Showing papers by "Hans-Peter Lenhof published in 2010"
TL;DR: A Lamarckian genetic algorithm (LGA) variant for flexible ligand‐receptor docking which allows to handle a large number of degrees of freedom and may be used to dock ligands with many rotatable bonds with high efficiency.
Abstract: We present a Lamarckian genetic algorithm (LGA) variant for flexible ligand-receptor docking which allows to handle a large number of degrees of freedom. Our hybrid method combines a multi-deme LGA with a recently published gradient-based method for local optimization of molecular complexes. We compared the performance of our new hybrid method to two non gradient-based search heuristics on the Astex diverse set for flexible ligand-receptor docking. Our results show that the novel approach is clearly superior to other LGAs employing a stochastic optimization method. The new algorithm features a shorter run time and gives substantially better results, especially with increasing complexity of the ligands. Thus, it may be used to dock ligands with many rotatable bonds with high efficiency.
161 citations
TL;DR: This study provides strong evidence for miRNA expression signatures of blood cells as useful biomarkers for melanoma and finds that blood samples of melanoma patients and healthy individuals can be well differentiated from each other based on mi RNA expression analysis.
Abstract: Background
MicroRNA (miRNA) signatures are not only found in cancer tissue but also in blood of cancer patients. Specifically, miRNA detection in blood offers the prospect of a non-invasive analysis tool.
158 citations
TL;DR: This study represents a comprehensive theoretical analysis of the relationship between miRNAs and their predicted target pathways, and provides a ‘miRNA-target pathway’ dictionary, which enables researchers to identify target pathways of differentially regulated mi RNAs.
Abstract: While in the last decade mRNA expression profiling was among the most popular research areas, over the past years the study of non-coding RNAs, especially microRNAs (miRNAs), has gained increasing interest. For almost 900 known human miRNAs hundreds of pretended targets are known. However, there is only limited knowledge about putative systemic effects of changes in the expression of miRNAs and their regulatory influence. We determined for each known miRNA the biochemical pathways in the KEGG and TRANSPATH database and the Gene Ontology categories that are enriched with respect to its target genes. We refer to these pathways and categories as target pathways of the corresponding miRNA. Investigating target pathways of miRNAs we found a strong relation to disease-related regulatory pathways, including mitogen-activated protein kinase (MAPK) signaling cascade, Transforming growth factor (TGF)-beta signaling pathway or the p53 network. Performing a sophisticated analysis of differentially expressed genes of 13 cancer data sets extracted from gene expression omnibus (GEO) showed that targets of specific miRNAs were significantly deregulated in these sets. The respective miRNA target analysis is also a novel part of our gene set analysis pipeline GeneTrail. Our study represents a comprehensive theoretical analysis of the relationship between miRNAs and their predicted target pathways. Our target pathways analysis provides a 'miRNA-target pathway' dictionary, which enables researchers to identify target pathways of differentially regulated miRNAs.
104 citations
TL;DR: This work discusses BALL's current functionality and highlights the key additions and improvements: support for additional file formats, molecular edit-functionality, new molecular mechanics force fields, novel energy minimization techniques, docking algorithms, and support for cheminformatics.
Abstract: The Biochemical Algorithms Library (BALL) is a comprehensive rapid application development framework for structural bioinformatics. It provides an extensive C++ class library of data structures and algorithms for molecular modeling and structural bioinformatics. Using BALL as a programming toolbox does not only allow to greatly reduce application development times but also helps in ensuring stability and correctness by avoiding the error-prone reimplementation of complex algorithms and replacing them with calls into the library that has been well-tested by a large number of developers. In the ten years since its original publication, BALL has seen a substantial increase in functionality and numerous other improvements. Here, we discuss BALL's current functionality and highlight the key additions and improvements: support for additional file formats, molecular edit-functionality, new molecular mechanics force fields, novel energy minimization techniques, docking algorithms, and support for cheminformatics. BALL is available for all major operating systems, including Linux, Windows, and MacOS X. It is available free of charge under the Lesser GNU Public License (LPGL). Parts of the code are distributed under the GNU Public License (GPL). BALL is available as source code and binary packages from the project web site at http://www.ball-project.org
. Recently, it has been accepted into the debian project; integration into further distributions is currently pursued.
67 citations
TL;DR: Evidence is provided that blood-based tests open new avenues for the early diagnosis of lung cancer and lung cancer patients could be seprated from patients with other non-tumor lung diseases by a newly developed computer aided image analysis procedure.
Abstract: Background: Lung cancer is a very frequent and lethal tumor with an identifiable risk population. Cytological analysis and chest X-ray failed to reduce mortality, and CT screenings are still controversially discussed. Recent studies provided first evidence for the potential usefulness of autoantigens as markers for lung cancer. Methods: We used extended panels of arrayed antigens and determined autoantibody signatures of sera from patients with different kinds of lung cancer, different common non-tumor lung pathologies, and controls without any lung disease by a newly developed computer aided image analysis procedure. The resulting signatures were classified using linear kernel Support Vector Machines and 10-fold cross-validation. Results: The novel approach allowed for discriminating lung cancer patients from controls without any lung disease with a specificity of 97.0%, a sensitivity of 97.9%, and an accuracy of 97.6%. The classification of stage IA/IB tumors and controls yielded a specificity of 97.6%, a sensitivity of 75.9%, and an accuracy of 92.9%. The discrimination of lung cancer patients from patients with non-tumor lung pathologies reached an accuracy of 88.5%. Conclusion: We were able to separate lung cancer patients from subjects without any lung disease with high accuracy. Furthermore, lung cancer patients could be seprated from patients with other non-tumor lung diseases. These results provide clear evidence that blood-based tests open new avenues for the early diagnosis of lung cancer.
39 citations
TL;DR: There is a significant longer survival time in glioblastoma patients that lack amplifications of either CDK4, CYP27B1, XRCC6BP1 (KUB3), or MDM2 and first evidence indicates that amplicon structures are largely maintained in recurrent tumors.
Abstract: There is limited knowledge on the in vivo behavior of amplified regions in human tumors First evidence indicates that amplicon structures are largely maintained in recurrent tumors Here, we investigated the fate of amplified regions in several independent cases of recurrent glioblastoma and the possible association of 12q13-21 amplifications and survival We analyzed 12q13-21 amplicon numbers and sizes in glioblastoma and their recurrences by array-CGH The majority of the 12q13-21 amplicons found in the original tumor are lost in the subsequent recurrence Likewise, the majority of the amplicons found in the first recurrence are lost in the second recurrence The remaining amplicons of recurrences often expanded or were maintained in size Because of re-emergences and de novo appearances of amplicons, however, the overall number of amplicons did not decrease in the recurrences Understanding genetic changes including gene amplifications in the development of tumor recurrences will contribute to rational therapeutic strategies for an improved patient survival We recognized a significant longer survival time in glioblastoma patients that lack amplifications of either CDK4, CYP27B1, XRCC6BP1 (KUB3), or MDM2
30 citations
19 Apr 2010
TL;DR: A very general and highly efficient approach for the accurate computation of molecular geometric properties, which is applicable to arbitrary molecular surface models, and relies on a high performance ray casting framework that can be easily adapted to the computation of further quantities of interest at interactive speed.
Abstract: Molecular geometric properties, such as volume, exposed surface area, and occurrence of internal cavities, are important inputs to many applications in molecular modeling. In this work we describe a very general and highly efficient approach for the accurate computation of such properties, which is applicable to arbitrary molecular surface models. The technique relies on a high performance ray casting framework that can be easily adapted to the computation of further quantities of interest at interactive speed, even for huge models.
18 citations
TL;DR: Application of the two approaches to the proteome analysis of proteins extracted from a tumor tissue revealed that the BU method identified more proteins while STD analysis offered higher sequence coverage, and a high degree of "pseudo-orthogonality" of protein and peptide separation by IP-RPC in both separation dimensions.
18 citations
TL;DR: The Roche Cancer Genome Database (RCGDB), a freely available biological information system integrating different kinds of mutation data, is developed, the first comprehensive integration of disparate cancer genome data like single nucleotide variants, singleucleotide polymorphisms, and chromosomal aberrations.
Abstract: Sequence variations are being studied for a better understanding of the mechanism and development of cancer as a mutation-driven disease. The systematic sequencing of genes in tumors and technological advances in high-throughput techniques combined with efficient data acquisition methods have resulted in an explosion of available cancer genome-related data. Despite the technological progress and increase of data, improvements in the application area, for example, drug target discovery, have failed to keep pace with increased research and development spending. One reason for this discrepancy is the ever increasing number of databases and the absence of a unified access to the mutation data. Currently, researchers typically have to browse several, often highly specialized databases to obtain the required information. A more complete understanding of relations and dependencies between mutations and cancer, however, requires the availability of an efficient integrative cancer genome information system. To facilitate this, we developed the Roche Cancer Genome Database (RCGDB), a freely available biological information system integrating different kinds of mutation data. The database is the first comprehensive integration of disparate cancer genome data like single nucleotide variants, single nucleotide polymorphisms, and chromosomal aberrations (CGH and FISH). RCGDB is freely accessible via a Google-like Web interface at http://rcgdb.bioinf.uni-sb.de/MutomeWeb/.
17 citations
26 Jul 2010
TL;DR: This work demonstrates how real-time ray tracing integrated into a molecular modelling and visualization tool allows for better understanding of the structural arrangement of biomolecules and natural creation of publication-quality images in real- time.
Abstract: Molecular visualization is one of the cornerstones in structural bioinformatics and related fields. Today, rasterization is typically used for the interactive display of molecular scenes, while ray tracing aims at generating high-quality images, taking typically minutes to hours to generate and requiring the usage of an external off-line program. Recently, real-time ray tracing evolved to combine the interactivity of rasterization-based approaches with the superb image quality of ray tracing techniques. We demonstrate how real-time ray tracing integrated into a molecular modelling and visualization tool allows for better understanding of the structural arrangement of biomolecules and natural creation of publication-quality images in real-time. However, unlike most approaches, our technique naturaly integrates into the full-featured molecular modelling and visualization tool BALLView, seamlessly extending a standard workflow with interactive high-quality rendering.
17 citations
TL;DR: Die visuelle Analytik biologischer Daten hat erst vor kurzem auf den Information-Visualizationund Visual-Analytics-Konferenzen Beachtung gefunden, das Ziel, die komplexen experimentellen Daten in Wissen umzusetzen.
Abstract: Einleitung Biologische Daten sind heterogen, sehr komplex und oft sehr gros. Eine angemessene Visualisierung leistet hierbei einen entscheidenden Beitrag zum Verstandnis der Daten. Die Visualisierung biologischer Daten spielt daher auch eine zentrale Rolle in der Bioinformatik. Hier reichen die Anwendungen von der Visualisierung einzelner Proteine oder ganzer Genome, von Familien vonGenen, evolutionaren Verwandtschaftsverhaltnissen, makromolekularer Strukturen, mikroskopischer Bilddaten bis hin zur Darstellung von metabolischen oder regulatorischen Netzwerken und systembiologischer Daten (siehe Abb. 1 fur einige Beispiele). Aufgrund der zunehmenden Komplexitat und Verbundenheit biologischer Daten (man denke hier insbesondere an systembiologische Daten) ist eine integrative sowie standardisierte Visualisierung und die Entwicklung leistungsstarker und benutzerfreundlicher Werkzeuge von wachsender Bedeutung. Eine zunehmend grose Rolle spielen dabei Werkzeuge, die zudem das Paradigma der visuellen Analytik (engl. ,,visual analytics“) verfolgen. Grundsatzlich integriert die visuelle Analytik Visualisierung, Datenanalyse und Interaktion durch den Menschen. Bei biologischen Daten hat der Einsatz der visuellen Analytik daruber hinaus das Ziel, die komplexen experimentellen Daten in Wissen umzusetzen. Forschern soll ein System zur Verfugung gestellt werden, das es erlaubt, Einsichten in biologische Prozesse in Zellen, Geweben und schlieslich Organismen zu gewinnen sowie eine Modellierung biologischer Systeme vorzunehmen. Die visuelle Analytik biologischer Daten hat erst vor kurzem auf den Information-Visualizationund Visual-Analytics-Konferenzen Beachtung gefunden. Einige auch in wissenschaftlichen Zeitschriften publizierte Artikel sind Themen wie Clustering von Expressionsdaten [17], der GenomAssemblierung [18] oder der Bestimmung von Funktionen von Genen in neu sequenzierten Genomen [20] gewidmet. Die diesjahrige IEEE VAST Challenge stand ganz im Zeichen einer biologischen Fragestellung. Im folgenden Artikel mochten wir insbesondere auf drei der oben genannten Teilgebiete der Visualisierung biologischer Daten genauer eingehen: die visuelle Analytik von Genexpressionsdaten, die Visualisierung biologischer Netzwerke sowie die inhaltsbasierte Suche in zellbiologischen Bilddatenbanken.