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 high-resolution map of the human small non-coding transcriptome

Abstract: Motivation Although the amount of small non-coding RNA-sequencing data is continuously increasing, it is still unclear to which extent small RNAs are represented in the human genome. Results In this study we analyzed 303 billion sequencing reads from nearly 25 000 datasets to answer this question. We determined that 0.8% of the human genome are reliably covered by 874 123 regions with an average length of 31 nt. On the basis of these regions, we found that among the known small non-coding RNA classes, microRNAs were the most prevalent. In subsequent steps, we characterized variations of miRNAs and performed a staged validation of 11 877 candidate miRNAs. Of these, many were actually expressed and significantly dysregulated in lung cancer. Selected candidates were finally validated by northern blots. Although isolated miRNAs could still be present in the human genome, our presented set likely contains the largest fraction of human miRNAs. Contact c.backes@mx.uni-saarland.de or andreas.keller@ccb.uni-saarland.de. Supplementary information Supplementary data are available at Bioinformatics online.

An algorithm for the protein docking problem

Abstract: We have implemented a parallel distributed geometrie dock.ing algorithm that uses a new measure for the size of the contact area of two moleeules. The measure is a potential function that counts the "van der Waals contacts" between the atoms of the two molecules ( the algorithm does not compute the Lennard-Jones potential). An integer constant C4 is added to the potential for each pair of atoms whose distance is in a certain interval. For each pair whose distance is smaller than the lower bound of the interval an integer constant c~ is subtracted hom the potential (c4 < c~) . The number of allowed overlapping atom pairs is handled by a third parameter N. Conformations where more than N atom pairs overlap are ignored. In our "real world" experiments we have used a small parameter N that allows small loeal penetration. Among the best five dockings found by the algorithm there was almost always a good (rms) approximation of the real conformation. In 42 of 52 test examples the best conformation with respect to the potential function was an approximation of the real conformation. The running time of our sequential algorithm is in the order of the running time of the algorithm of Norel et al. [NLW+]. The parallel version of the algorithm has a reasonable speedup and modest communication requirements.

A branch-and-cut algorithm for multiple sequence alignment

Abstract: We consider a branch-and-cut approach for solving the multiple sequence alignment problem, which is a central problem in computational biology We propose a general model for this problem in which arbitrary gap costs are allowed An interesting aspect of our approach is that the three (exponentially large) classes of natural valid inequalities that we consider turn out to be both facet-defining for the convex hull of integer solutions and separable in polynomial time Both the proofs that these classes of valid inequalities are facet-defining and the description of the separation algorithms are far from trivial Experimental results on several benchmark instances show that our method outperforms the best tools developed so far, in that it produces alignments that are better from a biological point of view A noteworthy outcome of the results is the effectiveness of using branch-and-cut with only a carefully-selected subset of the variables as a heuristic

Structure prediction of protein complexes by an NMR-based protein docking algorithm.

Abstract: 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 lengthy process of experimental structure elucidation of protein complexes by proposing potential structures. In this paper, we are discussing a variant of the protein-protein docking problem, where the input consists of the tertiary structures of proteins A and B plus an unassigned one-dimensional 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 one. 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. (2000) Biochemistry, 39, 2530–2537]) we do not use distance constraints (intermolecular NOE constraints). We have tested the approach with four protein complexes whose three-dimensional structures are stored in the PDB data bank [Bernstein et al. (1977)] and whose 1H-NMR shift assignments are available from the BMRB database. 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.

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.