinations of SNPs in association mapping
Confounder-corrected Classification with Support Vector Machines (Li et al., Bioinformatics 2011) http://goo.gl/Qz9Ap5
Visualization and analysis of data sets containing time series with history information
Automatically exported from code.google.com/p/dipha
Computational Framework for Genome-Wide Association Studies and Meta-Studies in C/C++ with Python Interfaces
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
Efficient algorithms and GPU implementations for genome-wide epistasis screens as described in (Achlioptas et al., KDD 2011) http://goo.gl/jX8kPi
Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'
Scientifica app for finding the most significant combinations of features
Official code for Fisher information embedding for node and graph learning (ICML 2023)
Code of our NeurIPS 2020 publication 'Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence'
A systematic evaluation of gene representations in network based genetic analysis
Genome-wide detection of intervals of genetic heterogeneity (Llinares-Lopez et al., ISMB/Bioinformatics 2015) http://goo.gl/h9gl6K
Genome-wide detection of intervals of genetic heterogeneity while accounting for categorical covariates (Llinares-López et al., Bioinformatics 2017) https://goo.gl/2QN2La
Official repository for the ICLR 2022 paper "Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions" https://openreview.net/forum?id=tBtoZYKd9n
Companion scripts to the GLIDE software
Graph kernels
Scalable kernels for graphs with continuous attributes (Feragen et al., NIPS 2013) http://goo.gl/VxSfzZ
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.