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Corrigendum: FOXM1 mediates Dox resistance in breast cancer by enhancing DNA repair

Carcinogenesis 2019年第7期40卷 936页

作者： Yun-Yong Park Sung Yun Jung Nicholas B Jennings Cristian Rodriguez-Aguayo Guang Peng Se-Ra Lee Sang Bae Kim Kyounghyun Kim Sun-Hee Leem Shiaw-Yih Lin Gabriel Lopez-Berestein Anil K Sood Ju-Seog Lee Department of Systems Biology The University of Texas MD Anderson Cancer Center Houston TX USA. Department of Biochemistry and Molecular Biology Baylor College of Medicine Houston TX USA. Department of Gynecologic Oncology Houston TX USA. Department of Experimental Therapeutics The University of Texas MD Anderson Cancer Center Houston TX USA. Department of Biology and Biomedical Science Dong-A University Busan Korea. Institute of Biosciences and Technology Texas A&M University Health Science Center Houston TX USA. Deparment of Cancer Biology The University of Texas MD Anderson Cancer Center Houston TX USA. Center for RNA Interference and Non-Coding RNA The University of Texas MD Anderson Cancer Center Houston TX USA.

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Identification of valid reference genes for microrna expression studies in a hepatitis B virus replicating liver cell line

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BMC Research Notes 2016年第1期9卷 1-7页

作者： Jacobsen, Kari Stougaard Nielsen, Kirstine Overgaard Winther, Thilde Nordmann Glebe, Dieter Pociot, Flemming Hogh, Birthe Department of Paediatrics Hvidovre Hospital University of Copenhagen Copenhagen Denmark Department of Paediatrics Center for Non-Coding RNA in Technology and Health Herlev Hospital University of Copenhagen Copenhagen Denmark Institute of Medical Virology National Reference Center for Hepatitis B and D Viruses German Center for Infection Research Biomedical Research Center Seltersberg Justus-Liebig University Giessen Giessen Germany

Background: Micrornas are regulatory molecules and suggested as non-invasive biomarkers for molecular diagnostics and prognostics. Altered expression levels of specific micrornas are associated with hepatitis B virus infection and hepatocellular carcinoma. We previously identified differentially expressed micrornas with liver-specific target genes in plasma from children with chronic hepatitis B. To further understand the biological role of these micrornas in the pathogenesis of chronic hepatitis B, we have used the human liver cell line HepG2, with and without HBV replication, after transfection of hepatitis B virus expression vectors. RT-qPCR is the preferred method for microrna studies, and a careful normalisation strategy, verifying the optimal set of reference genes, is decisive for correctly evaluating microrna expression levels. The aim of this study was to provide valid reference genes for the human HCC-derived cell line HepG2. Results: A panel of 739 micrornas was screened to identify the most stably expressed micrornas, followed by a PubMed search identifying micrornas previously used as reference genes. Sixteen candidate reference genes were validated by RT-qPCR. Reference gene stabilities were calculated first by standard deviations of ΔCt values and then by geNorm and NormFinder analyses, taking into account the amplification efficiency of each microrna primer set. The optimal set of reference genes was verified by a target analysis using RT-qPCR on miR-215-5p. Conclusion: We identified miR-24-3p, miR-151a-5p, and miR-425-5p as the most valid combination of reference genes for microrna RT-qPCR studies in our hepatitis B virus replicating HepG2 cell model. © 2016 Jacobsen et al.

关键词： Hepatitis B virus microrna Normalisation Reference genes RT-qPCR

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An intermediate level of abstraction for computational systems chemistry

arXiv

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arXiv 2017年

作者： Andersen, Jakob L. Flamm, Christoph Merkle, Daniel Stadler, Peter F. Earth-Life Science Institute Tokyo Institute of Technology Tokyo152-8550 Japan Department of Mathematics and Computer Science University of Southern Denmark Denmark Research Network Chemistry Meets Microbiology University of Vienna WienA-1090 Austria Institute for Theoretical Chemistry University of Vienna Austria Department of Computer Science University of Leipzig Germany Max Planck Institute for Mathematics in the Sciences Leipzig Germany Fraunhofer Institute for Cell Therapy and Immunology Leipzig Germany Center for non-coding RNA in Technology Health University of Copenhagen Denmark Santa Fe Institute Santa Fe United States

Computational techniques are required for narrowing down the vast space of possibilities to plausible prebiotic scenarios, since precise information on the molecular composition, the dominant reaction chemistry, and the conditions for that era are scarce. The exploration of large chemical reaction networks is a central aspect in this endeavour. While quantum chemical methods can accurately predict the structures and reactivities of small molecules, they are not efficient enough to cope with large-scale reaction systems. The formalization of chemical reactions as graph grammars provides a generative system, well grounded in category theory, at the right level of abstraction for the analysis of large and complex reaction networks. An extension of the basic formalism into the realm of integer hyperflows allows for the identification of complex reaction patterns, such as auto-catalysis, in large reaction networks using optimization techniques. Copyright © 2017, The Authors. All rights reserved.

关键词： Formal languages

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Quality Assessment of Domesticated Animal Genome Assemblies

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Bioinformatics and Biology Insights 2015年第Suppl 4期9S4卷 49-58页

作者： Seemann, Stefan E. Anthon, Christian Palasca, Oana Gorodkin, Jan Center for non-coding RNA in Technology and Health Department of Veterinary Clinical and Animal Sciences University of Copenhagen København Denmark

The era of high-throughput sequencing has made it relatively simple to sequence genomes and transcriptomes of individuals from many species. In order to analyze the resulting sequencing data, high-quality reference genome assemblies are required. However, this is still a major challenge, and many domesticated animal genomes still need to be sequenced deeper in order to produce high-quality assemblies. In the meanwhile, ironically, the extent to which rna seq and other next-generation data is produced frequently far exceeds that of the genomic sequence. Furthermore, basic comparative analysis is often affected by the lack of genomic sequence. Herein, we quantify the quality of the genome assemblies of 20 domesticated animals and related species by assessing a range of measurable parameters, and we show that there is a positive correlation between the fraction of mappable reads from rnaseq data and genome assembly quality. We rank the genomes by their assembly quality and discuss the implications for genotype analyses. © 2015, © 2015 SAGE Publications.

关键词： assembly quality domesticated animals genome assembly

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OUGENE： a disease associated over-expressed and under-expressed gene database

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Science Bulletin 2016年第10期61卷 752-754页

作者： Xiaoyong Pan Hong-Bin Shen Section for Animal Genetics Bioinformatics and Breeding Center for Non-Coding RNA in Technology and Health University of Copenhagen 1870 Frederiksberg Denmark Department of Disease Systems Biology Novo NordiskFoundation Center for Protein Research University ofCopenhagen 1870 Frederiksberg Denmark Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China

Gene over-expression or under-expression is closely associated with human diseases, which contributes to phenotypic variations and diversity. To our best knowledge, there is no single open specific resource available to provide the association information between gene over- or under-expression and various diseases. In this study, we presented a comprehensive disease-associated over- and under-expressed gene database （OUGene） based on our proposed text mining pipeline and several open curated databases. It contains total 41,269 unique associa- tions between 7,238 over- or under-expressed genes and 1,480 diseases, which are supported by 81,974 evidence sentences from 56,442 articles. The OUGene is compre- hensive and covers most important therapeutic areas. Meanwhile a new scoring system is designed to rank the associations based on benchmarking against hand-curated data. OUGene provides an easy-of-use web interface for researchers to analyze these data and visualize the associ- ated networks, which can give insights to the complex relationships between over- and under-expressed genes and diseases at a system level. It is available at ***. ***/bioinf/OUGene/.

关键词： Text mining Gene over- and under-expression Disease Database

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Chemical transformation motifs - Modelling pathways as integer hyperflows

arXiv

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arXiv 2017年

作者： Andersen, Jakob L. Flamm, Christoph Merkle, Daniel Stadler, Peter F. Earth-Life Science Institute Tokyo Institute of Technology Tokyo 152-8550 Japan Department of Mathematics and Computer Science University of Southern Denmark Odense M DK-5230 Denmark Research group Bioinformatics and Computational Biology Faculty of Computer Science University of Vienna Vienna 1090 Austria Institute for Theoretical Chemistry University of Vienna Wien 1090 Austria Halle-Jena-Leipzig and Competence Center for Scalable Data Services Solutions Dresden-Leipzig Leipzig Research Center for Civilization Diseases University of Leipzig Leipzig D-04107 Germany Max Planck Institute for Mathematics in the Sciences Leipzig D-04103 Germany Fraunhofer Institute for Cell Therapy and Immunology Leipzig D-04103 Germany Center for non-coding RNA in Technology and Health University of Copenhagen Frederiksberg C DK-1870 Denmark Santa Fe Institute 1399 Hyde Park Rd Santa Fe NM 87501 United States Research Network Chemistry Meets Microbiology University of Vienna Wien A-1090 Austria

We present an elaborate framework for formally modelling pathways in chemical reaction networks on a mechanistic level. Networks are modelled mathematically as directed multi-hypergraphs, with vertices corresponding to molecules and hyperedges to reactions. Pathways are modelled as integer hyperflows and we expand the network model by detailed routing constraints. In contrast to the more traditional approaches like Flux Balance Analysis or Elementary Mode analysis we insist on integer-valued flows. While this choice makes it necessary to solve possibly hard integer linear programs, it has the advantage that more detailed mechanistic questions can be formulated. It is thus possible to query networks for general transformation motifs, and to automatically enumerate optimal and near-optimal pathways. Similarities and differences between our work and traditional approaches in metabolic network analysis are discussed in detail. To demonstrate the applicability of the mathematical framework to real-life problems we first explore the design space of possible non-oxidative glycolysis pathways and show that recent manually designed pathways can be further optimised. We then use a model of sugar chemistry to investigate pathways in the autocatalytic formose process. A graph transformation-based approach is used to automatically generate the reaction networks of interest. Copyright © 2017, The Authors. All rights reserved.

关键词： Integer programming

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50 shades of rule composition from chemical reactions to higher levels of abstraction

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8738卷 115-135页

作者： Andersen, Jakob Lykke Flamm, Christoph Merkle, Daniel Stadler, Peter F. Department of Mathematics and Computer Science University of Southern Denmark Denmark Institute for Theoretical Chemistry University of Vienna Austria Bioinformatics Group Department of Computer Science and Interdisciplinary Center for Bioinformatics Leipzig Germany Max Planck Institute for Mathematics in the Sciences Leipzig Germany Fraunhofer Institute for Cell Therapy and Immunology Leipzig Germany Center for Non-coding RNA in Technology and Health University of Copenhagen Denmark Santa Fe Institute United States

ISBN: (纸本)9783319103976

Graph rewriting has been applied quite successfully to model chemical and biological systems at different levels of abstraction. A particularly powerful feature of rule-based models that are rigorously grounded in category theory, is, that they admit a well-defined notion of rule composition, hence, provide their users with an intrinsic mechanism for compressing trajectories and coarse grained representations of dynamical aspects. The same formal framework, however, also allows the detailed analysis of transitions in which the final and initial states are known, but the detailed stepwise mechanism remains hidden. To demonstrate the general principle we consider here how rule composition is used to determine accurate atom maps for complex enzyme reactions. This problem not only exemplifies the paradigm but is also of considerable practical importance for many down-stream analyses of metabolic networks and it is a necessary prerequisite for predicting atom traces for the analysis of isotope labelling experiments. © Springer International Publishing Switzerland 2014.

关键词： Biological systems

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Highlights from the 11th ISCB Student Council Symposium 2015. Dublin, Ireland. 10 July 2015

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BMC bioinformatics 2016年第3期17 Suppl 3卷 95页

作者： Katie Wilkins Mehedi Hassan Margherita Francescatto Jakob Jespersen R. Gonzalo Parra Bart Cuypers Dan DeBlasio Alexander Junge Anupama Jigisha Farzana Rahman Griet Laenen Sander Willems Lieven Thorrez Yves Moreau Nagarajan Raju Sonia Pankaj Chothani C. Ramakrishnan Masakazu Sekijima M. Michael Gromiha Paddy J Slator Nigel J Burroughs Przemysław Szałaj Zhonghui Tang Paul Michalski Oskar Luo Xingwang Li Yijun Ruan Dariusz Plewczynski Giulia Fiscon Emanuel Weitschek Massimo Ciccozzi Paola Bertolazzi Giovanni Felici Pieter Meysman Manu Vanaerschot Maya Berg Hideo Imamura Jean-Claude Dujardin Kris Laukens Westa Domanova James R. Krycer Rima Chaudhuri Pengyi Yang Fatemeh Vafaee Daniel J. Fazakerley Sean J. Humphrey David E. James Zdenka Kuncic Plant Pathology and Plant-Microbe Biology Section School of Integrative Plant Science Cornell University Ithaca USA Graduate Field of Computational Biology Cornell University Ithaca USA School of Computing & Mathematics University of South Wales Cardiff UK Department of Genome Biology for Neurodegenerative Diseases German Center for Neurodegenerative Diseases (DZNE) within the Helmholtz Association ᅟ Germany Department of Surgery Massachusetts General Hospital The Broad Institute of MIT and Harvard Boston USA Department of Systems Biology Technical University of Denmark Kemitorvet Denmark Protein Physiology Lab Facultad de Ciencias Exactas y Naturales Universidad de Buenos Aires Buenos Aires Argentina Molecular Parasitology Unit (MPU) Institute of Tropical Medicine Antwerp Belgium Advanced Database Research and Modeling (ADReM) research group University of Antwerp Antwerpen Belgium Department of Computer Science University of Arizona Tucson USA Department of Veterinary Clinical and Animal Sciences Center for non-coding RNA in Technology and Health University of Copenhagen Copenhagen Denmark University College Dublin Dublin Ireland Department of Electrical Engineering (ESAT) STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium Minds Medical IT Department Leuven Belgium Scientific Institute of Public Health (WIV-ISP) Platform of Biotechnology and Molecular Biology (PBB) Brussels Belgium Department of Development and Regeneration @ Kulak KU Leuven Kortrijk Belgium Department of Biotechnology Bhupat and Jyoti Metha School of Biosciences Indian Institute of Technology Madras Chennai India Philips Research North America Briarcliff Manor USA Global Scientific Information and Computing Center (GSIC) Tokyo Institute of Technology Tokyo Japan Systems Biology Centre University of Warwick Senate House Coventry UK Systems Biology Doctoral Training Centre University of Warwick Senate House Coventry UK Center for B

A1 Highlights from the eleventh ISCB Student Council Symposium 2015 Katie Wilkins, Mehedi Hassan, Margherita Francescatto, Jakob Jespersen, R. Gonzalo Parra, Bart Cuypers, Dan DeBlasio, Alexander Junge, Anupama Jigisha, Farzana Rahman O1 Prioritizing a drug’s targets using both gene expression and structural similarity Griet Laenen, Sander Willems, Lieven Thorrez, Yves Moreau O2 Organism specific protein-rna recognition: A computational analysis of protein-rna complex structures from different organisms Nagarajan Raju, Sonia Pankaj Chothani, C. Ramakrishnan, Masakazu Sekijima; M. Michael Gromiha O3 Detection of Heterogeneity in Single Particle Tracking Trajectories Paddy J Slator, Nigel J Burroughs O4 3D-NOME: 3D NucleOme Multiscale Engine for data-driven modeling of three-dimensional genome architecture Przemysław Szałaj, Zhonghui Tang, Paul Michalski, Oskar Luo, Xingwang Li, Yijun Ruan, Dariusz Plewczynski O5 A novel feature selection method to extract multiple adjacent solutions for viral genomic sequences classification Giulia Fiscon, Emanuel Weitschek, Massimo Ciccozzi, Paola Bertolazzi, Giovanni Felici O6 A Systems Biology Compendium for Leishmania donovani Bart Cuypers, Pieter Meysman, Manu Vanaerschot, Maya Berg, Hideo Imamura, Jean-Claude Dujardin, Kris Laukens O7 Unravelling signal coordination from large scale phosphorylation kinetic data Westa Domanova, James R. Krycer, Rima Chaudhuri, Pengyi Yang, Fatemeh Vafaee, Daniel J. Fazakerley, Sean J. Humphrey, David E. James, Zdenka Kuncic

关键词： Visceral Leishmaniasis Feature Selection Method Frequent Itemset Mining Leishmania Donovani Student Council

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Profiling of Ribose Methylations in rna by High‐Throughput Sequencing†

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Angewandte Chemie 2014年第2期127卷

作者： Ulf Birkedal Mikkel Christensen‐Dalsgaard Nicolai Krogh Radhakrishnan Sabarinathan Jan Gorodkin Henrik Nielsen Department of Cellular and Molecular Medicine University of Copenhagen Blegdamsvej 3B 2200 Copenhagen N (Denmark) Center for Non‐coding RNA in Technology and Health Department of Veterinary Clinical and Animal Science University of Copenhagen Grønnegårdsvej 3 1870 Frederiksberg C (Denmark)

Ribose methylations are the most abundant chemical modifications of ribosomal rna and are critical for ribosome assembly and fidelity of translation. Many aspects of ribose methylations have been difficult to study due to lack of efficient mapping methods. Here, we present a sequencing‐based method (RiboMeth‐seq) and its application to yeast ribosomes, presently the best‐studied eukaryotic model system. We demonstrate detection of the known as well as new modifications, reveal partial modifications and unexpected communication between modification events, and determine the order of modification at several sites during ribosome biogenesis. Surprisingly, the method also provides information on a subset of other modifications. Hence, RiboMeth‐seq enables a detailed evaluation of the importance of rna modifications in the cells most sophisticated molecular machine. RiboMeth‐seq can be adapted to other rna classes, for example, mrna, to reveal new biology involving rna modifications.

关键词： Ribosome Ribozyme rna‐Erkennung rna‐Strukturen Transferasen

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Comparative ncrna gene and structure prediction using foldalign and foldalignM

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Current Protocols in Bioinformatics 2012年第SUPPL.39期39卷

作者： Havgaard, Jakob Kaur, Simranjeet Gorodkin, Jan Center for Non-Coding RNA in Technology and Health Department of Veterinary Clinical and Animal Sciences University of Copenhagen Copenhagen Denmark

This unit describes how to use Foldalign and FoldalignM to make structural alignments of non-protein-coding-rna (ncrna). These tools can be used to find new ncrnas, to find the structure of novel ncrnas, and to improv... 详细信息

关键词： ncrna ncrna gene finding non-coding rna rna multiple sequence alignment rna structural alignment rna structure prediction

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