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  • 1
    In: Bioinformatics, 2015, Vol. 31(19), pp.3231-3233
    Description: Summary: With the widespread availability of high-throughput experimental technologies it has become possible to study hundreds to thousands of cellular factors simultaneously, such as coding- or non-coding mRNA or protein concentrations. Still, extracting information about the underlying regulatory or signaling interactions from these data remains a difficult challenge. We present a flexible approach towards network inference based on linear programming. Our method reconstructs the interactions of factors from a combination of perturbation/non-perturbation and steady-state/time-series data. We show both on simulated and real data that our methods are able to reconstruct the underlying networks fast and efficiently, thus shedding new light on biological processes and, in particular, into disease’s mechanisms of action. We have implemented the approach as an R package available through bioconductor. Availability and implementation: This R package is freely available under the Gnu Public License (GPL-3) from bioconductor.org ( http://bioconductor.org/packages/release/bioc/html/lpNet.html ) and is compatible with most operating systems (Windows, Linux, Mac OS) and hardware architectures. Contact: bettina.knapp@helmholtz-muenchen.de Supplementary information: Supplementary data are available at Bioinformatics online.
    Keywords: Biology;
    ISSN: 1367-4803
    E-ISSN: 1460-2059
    E-ISSN: 13674811
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  • 2
    In: Journal of Antimicrobial Chemotherapy, 2014, Vol. 69(10), pp.2809-2818
    Description: OBJECTIVES: The rapid early-phase decay of plasma HIV-1 RNA during integrase inhibitor-based therapy is not fully understood. The accumulation of biologically active episomal HIV-1 cDNAs, following aborted integration, could contribute to antiviral potency in vivo.METHODS: This prospective, controlled clinical observation study explored raltegravir's impact on the dynamics of HIV-1 RNA in plasma, and concentrations of total HIV-1 cDNA, episomal 2-long terminal repeat (LTR) circles and HIV-1 integrants in peripheral blood mononuclear cells (PBMC). Individuals starting therapy with two nucleoside reverse transcriptase inhibitors plus either raltegravir (raltegravir group; n = 10 patients) or boosted protease inhibitor/non-nucleoside reverse transcriptase inhibitor (control group; n = 10 patients) were followed for 48 weeks.RESULTS: Suppression of HIV-1 RNA (〈50 copies/mL) was reached earlier (5/10 versus 0/10 at week 4; 8/10 versus 4/10 at week 12) on raltegravir. Significant total HIV-1 cDNA reductions in PBMC were reached by day 99 and persisted until day 330, with median factors of decrease of 7.2 and 8.9, respectively. Broad inter-individual variations, yet no treatment-associated differences, were noted for HIV-1 cDNA concentrations. Despite reductions in HIV-1 RNA (∼3 log) and total HIV-1 cDNA (∼1 log), concentrations of integrants and 2-LTR circles remained largely unchanged.CONCLUSIONS: These results extend the previously reported early benefit of raltegravir on the decline of plasma viraemia to treatment-naive patients. The modest treatment-associated, yet group-independent, decline in total HIV-1 cDNA load and the lack of significant changes in integrated and episomal HIV-1 cDNA suggest that most integrated DNA is archival and targeting of HIV reservoirs other than PBMC may underlie beneficial effects of raltegravir.
    Keywords: Virus Load ; Decay ; Slope ; Antiretroviral Therapy ; Integrase Inhibitor ; Viral Dynamics ; Episomal Dna ; 2 - Ltr Circles
    ISSN: 0305-7453
    E-ISSN: 1460-2091
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  • 3
    In: Interactive CardioVascular and Thoracic Surgery, 2015, Vol. 21(2), pp.211-217
    Description: Despite the introduction of new target drugs to treat pulmonary metastatic renal cell carcinoma (mRCC), complete surgical resection still generates significantly longer survival. We analysed the survival outcome for patients with pulmonary mRCC after extended laser metastasectomy with up to 110 metastases and systematic lymphadenectomy to assess the utility and value of laser resection in the respective patient groups even with high number of metastases. Between 1996 and 2012, 237 patients (150 men, 87 women) underwent curative intended pulmonary laser metastasectomy of mRCC. A total of 2996 metastases (range: 1-110) were resected. Kaplan-Meier analysis was performed to assess overall survival in all 237 patients and for sub-groups. Multivariate analysis of prognostic factors was performed using Cox regression models. Two hundred and eight patients with R0-resection (88%) had 5-year overall survival rate and median overall survival of 54% and 69 months, respectively, significantly better than 7% and 19 months in those with incomplete resections (log-rank P 〈 0.00001). A mean of 13 metastases per patient were resected. Five-year survival for patients with 1, 2-5, 6-9, 10-29 or 30-110 metastases resected was 62, 59, 60, 43 and 40%, respectively. In multivariate Cox-regression of all 237 patients, only completeness of resection (P 〈 0.0001) and number of metastases (P = 0.0029) were independent factors. If complete resection is achieved, laser resection can remove even high numbers of metastases with considerable and comparable long-term survival known from previous reports. This tissue-saving technique allows repeated resections in case of recurrence.
    Keywords: Renal Cell Carcinoma ; Pulmonary Metastasectomy ; 1318 Nm Laser ; Survival Analysis
    ISSN: 1569-9293
    E-ISSN: 1569-9285
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  • 4
    In: Bioinformatics, 2002, Vol.18(10), pp.1340-1349
    Description: Motivation: DNA arrays are a very useful tool to quickly identify biological agents present in some given sample, e.g. to identify viruses causing disease, for quality control in the food industry, or to determine bacteria contaminating drinking water. The selection of specific oligos to attach to the array surface is a relevant problem in the experiment design process. Given a set S of genomic sequences (the target sequences), the task is to find at least one oligonucleotide, called probe, for each sequence in S . This probe will be attached to the array surface, and must be chosen in a way that it will not hybridize to any other sequence but the intended target. Furthermore, all probes on the array must hybridize to their intended targets under the same reaction conditions, most importantly at the temperature T at which the experiment is conducted. Results: We present an efficient algorithm for the probe design problem. Melting temperatures are calculated for all possible probetarget interactions using an extended nearest-neighbor model, allowing for both non-WatsonCrick base-pairing and unpaired bases within a duplex. To compute temperatures efficiently, a combination of suffix trees and dynamic programming based alignment algorithms is introduced. Additional filtering steps during preprocessing increase the speed of the computation. The practicability of the algorithms is demonstrated by two case studies: The identification of HIV-1 subtypes, and of 28S rDNA sequences from 400 organisms. Availability: The software is available on request. Contact: kaderali@zpr.uni-koeln.de
    Keywords: Biology;
    ISSN: 1367-4803
    E-ISSN: 1460-2059
    E-ISSN: 13674811
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  • 5
    Language: English
    In: Bioinformatics (Oxford, England), 15 September 2010, Vol.26(18), pp.i653-8
    Description: Detecting human proteins that are involved in virus entry and replication is facilitated by modern high-throughput RNAi screening technology. However, hit lists from different laboratories have shown only little consistency. This may be caused by not only experimental discrepancies, but also not fully explored possibilities of the data analysis. We wanted to improve reliability of such screens by combining a population analysis of infected cells with an established dye intensity readout. Viral infection is mainly spread by cell-cell contacts and clustering of infected cells can be observed during spreading of the infection in situ and in vivo. We employed this clustering feature to define knockdowns which harm viral infection efficiency of human Hepatitis C Virus. Images of knocked down cells for 719 human kinase genes were analyzed with an established point pattern analysis method (Ripley's K-function) to detect knockdowns in which virally infected cells did not show any clustering and therefore were hindered to spread their infection to their neighboring cells. The results were compared with a statistical analysis using a common intensity readout of the GFP-expressing viruses and a luciferase-based secondary screen yielding five promising host factors which may suit as potential targets for drug therapy. We report of an alternative method for high-throughput imaging methods to detect host factors being relevant for the infection efficiency of viruses. The method is generic and has the potential to be used for a large variety of different viruses and treatments being screened by imaging techniques.
    Keywords: Image Processing, Computer-Assisted ; RNA Interference ; RNA, Small Interfering ; Virus Replication ; Biological Factors -- Analysis ; Hepacivirus -- Physiology
    ISSN: 13674803
    E-ISSN: 1367-4811
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  • 6
    In: Bioinformatics, 2005, Vol.21(10), pp.2375-2382
    Description: Motivation: In a wide range of experimental techniques in biology, there is a need for an efficient method to calculate the melting temperature of pairings of two single DNA strands. Avoiding cross-hybridization when choosing primers for the polymerase chain reaction or selecting probes for large-scale DNA assays are examples where the exact determination of melting temperatures is important. Beyond being exact, the method has to be efficient, as these techniques often require the simultaneous calculation of melting temperatures of up to millions of possible pairings. The problem is to simultaneously determine the most stable alignment of two sequences, including potential loops and bulges, and calculate the corresponding melting temperature. Results: As the melting temperature can be expressed as a fraction in terms of enthalpy and entropy differences of the corresponding annealing reaction, we propose to use a fractional programming algorithm, the Dinkelbach algorithm, to solve the problem. To calculate the required differences of enthalpy and entropy, the Nearest Neighbor model is applied. Using this model, the substeps of the Dinkelbach algorithm in our problem setting turn out to be calculations of alignments which optimize an additive score function. Thus, the usual dynamic programming techniques can be applied. The result is an efficient algorithm to determine melting temperatures of two DNA strands, suitable for large-scale applications such as primer or probe design. Availability: The software is available for academic purposes from the authors. A web interface is provided at http://www.zaik.uni-koeln.de/bioinformatik/fptm.html . Contact: kaderali@zpr.uni-koeln.de
    Keywords: Biology;
    ISSN: 1367-4803
    E-ISSN: 1460-2059
    E-ISSN: 13674811
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  • 7
    In: Bioinformatics, 2009, Vol. 25(5), pp.678-679
    Description: Summary: We present RNAither, a package for the free statistical environment R which performs an analysis of high-throughput RNA interference (RNAi) knock-down experiments, generating lists of relevant genes and pathways out of raw experimental data. The library provides a quality assessment of the signal intensities, as well as a broad range of options for data normalization, different statistical tests for the identification of significant siRNAs, and a significance analysis of the biological processes involving corresponding genes. The results of the analysis are presented as a set of HTML pages. Additionally, all values and plots are available as either text files or pdf and png files. 〈p〉〈bold〉Availability:〈/bold〉 〈ext-link ext-link-type="uri" xlink_href="http://bioconductor.org/"〉http://bioconductor.org/〈/ext-link〉〈/p〉 〈p〉〈bold〉Contact:〈/bold〉 〈email〉RNAither@gmx.de〈/email〉〈/p〉
    Keywords: Genes ; Quality Assessment ; Ribonucleic Acids ; Lists ; Hypertext Markup Language ; Biological ; Texts ; Contact ; Life and Medical Sciences (Ci) ; Article;
    ISSN: 1367-4803
    E-ISSN: 1460-2059
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  • 8
    In: Bioinformatics, 2006, Vol.22(12), pp.1495-1502
    Description: Motivation: DNA microarrays allow the simultaneous measurement of thousands of gene expression levels in any given patient sample. Gene expression data have been shown to correlate with survival in several cancers, however, analysis of the data is difficult, since typically at most a few hundred patients are available, resulting in severely underdetermined regression or classification models. Several approaches exist to classify patients in different risk classes, however, relatively little has been done with respect to the prediction of actual survival times. We introduce CASPAR, a novel method to predict true survival times for the individual patient based on microarray measurements. CASPAR is based on a multivariate Cox regression model that is embedded in a Bayesian framework. A hierarchical prior distribution on the regression parameters is specifically designed to deal with high dimensionality (large number of genes) and low sample size settings, that are typical for microarray measurements. This enables CASPAR to automatically select small, most informative subsets of genes for prediction. Results: Validity of the method is demonstrated on two publicly available datasets on diffuse large B-cell lymphoma (DLBCL) and on adenocarcinoma of the lung. The method successfully identifies long and short survivors, with high sensitivity and specificity. We compare our method with two alternative methods from the literature, demonstrating superior results of our approach. In addition, we show that CASPAR can further refine predictions made using clinical scoring systems such as the International Prognostic Index (IPI) for DLBCL and clinical staging for lung cancer, thus providing an additional tool for the clinician. An analysis of the genes identified confirms previously published results, and furthermore, new candidate genes correlated with survival are identified. Availability: The software is available upon request from the authors. Contact: kaderali@zpr.uni-koeln.de Supplementary information: http://www.zaik.uni-koeln.de/bioinformatik/caspar.html
    Keywords: Biology;
    ISSN: 1367-4803
    E-ISSN: 1460-2059
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  • 9
    In: Bioinformatics, 2009, Vol. 25(17), pp.2229-2235
    Description: Motivation: The reconstruction of signaling pathways from gene knockdown data is a novel research field enabled by developments in RNAi screening technology. However, while RNA interference is a powerful technique to identify genes related to a phenotype of interest, their placement in the corresponding pathways remains a challenging problem. Difficulties are aggravated if not all pathway components can be observed after each knockdown, but readouts are only available for a small subset. We are then facing the problem of reconstructing a network from incomplete data. We infer pathway topologies from gene knockdown data using Bayesian networks with probabilistic Boolean threshold functions. To deal with the problem of underdetermined network parameters, we employ a Bayesian learning approach, in which we can integrate arbitrary prior information on the network under consideration. Missing observations are integrated out. We compute the exact likelihood function for smaller networks, and use an approximation to evaluate the likelihood for larger networks. The posterior distribution is evaluated using mode hopping Markov chain Monte Carlo. Distributions over topologies and parameters can then be used to design additional experiments. We evaluate our approach on a small artificial dataset, and present inference results on RNAi data from the Jak/Stat pathway in a human hepatoma cell line. Software is available on request. 〈p〉〈bold〉Contact:〈/bold〉 〈email〉lars.kaderali@bioquant.uni-heidelberg.de〈/email〉〈/p〉 are available at online.
    Keywords: Biology;
    ISSN: 1367-4803
    E-ISSN: 1460-2059
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  • 10
    Language: English
    In: Nucleic acids research, 15 March 2003, Vol.31(6), pp.1796-802
    Description: Single-nucleotide polymorphism (SNP) analysis is a powerful tool for mapping and diagnosing disease-related alleles. Mutation analysis by polymerase-mediated single-base primer extension (minisequencing) can be massively parallelized using DNA microchips or flow cytometry with microspheres as solid support. By adding a unique oligonucleotide tag to the 5' end of the minisequencing primer and attaching the complementary antitag to the array or bead surface, the assay can be 'demultiplexed'. Such high-throughput scoring of SNPs requires a high level of primer multiplexing in order to analyze multiple loci in one assay, thus enabling inexpensive and fast polymorphism scoring. We present a computer program to automate the design process for the assay. Oligonucleotide primers for the reaction are automatically selected by the software, a unique DNA tag/antitag system is generated, and the pairing of primers and DNA tags is automatically done in a way to avoid any crossreactivity. We report results on a 45-plex genotyping assay, indicating that minisequencing can be adapted to be a powerful tool for high-throughput, massively parallel genotyping. The software is available to academic users on request.
    Keywords: Software ; DNA Primers -- Genetics ; Polymorphism, Single Nucleotide -- Genetics
    E-ISSN: 1362-4962
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