Kooperativer Bibliotheksverbund

Berlin Brandenburg

and
and

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
Type of Medium
Language
Year
  • 1
    Book
    Book
    United Kingdom: Packt Publishing
    Language: English
    Description: This book is an easy-to-follow, stepwise guide to handle real life Bioinformatics problems. Each recipe comes with a detailed explanation to the solution steps. A...
    ISBN: 1783283130
    ISBN: 9781783283132
    Source: Dawsonera
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 2
    In: PLoS ONE, 2013, Vol.8(6)
    Description: Inferring regulatory networks from experimental data via probabilistic graphical models is a popular framework to gain insights into biological systems. However, the inherent noise in experimental data coupled with a limited sample size reduces the performance of network reverse engineering. Prior knowledge from existing sources of biological information can address this low signal to noise problem by biasing the network inference towards biologically plausible network structures. Although integrating various sources of information is desirable, their heterogeneous nature makes this task challenging. We propose two computational methods to incorporate various information sources into a probabilistic consensus structure prior to be used in graphical model inference. Our first model, called Latent Factor Model (LFM), assumes a high degree of correlation among external information sources and reconstructs a hidden variable as a common source in a Bayesian manner. The second model, a Noisy-OR, picks up the strongest support for an interaction among information sources in a probabilistic fashion. Our extensive computational studies on KEGG signaling pathways as well as on gene expression data from breast cancer and yeast heat shock response reveal that both approaches can significantly enhance the reconstruction accuracy of Bayesian Networks compared to other competing methods as well as to the situation without any prior. Our framework allows for using diverse information sources, like pathway databases, GO terms and protein domain data, etc. and is flexible enough to integrate new sources, if available.
    Keywords: Research Article ; Biology ; Computer Science
    E-ISSN: 1932-6203
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 3
    Language: English
    In: Microbiome, 24 September 2015, Vol.3, pp.41
    Description: The human intestinal microbiota changes from being sparsely populated and variable to possessing a mature, adult-like stable microbiome during the first 2 years of life. This assembly process of the microbiota can lead to either negative or positive effects on health, depending on the colonization sequence and diet. An integrative study on the diet, the microbiota, and genomic activity at the transcriptomic level may give an insight into the role of diet in shaping the human/microbiome relationship. This study aims at better understanding the effects of microbial community and feeding mode (breast-fed and formula-fed) on the immune system, by comparing intestinal metagenomic and transcriptomic data from breast-fed and formula-fed babies. We re-analyzed a published metagenomics and host gene expression dataset from a systems biology perspective. Our results show that breast-fed samples co-express genes associated with immunological, metabolic, and biosynthetic activities. The diversity of the microbiota is higher in formula-fed than breast-fed infants, potentially reflecting the weaker dependence of infants on maternal microbiome. We mapped the microbial composition and the expression patterns for host systems and studied their relationship from a systems biology perspective, focusing on the differences. Our findings revealed that there is co-expression of more genes in breast-fed samples but lower microbial diversity compared to formula-fed. Applying network-based systems biology approach via enrichment of microbial species with host genes revealed the novel key relationships of the microbiota with immune and metabolic activity. This was supported statistically by data and literature.
    Keywords: Breast Feeding ; Immune System -- Physiology ; Milk, Human -- Immunology
    ISSN: 2049-2618
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 4
    In: Bioinformatics, 2011, Vol. 27(2), pp.238-244
    Description: Motivation: Targeted interventions in combination with the measurement of secondary effects can be used to computationally reverse engineer features of upstream non-transcriptional signaling cascades. Nested effect models (NEMs) have been introduced as a statistical approach to estimate the upstream signal flow from downstream nested subset structure of perturbation effects. The method was substantially extended later on by several authors and successfully applied to various datasets. The connection of NEMs to Bayesian Networks and factor graph models has been highlighted. Here, we introduce a computationally attractive extension of NEMs that enables the analysis of perturbation time series data, hence allowing to discriminate between direct and indirect signaling and to resolve feedback loops. The implementation (R and C) is part of the Supplement to this article. 〈p〉〈bold〉Contact:〈/bold〉 〈email〉frohlich@bit.uni-bonn.de〈/email〉〈/p〉 are available at online.
    Keywords: Nanoelectromechanical Systems ; Computation ; Mathematical Models ; Upstream ; Perturbation Methods ; Feedback ; Bioinformatics ; Cascades ; Life and Medical Sciences (Ci);
    ISSN: 1367-4803
    E-ISSN: 1460-2059
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 5
    In: Bioinformatics, 2013, Vol. 29(12), pp.1534-1540
    Description: Motivation: As RNA interference is becoming a standard method for targeted gene perturbation, computational approaches to reverse engineer parts of biological networks based on measurable effects of RNAi become increasingly relevant. The vast majority of these methods use gene expression data, but little attention has been paid so far to other data types. : Here we present a method, which can infer gene networks from high-dimensional phenotypic perturbation effects on single cells recorded by time-lapse microscopy. We use data from the Mitocheck project to extract multiple shape, intensity and texture features at each frame. Features from different cells and movies are then aligned along the cell cycle time. Subsequently we use Dynamic Nested Effects Models (dynoNEMs) to estimate parts of the network structure between perturbed genes via a Markov Chain Monte Carlo approach. Our simulation results indicate a high reconstruction quality of this method. A reconstruction based on 22 gene knock downs yielded a network, where all edges could be explained via the biological literature. : The implementation of dynoNEMs is part of the Bioconductor R-package . 〈p〉〈bold〉Contact:〈/bold〉 〈email〉frohlich@bit.uni-bonn.de〈/email〉〈/p〉 are available at online.
    Keywords: Gene Expression ; Computer Programs ; Learning ; Data Processing ; Cell Cycle ; Microscopy ; RNA-Mediated Interference ; Bioinformatics ; Computer Applications ; Imaging ; Internet ; Bioinformatics & Computer Applications ; Methods;
    ISSN: 1367-4803
    E-ISSN: 1460-2059
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 6
    Book
    Book
    Birmingham : Packt Publishing
    Language: English
    Description: In Detail Bioinformatics is an interdisciplinary field that develops and improves upon the methods for storing, retrieving, organizing, and analyzing biological data. R is the primary language used for handling most of the data analysis work done in the domain of bioinformatics. Bioinformatics with R...
    Keywords: Bioinformatics ; Data Visualization ; Math & Science ; Bioinformatics ; Biology;
    ISBN: 9781783283132
    E-ISSN: 97817832
    Source: VLeBooks
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 7
    In: Scientific Reports, 2015, Vol.5
    Description: Coexisting bacteria form various microbial communities in human body parts. In these ecosystems they interact in various ways and the properties of the interaction network can be related to the stability and functional diversity of the local bacterial community. In this study, we analyze the interaction network among bacterial OTUs in 11 locations of the human body. These belong to two major groups. One is the digestive system and the other is the female genital tract. In each local ecosystem we determine the key species, both the ones being in key positions in the interaction network and the ones that dominate by frequency. Beyond identifying the key players and discussing their biological relevance, we also quantify and compare the properties of the 11 networks. The interaction networks of the female genital system and the digestive system show totally different architecture. Both the topological properties and the identity of the key groups differ. Key groups represent four phyla of prokaryotes. Some groups appear in key positions in several locations, while others are assigned only to a single body part. The key groups of the digestive and the genital tracts are totally different.
    Keywords: Bacteria -- Isolation & Purification ; Gastrointestinal Tract -- Microbiology ; Genitalia, Female -- Microbiology;
    ISSN: 20452322
    E-ISSN: 20452322
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 8
    In: Scientific Reports, 2016, Vol.6
    Description: Lung cancers globally account for 12% of new cancer cases, 85% of these being Non Small Cell Lung Cancer (NSCLC). Therapies like erlotinib target the key player EGFR, which is mutated in about 10% of lung adenocarcinoma. However, drug insensitivity and resistance caused by second mutations in the EGFR or aberrant bypass signaling have evolved as a major challenge in controlling these tumors. Recently, AMPK activation was proposed to sensitize NSCLC cells against erlotinib treatment. However, the underlying mechanism is largely unknown. In this work we aim to unravel the interplay between 20 proteins that were previously associated with EGFR signaling and erlotinib drug sensitivity. The inferred network shows a high level of agreement with protein-protein interactions reported in STRING and HIPPIE databases. It is further experimentally validated with protein measurements. Moreover, predictions derived from our network model fairly agree with somatic mutations and gene expression data from primary lung adenocarcinoma. Altogether our results support the role of AMPK in EGFR signaling and drug sensitivity.
    Keywords: Biology;
    ISSN: 20452322
    E-ISSN: 20452322
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 9
    Description: GO enrichment tables for human genes involved in the system. (CSV 79 kb)...
    Keywords: Space Science ; Medicine ; Microbiology ; Biological Sciences Not Elsewhere Classified ; Information Systems Not Elsewhere Classified ; Developmental Biology ; Infectious Diseases
    Source: DataCite
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 10
    Description: Microbial abundance tables. (CSV 14 kb)...
    Keywords: Space Science ; Microbiology ; Ecology ; Biological Sciences Not Elsewhere Classified ; Developmental Biology
    Source: DataCite
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. Further information can be found on the KOBV privacy pages