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.

Multicenter study identified molecular blood-born protein signatures for Wilms Tumor

Abstract: Wilms Tumor (WT) is the most common renal childhood tumor. Recently, we reported a cDNA microarray expression pattern that varied between WTs with different risk histology. Since the Societe Internationale d'Oncologie Pediatrique (SIOP) in Europe initiates treatment without a histological confirmation, it is important to identify blood-born markers that indicate WT development. In a multicenter study, we established an autoantibody signature by using an array with 1,827 recombinant E. coli clones. This array was screened with sera of patients with WT recruited by SIOP or the Children's Oncology Group (COG). We report an extended number of antigens that are reactive with autoantibodies present in sera from patients with WT. We established an autoantibody signature that separates untreated patients with WT recruited in SIOP from non-WT controls with a specificity of 0.83 and a sensitivity of 0.82 at standard deviations of 0.02 and 0.04, respectively. Likewise, patients recruited in the COG in the United States were separated from the controls with an accuracy of 0.83 at a standard deviation of 0.02. Proteins that were most significant include zinc finger proteins (e.g., ZFP 346), ribosomal proteins and the protein fascin that has been associated with various types of cancer including renal cell carcinoma. Our study provides first evidence for autoantibody signatures for WTs and suggests that these may be most informative before chemotherapy. We present the first multicenter study of autoantibody signatures in patients with WT. We established an autoantibody signature that separates patients with WT from controls.

An animation of a fixed-radius all-nearest-neighbors algorithm

Abstract: This video shows an animation of an algorithm due to the authors [2] for solving the fixed-radius all-nearest-neighbors problem. In this problem, we are given a set S of n points and a real number 6, and we have to report all pairs of points that are at distance at most 6. The algorithm works in two stages. In the first stage, a grid is computed. Instead of a standard grid, we use a so-called degraded grid that is easier to construct by means of a simple sweep algorithm. This degraded grid consists of boxes with sides of length at least 8. If a box contains points of S, then its sides are of length exactly 8. In the second stage, this grid is used for the actual enumeration. For each non-empty box, it suffices to compare each of its points with all points in the same box or in one of the neighboring boxes. Although the algorithm may compare many pairs having distance more than 6, it can be shown that the total number of pairs considered is proportional to the number of pairs that are at most 6 apart. As a result, the total running time of the algorithm is proportional to n log n plus the number of pairs that are at distance at most 6. As an application, we give an animation of the algorithm of Heiden at al. [1] for triangulating the contact surface of a molecule. In a first step, points on this surface are computed. Given these points,

Large-scale validation of miRNAs by disease association, evolutionary conservation and pathway activity

Abstract: The validation of microRNAs (miRNAs) identified by next generation sequencing involves amplification-free and hybridization-based detection of transcripts as criteria for confirming valid miRNAs. S...

A NMR-spectra-based scoring function for protein docking

Abstract: A well studied problem in the area of Computational Molecular Biology is the so-called Protein-Protein Docking problem (PPD) that can be formulated as follows: Given two proteins A and B that form a protein complex, compute the 3D-structure of the protein complex AB. Protein docking algorithms can be used to study the driving forces and reaction mechanisms of docking processes. They are also able to speed up the lenghty process of experimental structure elucidation of protein complexes by proposing potential structures. In this paper, we are discussing a variant of the PPD-problem where the input consists of the tertiary structures of A and B plus an unassigned 1H-NMR spectrum of the complex AB. We present a new scoring function for evaluating and ranking potential complex structures produced by a docking algorithm. The scoring function computes a “theoretical” 1H-NMR spectrum for each tentative complex structure and subtracts the calculated spectrum from the experimental spectrum. The absolute areas of the difference spectra are then used to rank the potential complex structures. In contrast to formerly published approaches (e.g. Morelli et. al. [38]) we do not use distance constraints (intermolecular NOE constraints). We have tested the approach with the bound conformations of four protein complexes whose three-dimensional structures are stored in the PDB data bank [5] and whose 1H-NMR shift assignments are available from the BMRB database (BioMagResBank [47]).In all examples, the new scoring function produced very good rankings of the structures. The best result was obtained for an example, where all standard scoring functions failed completely. Here, our new scoring function achieved an almost perfect separation between good approximations of the true complex structure and false positives.Unfortunately, the number of complexes with known structure and available spectra is very small. Nevertheless, these experiments indicate that scoring functions based on comparisons of one- or multi-dimensional NMR spectra might be a good instrument to improve the reliability and accuracy of docking predictions and perhaps also of protein structure predictions (threading).

The role of TCF3 as potential master regulator in blastemal Wilms tumors.

Abstract: Wilms tumors are the most common type of pediatric kidney tumors While the overall prognosis for patients is favorable, especially tumors that exhibit a blastemal subtype after preoperative chemotherapy have a poor prognosis For an improved risk assessment and therapy stratification, it is essential to identify the driving factors that are distinctive for this aggressive subtype In our study, we compared gene expression profiles of 33 tumor biopsies (17 blastemal and 16 other tumors) after neoadjuvant chemotherapy The analysis of this dataset using the Regulator Gene Association Enrichment algorithm successfully identified several biomarkers and associated molecular mechanisms that distinguish between blastemal and nonblastemal Wilms tumors Specifically, regulators involved in embryonic development and epigenetic processes like chromatin remodeling and histone modification play an essential role in blastemal tumors In this context, we especially identified TCF3 as the central regulatory element Furthermore, the comparison of ChIP-Seq data of Wilms tumor cell cultures from a blastemal mouse xenograft and a stromal tumor provided further evidence that the chromatin states of blastemal cells share characteristics with embryonic stem cells that are not present in the stromal tumor cell line These stem-cell like characteristics could potentially add to the increased malignancy and chemoresistance of the blastemal subtype Along with TCF3, we detected several additional biomarkers that are distinctive for blastemal Wilms tumors after neoadjuvant chemotherapy and that may provide leads for new therapeutic regimens

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.