Hans-Peter Lenhof

Bio: Hans-Peter Lenhof is an academic researcher from Saarland University. The author has contributed to research in topics: Macromolecular docking & Autoantibody. The author has an hindex of 44, co-authored 164 publications receiving 6046 citations. Previous affiliations of Hans-Peter Lenhof include Max Planck Society.

A new method for the gradient-based optimization of molecular complexes.

Abstract: We present a novel method for the local optimization of molecular complexes. This new approach is especially suited for usage in molecular docking. In molecular modeling, molecules are often described employing a compact representation to reduce the number of degrees of freedom. This compact representation is realized by fixing bond lengths and angles while permitting changes in translation, orientation, and selected dihedral angles. Gradient-based energy minimization of molecular complexes using this representation suffers from well-known singularities arising during the optimization process. We suggest an approach new in the field of structure optimization that allows to employ gradient-based optimization algorithms for such a compact representation. We propose to use exponential mapping to define the molecular orientation which facilitates calculating the orientational gradient. To avoid singularities of this parametrization, the local minimization algorithm is modified to change efficiently the orientational parameters while preserving the molecular orientation, i.e. we perform well-defined jumps on the objective function. Our approach is applicable to continuous, but not necessarily differentiable objective functions. We evaluated our new method by optimizing several ligands with an increasing number of internal degrees of freedom in the presence of large receptors. In comparison to the method of Solis and Wets in the challenging case of a non-differentiable scoring function, our proposed method leads to substantially improved results in all test cases, i.e. we obtain better scores in fewer steps for all complexes. © 2008 Wiley Periodicals, Inc. J Comput Chem, 2009

DrugTargetInspector: An assistance tool for patient treatment stratification.

Abstract: Cancer is a large class of diseases that are characterized by a common set of features, known as the Hallmarks of cancer. One of these hallmarks is the acquisition of genome instability and mutations. This, combined with high proliferation rates and failure of repair mechanisms, leads to clonal evolution as well as a high genotypic and phenotypic diversity within the tumor. As a consequence, treatment and therapy of malignant tumors is still a grand challenge. Moreover, under selective pressure, e.g., caused by chemotherapy, resistant subpopulations can emerge that then may lead to relapse. In order to minimize the risk of developing multidrug-resistant tumor cell populations, optimal (combination) therapies have to be determined on the basis of an in-depth characterization of the tumor's genetic and phenotypic makeup, a process that is an important aspect of stratified medicine and precision medicine. We present DrugTargetInspector (DTI), an interactive assistance tool for treatment stratification. DTI analyzes genomic, transcriptomic, and proteomic datasets and provides information on deregulated drug targets, enriched biological pathways, and deregulated subnetworks, as well as mutations and their potential effects on putative drug targets and genes of interest. To demonstrate DTI's broad scope of applicability, we present case studies on several cancer types and different types of input -omics data. DTI's integrative approach allows users to characterize the tumor under investigation based on various -omics datasets and to elucidate putative treatment options based on clinical decision guidelines, but also proposing additional points of intervention that might be neglected otherwise. DTI can be freely accessed at http://dti.bioinf.uni-sb.de.

BALL-SNP: Combining Genetic and Structural Information to Identify Candidate non-Synonymous Single Nucleotide Polymorphisms

Abstract: Background High-throughput genetic testing is increasingly applied in clinics. Next-Generation Sequencing (NGS) data analysis however still remains a great challenge. The interpretation of pathogenicity of single variants or combinations of variants is crucial to provide accurate diagnostic information or guide therapies.

NetworkTrail—a web service for identifying and visualizing deregulated subnetworks

Abstract: Summary: The deregulation of biochemical pathways plays a central role in many diseases like cancer or Parkinsons’s disease. In silico tools for calculating these deregulated pathways may help to gain new insights into pathogenic mechanisms and may open novel avenues for therapy stratification in the sense of personalized medicine. Here, we present NetworkTrail, a web service for the detection of deregulated pathways and subgraphs in biological networks. NetworkTrail uses a state-of-the-art integer linear programmingbased approach for this task and offers interfaces to the Biological Network Analyzer (BiNA) and Cytoscape Web for visualizing the resulting subnetworks. By providing an accessible interface to otherwise hard-to-use command line tools, the new web service enables nonexperts to quickly and reliably carry out this type of network analyses. Availability and implementation: NetworkTrail is a JavaServer Pages-based web service. The algorithm for finding deregulated subnetworks has been implemented in Cþþ. NetworkTrail is available at http://networktrail.bioinf.uni-sb.de/.

Efficient computation of root mean square deviations under rigid transformations.

Abstract: The computation of root mean square deviations (RMSD) is an important step in many bioinformatics applications. If approached naively, each RMSD computation takes time linear in the number of atoms. In addition, a careful implementation is required to achieve numerical stability, which further increases runtimes. In practice, the structural variations under consideration are often induced by rigid transformations of the protein, or are at least dominated by a rigid component. In this work, we show how RMSD values resulting from rigid transformations can be computed in constant time from the protein's covariance matrix, which can be precomputed in linear time. As a typical application scenario is protein clustering, we will also show how the Ward-distance which is popular in this field can be reduced to RMSD evaluations, yielding a constant time approach for their computation. © 2014 Wiley Periodicals, Inc.

Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

Abstract: Functional analysis of large gene lists, derived in most cases from emerging high-throughput genomic, proteomic and bioinformatics scanning approaches, is still a challenging and daunting task. The gene-annotation enrichment analysis is a promising high-throughput strategy that increases the likelihood for investigators to identify biological processes most pertinent to their study. Approximately 68 bioinformatics enrichment tools that are currently available in the community are collected in this survey. Tools are uniquely categorized into three major classes, according to their underlying enrichment algorithms. The comprehensive collections, unique tool classifications and associated questions/issues will provide a more comprehensive and up-to-date view regarding the advantages, pitfalls and recent trends in a simpler tool-class level rather than by a tool-by-tool approach. Thus, the survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.

Diagnostic criteria for multiple sclerosis: 2010 Revisions to the McDonald criteria

Abstract: New evidence and consensus has led to further revision of the McDonald Criteria for diagnosis of multiple sclerosis. The use of imaging for demonstration of dissemination of central nervous system lesions in space and time has been simplified, and in some circumstances dissemination in space and time can be established by a single scan. These revisions simplify the Criteria, preserve their diagnostic sensitivity and specificity, address their applicability across populations, and may allow earlier diagnosis and more uniform and widespread use.

Metascape provides a biologist-oriented resource for the analysis of systems-level datasets.

Abstract: A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era

Enrichr: a comprehensive gene set enrichment analysis web server 2016 update

Abstract: Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr.