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Article: OrthoFocus: program for identification of orthologs in multiple genomes in family-focused studies.

Ivliev, Alexander E / Sergeeva, Marina G

Journal of bioinformatics and computational biology

2008 Volume 6, Issue 4, Page(s) 811–824

Abstract: The identification of orthologs to a set of known genes is often the starting point for evolutionary studies focused on gene families of interest. To date, the existing orthology detection tools (COG, InParanoid, OrthoMCL, etc.) are aimed at genome-wide ... ...

Abstract	The identification of orthologs to a set of known genes is often the starting point for evolutionary studies focused on gene families of interest. To date, the existing orthology detection tools (COG, InParanoid, OrthoMCL, etc.) are aimed at genome-wide ortholog identification and lack flexibility for the purposes of case studies. We developed a program OrthoFocus, which employs an extended reciprocal best hit approach to quickly search for orthologs in a pair of genomes. A group of paralogs from the input genome is used as the start for the forward search and the criterion for the reverse search, which allows handling many-to-one and many-to-many relationships. By pairwise comparison of genomes with the input species genome, OrthoFocus enables quick identification of orthologs in multiple genomes and generates a multiple alignment of orthologs so that it can further be used in phylogenetic analysis. The program is available at http://www.lipidomics.ru/.
MeSH term(s)	Algorithms ; Base Sequence ; Chromosome Mapping/methods ; Molecular Sequence Data ; Sequence Alignment/methods ; Sequence Analysis, DNA/methods ; Sequence Homology, Nucleic Acid ; Software
Language	English
Publishing date	2008-08-28
Publishing country	Singapore
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2115015-1
ISSN	1757-6334 ; 0219-7200
ISSN (online)	1757-6334
ISSN	0219-7200
DOI	10.1142/s0219720008003692
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Drug Repositioning through Systematic Mining of Gene Coexpression Networks in Cancer.

Ivliev, Alexander E / 't Hoen, Peter A C / Borisevich, Dmitrii / Nikolsky, Yuri / Sergeeva, Marina G

PloS one

2016 Volume 11, Issue 11, Page(s) e0165059

Abstract: Gene coexpression network analysis is a powerful "data-driven" approach essential for understanding cancer biology and mechanisms of tumor development. Yet, despite the completion of thousands of studies on cancer gene expression, there have been few ... ...

Abstract	Gene coexpression network analysis is a powerful "data-driven" approach essential for understanding cancer biology and mechanisms of tumor development. Yet, despite the completion of thousands of studies on cancer gene expression, there have been few attempts to normalize and integrate co-expression data from scattered sources in a concise "meta-analysis" framework. We generated such a resource by exploring gene coexpression networks in 82 microarray datasets from 9 major human cancer types. The analysis was conducted using an elaborate weighted gene coexpression network (WGCNA) methodology and identified over 3,000 robust gene coexpression modules. The modules covered a range of known tumor features, such as proliferation, extracellular matrix remodeling, hypoxia, inflammation, angiogenesis, tumor differentiation programs, specific signaling pathways, genomic alterations, and biomarkers of individual tumor subtypes. To prioritize genes with respect to those tumor features, we ranked genes within each module by connectivity, leading to identification of module-specific functionally prominent hub genes. To showcase the utility of this network information, we positioned known cancer drug targets within the coexpression networks and predicted that Anakinra, an anti-rheumatoid therapeutic agent, may be promising for development in colorectal cancer. We offer a comprehensive, normalized and well documented collection of >3000 gene coexpression modules in a variety of cancers as a rich data resource to facilitate further progress in cancer research.
MeSH term(s)	Biomarkers, Tumor/genetics ; Cell Differentiation/genetics ; Cell Proliferation/genetics ; Data Mining/methods ; Drug Repositioning/methods ; Gene Expression/genetics ; Gene Expression Profiling/methods ; Gene Regulatory Networks/genetics ; Genomics/methods ; Humans ; Hypoxia/genetics ; Inflammation/genetics ; Neoplasms/genetics ; Signal Transduction/genetics
Chemical Substances	Biomarkers, Tumor
Language	English
Publishing date	2016
Publishing country	United States
Document type	Journal Article
ISSN	1932-6203
ISSN (online)	1932-6203
DOI	10.1371/journal.pone.0165059
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Coexpression network analysis identifies transcriptional modules related to proastrocytic differentiation and sprouty signaling in glioma.

Ivliev, Alexander E / 't Hoen, Peter A C / Sergeeva, Marina G

Cancer research

2010 Volume 70, Issue 24, Page(s) 10060–10070

Abstract: Gliomas are primary brain tumors with high mortality and heterogeneous biology that is insufficiently understood. In this study, we performed a systematic analysis of the intrinsic organization of complex glioma transcriptome to gain deeper knowledge of ... ...

Abstract	Gliomas are primary brain tumors with high mortality and heterogeneous biology that is insufficiently understood. In this study, we performed a systematic analysis of the intrinsic organization of complex glioma transcriptome to gain deeper knowledge of the tumor biology. Gene coexpression relationships were explored in 790 glioma samples from 5 published patient cohorts treated at different institutions. We identified 20 coexpression modules that were common to all the data sets and associated with proliferation, angiogenesis, hypoxia, immune response, genomic alterations, cell differentiation phenotypes, and other features inherent to glial tumors. A collection of high-quality signatures for the respective processes was obtained using cross-data set summarization of the modules' gene composition. Individual modules were found to be organized into higher order coexpression groups, the two largest of them associated with glioblastoma and oligodendroglioma, respectively. We identified a novel prognostic gene expression signature (185 genes) linked to a proastrocytic pattern of tumor cell differentiation. This "proastrocytic" signature was associated with long survival and defined a subgroup of the previously established "proneural" class of gliomas. A strong negative correlation between proastrocytic and proneural markers across differentiated tumors underscored the distinction between these subtypes of glioma. Interestingly, one further novel signature in glioma was identified that was associated with EGFR (epidermal growth factor receptor) gene amplification and suggested that EGF signaling in glioma may be a subject to regulation by Sprouty family proteins. In summary, this integrated analysis of the glioma transcriptome provided several novel insights into molecular heterogeneity and pathogenesis of glial tumors.
MeSH term(s)	Algorithms ; Astrocytoma/enzymology ; Astrocytoma/genetics ; Astrocytoma/pathology ; Brain Neoplasms/enzymology ; Brain Neoplasms/genetics ; Brain Neoplasms/pathology ; Cell Differentiation/genetics ; Gene Amplification ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Gene Regulatory Networks ; Glioma/enzymology ; Glioma/genetics ; Glioma/pathology ; Humans ; Oligodendroglioma/enzymology ; Oligodendroglioma/genetics ; Oligodendroglioma/pathology ; Receptor, Epidermal Growth Factor/genetics ; Receptor, Epidermal Growth Factor/metabolism ; Signal Transduction/genetics
Chemical Substances	Receptor, Epidermal Growth Factor (EC 2.7.10.1)
Language	English
Publishing date	2010-12-15
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1432-1
ISSN	1538-7445 ; 0008-5472
ISSN (online)	1538-7445
ISSN	0008-5472
DOI	10.1158/0008-5472.CAN-10-2465
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Article ; Online: Drug Repositioning through Systematic Mining of Gene Coexpression Networks in Cancer.

Alexander E Ivliev / Peter A C 't Hoen / Dmitrii Borisevich / Yuri Nikolsky / Marina G Sergeeva

PLoS ONE, Vol 11, Iss 11, p e

2016 Volume 0165059

Abstract	Gene coexpression network analysis is a powerful "data-driven" approach essential for understanding cancer biology and mechanisms of tumor development. Yet, despite the completion of thousands of studies on cancer gene expression, there have been few attempts to normalize and integrate co-expression data from scattered sources in a concise "meta-analysis" framework. We generated such a resource by exploring gene coexpression networks in 82 microarray datasets from 9 major human cancer types. The analysis was conducted using an elaborate weighted gene coexpression network (WGCNA) methodology and identified over 3,000 robust gene coexpression modules. The modules covered a range of known tumor features, such as proliferation, extracellular matrix remodeling, hypoxia, inflammation, angiogenesis, tumor differentiation programs, specific signaling pathways, genomic alterations, and biomarkers of individual tumor subtypes. To prioritize genes with respect to those tumor features, we ranked genes within each module by connectivity, leading to identification of module-specific functionally prominent hub genes. To showcase the utility of this network information, we positioned known cancer drug targets within the coexpression networks and predicted that Anakinra, an anti-rheumatoid therapeutic agent, may be promising for development in colorectal cancer. We offer a comprehensive, normalized and well documented collection of >3000 gene coexpression modules in a variety of cancers as a rich data resource to facilitate further progress in cancer research.
Keywords	Medicine ; R ; Science ; Q
Subject code	004
Language	English
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Exploring the transcriptome of ciliated cells using in silico dissection of human tissues.

Ivliev, Alexander E / 't Hoen, Peter A C / van Roon-Mom, Willeke M C / Peters, Dorien J M / Sergeeva, Marina G

PloS one

2012 Volume 7, Issue 4, Page(s) e35618

Abstract: Cilia are cell organelles that play important roles in cell motility, sensory and developmental functions and are involved in a range of human diseases, known as ciliopathies. Here, we search for novel human genes related to cilia using a strategy that ... ...

Abstract	Cilia are cell organelles that play important roles in cell motility, sensory and developmental functions and are involved in a range of human diseases, known as ciliopathies. Here, we search for novel human genes related to cilia using a strategy that exploits the previously reported tendency of cell type-specific genes to be coexpressed in the transcriptome of complex tissues. Gene coexpression networks were constructed using the noise-resistant WGCNA algorithm in 12 publicly available microarray datasets from human tissues rich in motile cilia: airways, fallopian tubes and brain. A cilia-related coexpression module was detected in 10 out of the 12 datasets. A consensus analysis of this module's gene composition recapitulated 297 known and predicted 74 novel cilia-related genes. 82% of the novel candidates were supported by tissue-specificity expression data from GEO and/or proteomic data from the Human Protein Atlas. The novel findings included a set of genes (DCDC2, DYX1C1, KIAA0319) related to a neurological disease dyslexia suggesting their potential involvement in ciliary functions. Furthermore, we searched for differences in gene composition of the ciliary module between the tissues. A multidrug-and-toxin extrusion transporter MATE2 (SLC47A2) was found as a brain-specific central gene in the ciliary module. We confirm the localization of MATE2 in cilia by immunofluorescence staining using MDCK cells as a model. While MATE2 has previously gained attention as a pharmacologically relevant transporter, its potential relation to cilia is suggested for the first time. Taken together, our large-scale analysis of gene coexpression networks identifies novel genes related to human cell cilia.
MeSH term(s)	Algorithms ; Animals ; Brain/cytology ; Brain/metabolism ; Cell Line ; Cilia/genetics ; Cilia/metabolism ; Cytoskeletal Proteins ; Databases, Genetic ; Dogs ; Dyslexia/genetics ; Fallopian Tubes/cytology ; Fallopian Tubes/metabolism ; Female ; Gene Expression Profiling ; Gene Expression Regulation ; Humans ; Microtubule-Associated Proteins/genetics ; Nerve Tissue Proteins/genetics ; Nuclear Proteins/genetics ; Oligonucleotide Array Sequence Analysis ; Organ Specificity ; Organic Cation Transport Proteins/genetics ; Proteomics/methods ; Respiratory System/cytology ; Respiratory System/metabolism ; Transcriptome
Chemical Substances	Cytoskeletal Proteins ; DCDC2 protein, human ; DNAAF4 protein, human ; KIAA0319 protein, human ; Microtubule-Associated Proteins ; Nerve Tissue Proteins ; Nuclear Proteins ; Organic Cation Transport Proteins ; SLC47A2 protein, human
Language	English
Publishing date	2012-04-25
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1932-6203
ISSN (online)	1932-6203
DOI	10.1371/journal.pone.0035618
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Systems-based analyses of brain regions functionally impacted in Parkinson's disease reveals underlying causal mechanisms.

Riley, Brigit E / Gardai, Shyra J / Emig-Agius, Dorothea / Bessarabova, Marina / Ivliev, Alexander E / Schüle, Birgitt / Schüle, Birgit / Alexander, Jeff / Wallace, William / Halliday, Glenda M / Langston, J William / Braxton, Scott / Yednock, Ted / Shaler, Thomas / Johnston, Jennifer A

PloS one

2014 Volume 9, Issue 8, Page(s) e102909

Abstract: Detailed analysis of disease-affected tissue provides insight into molecular mechanisms contributing to pathogenesis. Substantia nigra, striatum, and cortex are functionally connected with increasing degrees of alpha-synuclein pathology in Parkinson's ... ...

Abstract	Detailed analysis of disease-affected tissue provides insight into molecular mechanisms contributing to pathogenesis. Substantia nigra, striatum, and cortex are functionally connected with increasing degrees of alpha-synuclein pathology in Parkinson's disease. We undertook functional and causal pathway analysis of gene expression and proteomic alterations in these three regions, and the data revealed pathways that correlated with disease progression. In addition, microarray and RNAseq experiments revealed previously unidentified causal changes related to oligodendrocyte function and synaptic vesicle release, and these and other changes were reflected across all brain regions. Importantly, subsets of these changes were replicated in Parkinson's disease blood; suggesting peripheral tissue may provide important avenues for understanding and measuring disease status and progression. Proteomic assessment revealed alterations in mitochondria and vesicular transport proteins that preceded gene expression changes indicating defects in translation and/or protein turnover. Our combined approach of proteomics, RNAseq and microarray analyses provides a comprehensive view of the molecular changes that accompany functional loss and alpha-synuclein pathology in Parkinson's disease, and may be instrumental to understand, diagnose and follow Parkinson's disease progression.
MeSH term(s)	Animals ; Brain/metabolism ; Brain/pathology ; Disease Progression ; Gene Expression Regulation ; Humans ; Microarray Analysis ; Parkinson Disease/metabolism ; Parkinson Disease/pathology ; Proteins/analysis ; Proteins/genetics ; Proteins/metabolism ; Proteomics ; Sequence Analysis, RNA ; Signal Transduction ; alpha-Synuclein/analysis ; alpha-Synuclein/genetics ; alpha-Synuclein/metabolism
Chemical Substances	Proteins ; alpha-Synuclein
Language	English
Publishing date	2014-08-29
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1932-6203
ISSN (online)	1932-6203
DOI	10.1371/journal.pone.0102909
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Microarray retriever: a web-based tool for searching and large scale retrieval of public microarray data

Ivliev, Alexander E / Hoen, Peter A.C. 't / Villerius, Michel P / den Dunnen, Johan T / Brandt, Bernd W

Nucleic acids research. 2008 July 1, v. 36, no. suppl_2

2008

Abstract: The major public microarray repositories Gene Expression Omnibus and ArrayExpress are growing rapidly. This enables meta-analysis studies, in which expression data from multiple individual studies are combined. To facilitate these types of studies, we ... ...

Abstract	The major public microarray repositories Gene Expression Omnibus and ArrayExpress are growing rapidly. This enables meta-analysis studies, in which expression data from multiple individual studies are combined. To facilitate these types of studies, we developed Microarray Retriever for searching and retrieval of data from GEO and ArrayExpress. The tool allows access to the two repositories simultaneously, to search in the repositories using complex queries, to retrieve microarray data for published articles and to download data in one structured archive. The tool is available on the web at: http://www.lgtc.nl/MaRe/
Keywords	Internet ; gene expression ; meta-analysis ; microarray technology ; nucleic acids
Language	English
Dates of publication	2008-0701
Size	p. W327-W331.
Document type	Article
ZDB-ID	186809-3
ISSN	0301-5610 ; 0305-1048
ISSN	0301-5610 ; 0305-1048
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Microarray retriever: a web-based tool for searching and large scale retrieval of public microarray data.

Ivliev, Alexander E / 't Hoen, Peter A C / Villerius, Michel P / den Dunnen, Johan T / Brandt, Bernd W

Nucleic acids research

2008 Volume 36, Issue Web Server issue, Page(s) W327–31

Abstract	The major public microarray repositories Gene Expression Omnibus and ArrayExpress are growing rapidly. This enables meta-analysis studies, in which expression data from multiple individual studies are combined. To facilitate these types of studies, we developed Microarray Retriever for searching and retrieval of data from GEO and ArrayExpress. The tool allows access to the two repositories simultaneously, to search in the repositories using complex queries, to retrieve microarray data for published articles and to download data in one structured archive. The tool is available on the web at: http://www.lgtc.nl/MaRe/
MeSH term(s)	Databases, Genetic ; Gene Expression Profiling/methods ; Internet ; Meta-Analysis as Topic ; Oligonucleotide Array Sequence Analysis/methods ; Software
Language	English
Publishing date	2008-05-07
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	186809-3
ISSN	1362-4962 ; 1362-4954 ; 0301-5610 ; 0305-1048
ISSN (online)	1362-4962 ; 1362-4954
ISSN	0301-5610 ; 0305-1048
DOI	10.1093/nar/gkn213
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Article ; Online: Systems-based analyses of brain regions functionally impacted in Parkinson's disease reveals underlying causal mechanisms.

Brigit E Riley / Shyra J Gardai / Dorothea Emig-Agius / Marina Bessarabova / Alexander E Ivliev / Birgitt Schüle / Jeff Alexander / William Wallace / Glenda M Halliday / J William Langston / Scott Braxton / Ted Yednock / Thomas Shaler / Jennifer A Johnston

PLoS ONE, Vol 9, Iss 8, p e

2014 Volume 102909

Abstract	Detailed analysis of disease-affected tissue provides insight into molecular mechanisms contributing to pathogenesis. Substantia nigra, striatum, and cortex are functionally connected with increasing degrees of alpha-synuclein pathology in Parkinson's disease. We undertook functional and causal pathway analysis of gene expression and proteomic alterations in these three regions, and the data revealed pathways that correlated with disease progression. In addition, microarray and RNAseq experiments revealed previously unidentified causal changes related to oligodendrocyte function and synaptic vesicle release, and these and other changes were reflected across all brain regions. Importantly, subsets of these changes were replicated in Parkinson's disease blood; suggesting peripheral tissue may provide important avenues for understanding and measuring disease status and progression. Proteomic assessment revealed alterations in mitochondria and vesicular transport proteins that preceded gene expression changes indicating defects in translation and/or protein turnover. Our combined approach of proteomics, RNAseq and microarray analyses provides a comprehensive view of the molecular changes that accompany functional loss and alpha-synuclein pathology in Parkinson's disease, and may be instrumental to understand, diagnose and follow Parkinson's disease progression.
Keywords	Medicine ; R ; Science ; Q
Subject code	610
Language	English
Publishing date	2014-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Drug target prediction and repositioning using an integrated network-based approach.

Dorothea Emig / Alexander Ivliev / Olga Pustovalova / Lee Lancashire / Svetlana Bureeva / Yuri Nikolsky / Marina Bessarabova

PLoS ONE, Vol 8, Iss 4, p e

2013 Volume 60618

Abstract: The discovery of novel drug targets is a significant challenge in drug development. Although the human genome comprises approximately 30,000 genes, proteins encoded by fewer than 400 are used as drug targets in the treatment of diseases. Therefore, novel ...

Abstract	The discovery of novel drug targets is a significant challenge in drug development. Although the human genome comprises approximately 30,000 genes, proteins encoded by fewer than 400 are used as drug targets in the treatment of diseases. Therefore, novel drug targets are extremely valuable as the source for first in class drugs. On the other hand, many of the currently known drug targets are functionally pleiotropic and involved in multiple pathologies. Several of them are exploited for treating multiple diseases, which highlights the need for methods to reliably reposition drug targets to new indications. Network-based methods have been successfully applied to prioritize novel disease-associated genes. In recent years, several such algorithms have been developed, some focusing on local network properties only, and others taking the complete network topology into account. Common to all approaches is the understanding that novel disease-associated candidates are in close overall proximity to known disease genes. However, the relevance of these methods to the prediction of novel drug targets has not yet been assessed. Here, we present a network-based approach for the prediction of drug targets for a given disease. The method allows both repositioning drug targets known for other diseases to the given disease and the prediction of unexploited drug targets which are not used for treatment of any disease. Our approach takes as input a disease gene expression signature and a high-quality interaction network and outputs a prioritized list of drug targets. We demonstrate the high performance of our method and highlight the usefulness of the predictions in three case studies. We present novel drug targets for scleroderma and different types of cancer with their underlying biological processes. Furthermore, we demonstrate the ability of our method to identify non-suspected repositioning candidates using diabetes type 1 as an example.
Keywords	Medicine ; R ; Science ; Q
Subject code	006
Language	English
Publishing date	2013-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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