Julian Späth's repositories
random-survival-forest
A Random Survival Forest implementation for python inspired by Ishwaran et al. - Easily understandable, adaptable and extendable.
skin-cancer-detection
Praktikum Maschinelles Lernen 2017 der Universität Tübingen
mhc-I-epitope-predictor
MHC-class-I epitope binding predictor based on a SVM.
fc-nelson-aalen-estimator
A federated Nelson-Aalen estimator to estimate the cumulative hazard function of time-to-event data
BWA-Docker
dockerized bwa
fc-kaplan-meier-estimator
A federated Kaplan-Meier estimator to estimate the survival function
Machine-learning-without-any-libraries
This is a collection of some of the important machine learning algorithms which are implemented with out using any libraries. Libraries such as numpy and pandas are used to improve computational complexity of algorithms
pdb-viewer
A PDB Viewer Application implemented completely in JavaFX
qbic_presentations
Presentations created with reveal.js
Samtools-Docker
dockerized samtools
snv-calling-workflow
SNV calling workflow
transmembrane-identifier
Identifying transmembrane helices in tertiary structures
TSSPredator-Docker
dockerized TSSpredator
TSSTools-Docker
dockerized tsstools