Bertil Schmidt
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View article: Improved vapor pressure predictions using group contribution-assisted graph convolutional neural networks (GC <sup>2</sup> NN)
Improved vapor pressure predictions using group contribution-assisted graph convolutional neural networks (GC <sup>2</sup> NN) Open
The vapor pressures (pvap) of organic molecules play a crucial role in the partitioning of secondary organic aerosol (SOA). Given the vast diversity of atmospheric organic compounds, experimentally determining pvap of each compound is unfe…
View article: Corrigendum to Studying Privacy Aspects of Learned Knowledge Bases in the Context of Synthetic and Medical Data
Corrigendum to Studying Privacy Aspects of Learned Knowledge Bases in the Context of Synthetic and Medical Data Open
This is a corrigendum to our GMDS 2024 article “Studying Privacy Aspects of Learned Knowledge Bases in the Context of Synthetic and Medical Data”, published in Studies in Health Technology and Informatics, Volume 317 (IOS Press). The corri…
View article: RMapAlign3N: Fast mapping of 3N-Reads
RMapAlign3N: Fast mapping of 3N-Reads Open
Summary Nucleotide conversion sequencing techniques are frequently used for the detection of various types of chemical modifications at nucleotide level. However, mapping of chemically treated reads to large reference sequences that contai…
View article: RabbitSketch: a high-performance sketching library for genome analysis
RabbitSketch: a high-performance sketching library for genome analysis Open
Summary We present RabbitSketch, a highly optimized library of sketching algorithms such as MinHash, OrderMinHash, and HyperLogLog that can exploit the power of modern multi-core CPUs. It provides significant speedups compared to existing …
View article: Improved vapor pressure predictions using group contribution-assisted graph convolutional neural networks (GC <sup>2</sup> NN)
Improved vapor pressure predictions using group contribution-assisted graph convolutional neural networks (GC <sup>2</sup> NN) Open
The vapor pressures (pvap) of organic molecules play a crucial role in the partitioning of secondary organic aerosol (SOA). Given the vast diversity of atmospheric organic compounds, experimentally determining pvap of each compound is unfe…
View article: Improved vapor pressure predictions using group contribution-assisted graph convolutional neural networks (GC<sup>2</sup>NN)
Improved vapor pressure predictions using group contribution-assisted graph convolutional neural networks (GC<sup>2</sup>NN) Open
The vapor pressures (pvap) of organic molecules play a crucial role in the partitioning of secondary organic aerosol (SOA). Given the vast diversity of atmospheric organic compounds, experimentally determining pvap of each compound is unfe…
View article: gpuPairHMM: High-speed Pair-HMM Forward Algorithm for DNA Variant Calling on GPUs
gpuPairHMM: High-speed Pair-HMM Forward Algorithm for DNA Variant Calling on GPUs Open
The continually increasing volume of DNA sequence data has resulted in a growing demand for fast implementations of core algorithms. Computation of pairwise alignments between candidate haplotypes and sequencing reads using Pair-HMMs is a …
View article: GPU-accelerated homology search with MMseqs2
GPU-accelerated homology search with MMseqs2 Open
Rapidly growing protein databases demand faster sensitive sequence similarity detection. We present GPU-accelerated search utilizing intra-query parallelization delivering 6x faster single-protein searches compared to state-of-the-art CPU …
View article: CUDASW++4.0: ultra-fast GPU-based Smith–Waterman protein sequence database search
CUDASW++4.0: ultra-fast GPU-based Smith–Waterman protein sequence database search Open
Background The maximal sensitivity for local pairwise alignment makes the Smith-Waterman algorithm a popular choice for protein sequence database search. However, its quadratic time complexity makes it compute-intensive. Unfortunately, cur…
View article: Studying Privacy Aspects of Learned Knowledge Bases in the Context of Synthetic and Medical Data
Studying Privacy Aspects of Learned Knowledge Bases in the Context of Synthetic and Medical Data Open
Introduction: Retrieving comprehensible rule-based knowledge from medical data by machine learning is a beneficial task, e.g., for automating the process of creating a decision support system. While this has recently been studied by means …
View article: Massively Parallel Inverse Block-sorting Transforms for bzip2 Decompression on GPUs
Massively Parallel Inverse Block-sorting Transforms for bzip2 Decompression on GPUs Open
Lossless data compression has evolved into an indispensable tool for reducing data transfer times in heterogeneous systems. However, performing decompression on host systems can create performance bottlenecks. Accelerator libraries, such a…
View article: Scalable GPU-Enabled Creation of Three Dimensional Weather Fronts
Scalable GPU-Enabled Creation of Three Dimensional Weather Fronts Open
Weather fronts play an important role in atmospheric science. Their correlation to severe natural hazards such as extreme precipitation, cyclones or thunderstorms makes localization and understanding of frontal systems an important factor …
View article: From GPUs to AI and quantum: three waves of acceleration in bioinformatics
From GPUs to AI and quantum: three waves of acceleration in bioinformatics Open
The enormous growth in the amount of data generated by the life sciences is continuously shifting the field from model-driven science towards data-driven science. The need for efficient processing has led to the adoption of massively paral…
View article: RabbitKSSD: accelerating genome distance estimation on modern multi-core architectures
RabbitKSSD: accelerating genome distance estimation on modern multi-core architectures Open
Summary We propose RabbitKSSD, a high-speed genome distance estimation tool. Specifically, we leverage load-balanced task partitioning, fast I/O, efficient intermediate result accesses, and high-performance data structures to improve overa…
View article: CUDASW++4.0: Ultra-fast GPU-based Smith-Waterman Protein Sequence Database Search
CUDASW++4.0: Ultra-fast GPU-based Smith-Waterman Protein Sequence Database Search Open
Background The maximal sensitivity for local pairwise alignment makes the Smith-Waterman algorithm a popular choice for protein sequence database search. However, its quadratic time complexity makes it compute-intensive. Unfortunately, cur…
View article: MetaTransformer: deep metagenomic sequencing read classification using self-attention models
MetaTransformer: deep metagenomic sequencing read classification using self-attention models Open
Deep learning has emerged as a paradigm that revolutionizes numerous domains of scientific research. Transformers have been utilized in language modeling outperforming previous approaches. Therefore, the utilization of deep learning as a t…
View article: DeepFilter: A Deep Learning Based Variant Filter for VarDict
DeepFilter: A Deep Learning Based Variant Filter for VarDict Open
With the development of sequencing technologies, somatic mutation analysis has become an important component in cancer research and treatment. VarDict is a commonly used somatic variant caller for this task. Although the heuristic-based Va…
View article: RabbitVar: ultra-fast and accurate somatic small-variant calling on multi-core architectures
RabbitVar: ultra-fast and accurate somatic small-variant calling on multi-core architectures Open
The continuous development of next-generation sequencing (NGS) technology has led to extensive and frequent use of genomic analysis in cancer research. The associated production of large-scale NGS datasets establishes the need for high-pre…
View article: RabbitTClust: enabling fast clustering analysis of millions bacteria genomes with MinHash sketches
RabbitTClust: enabling fast clustering analysis of millions bacteria genomes with MinHash sketches Open
We present RabbitTClust, a fast and memory-efficient genome clustering tool based on sketch-based distance estimation. Our approach enables efficient processing of large-scale datasets by combining dimensionality reduction techniques with …
View article: Convolutional neural network prediction of molecular properties for aerosol chemistry and health effects
Convolutional neural network prediction of molecular properties for aerosol chemistry and health effects Open
Quinones are chemical compounds commonly found in air particulate matter (PM). Their redox activity can generate reactive oxygen species (ROS) and contribute to the oxidative potential (OP) of PM leading to adverse health effects of aeroso…
View article: Online Event Selection for Mu3e using GPUs
Online Event Selection for Mu3e using GPUs Open
In the search for physics beyond the Standard Model the Mu3e experiment tries\nto observe the lepton flavor violating decay $\\mu^+ \\rightarrow e^+ e^- e^+$.\nBy observing the decay products of $1 \\cdot 10^8\\mu$/s it aims to either\nobs…
View article: AnySeq/GPU
AnySeq/GPU Open
In recent years, the rapidly increasing number of reads produced by next-generation sequencing (NGS) technologies has driven the demand for efficient implementations of sequence alignments in bioinformatics. However, current state-of-the-a…
View article: Automated detection and classification of synoptic scale fronts from atmospheric data grids
Automated detection and classification of synoptic scale fronts from atmospheric data grids Open
<p>Automatic determination of fronts from atmospheric data is an important task for weather prediction as well as for research of synoptic scale phenomena. We developed a deep neural network to detect and classify fronts from multi-l…
View article: Automated detection and classification of synoptic-scale fronts from atmospheric data grids
Automated detection and classification of synoptic-scale fronts from atmospheric data grids Open
Automatic determination of fronts from atmospheric data is an important task for weather prediction as well as for research of synoptic-scale phenomena. In this paper we introduce a deep neural network to detect and classify fronts from mu…