5 citations · 10 across the 7 of their papers we have counts for
7 papers
Hecate: A Modular Genomic Compressor
Kamila Szewczyk, Sven Rahmann
We present Hecate, a modular lossless genomic compression framework. It is designed around uncommon but practical source-coding choices. Unlike many single-method compressors, Heca…
Variant tolerant read mapping using min-hashing
Jens Quedenfeld, Sven Rahmann
DNA read mapping is a ubiquitous task in bioinformatics, and many tools have been developed to solve the read mapping problem. However, there are two trends that are changing the l…
Using the Expectation Maximization Algorithm with Heterogeneous Mixture Components for the Analysis of Spectrometry Data
Dominik Kopczynski, Sven Rahmann
Coupling a multi-capillary column (MCC) with an ion mobility (IM) spectrometer (IMS) opened a multitude of new application areas for gas analysis, especially in a medical context,…
Massively parallel read mapping on GPUs with PEANUT
Johannes Köster, Sven Rahmann
We present PEANUT (ParallEl AligNment UTility), a highly parallel GPU-based read mapper with several distinguishing features, including a novel q-gram index (called the q-group ind…
Protein Hypernetworks: a Logic Framework for Interaction Dependencies and Perturbation Effects in Protein Networks
Johannes Köster, Eli Zamir, Sven Rahmann
Motivation: Protein interactions are fundamental building blocks of biochemical reaction systems underlying cellular functions. The complexity and functionality of such systems eme…
Probabilistic Arithmetic Automata and their Applications
Tobias Marschall, Inke Herms, Hans-Michael Kaltenbach +1
We present probabilistic arithmetic automata (PAAs), a general model to describe chains of operations whose operands depend on chance, along with two different algorithms to exactl…