Hans-Christian Ehrlich

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In life sciences, scientists are confronted with an exponential growth of biological data, especially in the genomics and proteomics area. The efficient management and use of these data, and its transformation into knowledge are basic requirements for biological research. Therefore, integration of diverse applications and data from geographically(More)
The intuitive way of chemists to communicate molecules is via two-dimensional structure diagrams. The straightforward visual representations are mostly preferred to the often complicated systematic chemical names. For chemical patterns, however, no comparable visualization standards have evolved so far. Chemical patterns denoting descriptions of chemical(More)
MOTIVATION The landscape of structural variation (SV) including complex duplication and translocation patterns is far from resolved. SV detection tools usually exhibit low agreement, are often geared toward certain types or size ranges of variation and struggle to correctly classify the type and exact size of SVs. RESULTS We present Gustaf (Generic(More)
UNLABELLED BACKGROUND Searching for substructures in molecules belongs to the most elementary tasks in cheminformatics and is nowadays part of virtually every cheminformatics software. The underlying algorithms, used over several decades, are designed for the application to general graphs. Applied on molecular graphs, little effort has been spend on(More)
We describe ProteomeTools, a project building molecular and digital tools from the human proteome to facilitate biomedical research. Here we report the generation and multimodal liquid chromatography-tandem mass spectrometry analysis of >330,000 synthetic tryptic peptides representing essentially all canonical human gene products, and we exemplify the(More)
High-resolution mass spectrometry (MS) has become an important tool in the life sciences, contributing to the diagnosis and understanding of human diseases, elucidating biomolecular structural information and characterizing cellular signaling networks. However, the rapid growth in the volume and complexity of MS data makes transparent, accurate and(More)
Retrieving molecules with specific structural features is a fundamental requirement of today's molecular database technologies. Estimates claim the chemical space relevant for drug discovery to be around 10⁶⁰ molecules. This figure is many orders of magnitude larger than the amount of molecules conventional databases retain today and will store in the(More)
A common task in drug development is the selection of compounds fulfilling specific structural features from a large data pool. While several methods that iteratively search through such data sets exist, their application is limited compared to the infinite character of molecular space. The introduction of the concept of fragment spaces (FSs), which are(More)
Chemical patterns are essential for various fields of chemical , chemoinformatic and pharmaceutical applications. So far, representations of chemical patterns are limited to linear molecular pattern languages like SMARTS [1]. As these languages are designed for computational efficiency , they are often hardly human readable. In order to improve the(More)