A Data Fusion Pipeline for Generating and Enriching Adverse Outcome Pathway Descriptions
暂无分享,去创建一个
Georgia Tsiliki | Haralambos Sarimveis | Egon Willighagen | Nina Jeliazkova | Friederike Ehrhart | Linda Rieswijk | Pekka Kohonen | Penny Nymark | Roland C Grafström | Chris T Evelo | Vesa Hongisto | H. Sarimveis | Egon Willighagen | C. Evelo | P. Kohonen | R. Grafström | Linda Rieswijk | G. Tsiliki | F. Ehrhart | V. Hongisto | N. Jeliazkova | P. Nymark
[1] Krister Wennerberg,et al. A transcriptomics data-driven gene space accurately predicts liver cytopathology and drug-induced liver injury , 2017, Nature Communications.
[2] P. Shannon,et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.
[3] Ola Spjuth,et al. Toward the Replacement of Animal Experiments through the Bioinformatics-driven Analysis of ‘Omics’ Data from Human Cell Cultures , 2015, Alternatives to laboratory animals : ATLA.
[4] Ali Emad,et al. Relationship Between Eosinophilia and Levels of Chemokines (CCL5 and CCL11) and IL-5 in Bronchoalveolar Lavage Fluid of Patients With Mustard Gas-Induced Pulmonary Fibrosis , 2007, Journal of Clinical Immunology.
[5] Angela N. Brooks,et al. A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles , 2017, Cell.
[6] Chris T. A. Evelo,et al. Presenting and exploring biological pathways with PathVisio , 2008, BMC Bioinformatics.
[7] Jie Dong,et al. Advances in mechanisms and signaling pathways of carbon nanotube toxicity , 2015, Nanotoxicology.
[8] François Schiettecatte,et al. OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders , 2014, Nucleic Acids Res..
[9] Dongmei Wu,et al. Transcriptomic Analysis Reveals Novel Mechanistic Insight into Murine Biological Responses to Multi-Walled Carbon Nanotubes in Lungs and Cultured Lung Epithelial Cells , 2013, PloS one.
[10] Denis Wirtz,et al. Hypoxia-inducible Factor 1 (HIF-1) Promotes Extracellular Matrix Remodeling under Hypoxic Conditions by Inducing P4HA1, P4HA2, and PLOD2 Expression in Fibroblasts* , 2013, The Journal of Biological Chemistry.
[11] Henning Hermjakob,et al. The Reactome pathway knowledgebase , 2013, Nucleic Acids Res..
[12] Ali Emad,et al. Levels of cytokine in bronchoalveolar lavage (BAL) fluid in patients with pulmonary fibrosis due to sulfur mustard gas inhalation. , 2007, Journal of interferon & cytokine research : the official journal of the International Society for Interferon and Cytokine Research.
[13] Chris T. A. Evelo,et al. The BridgeDb framework: standardized access to gene, protein and metabolite identifier mapping services , 2010, BMC Bioinformatics.
[14] Manuel C. Peitsch,et al. Systems Toxicology: From Basic Research to Risk Assessment , 2014, Chemical research in toxicology.
[15] Yong Qian,et al. mRNA and miRNA regulatory networks reflective of multi-walled carbon nanotube-induced lung inflammatory and fibrotic pathologies in mice. , 2015, Toxicological sciences : an official journal of the Society of Toxicology.
[16] Thomas C. Wiegers,et al. The Comparative Toxicogenomics Database: update 2017 , 2016, Nucleic Acids Res..
[17] Raymond R Tice,et al. Intersection of toxicogenomics and high throughput screening in the Tox21 program: an NIEHS perspective. , 2016, International journal of biotechnology.
[18] Georgia Tsiliki,et al. The eNanoMapper database for nanomaterial safety information , 2015, Beilstein journal of nanotechnology.
[19] Dominique Lison,et al. Mechanisms of lung fibrosis induced by carbon nanotubes: towards an Adverse Outcome Pathway (AOP) , 2015, Particle and Fibre Toxicology.
[20] Carlo Vancheri,et al. Common pathways in idiopathic pulmonary fibrosis and cancer , 2013, European Respiratory Review.
[21] Nianqiang Wu,et al. Mouse pulmonary dose- and time course-responses induced by exposure to multi-walled carbon nanotubes. , 2010, Toxicology.
[22] N. Todd,et al. Molecular and cellular mechanisms of pulmonary fibrosis , 2012, Fibrogenesis & tissue repair.
[23] David Allen,et al. Expert consensus on an in vitro approach to assess pulmonary fibrogenic potential of aerosolized nanomaterials , 2016, Archives of Toxicology.
[24] Andreas Krämer,et al. Causal analysis approaches in Ingenuity Pathway Analysis , 2013, Bioinform..
[25] D BurgoonLyle,et al. The AOPOntology: A Semantic Artificial Intelligence Tool for Predictive Toxicology , 2017 .
[26] Gary D. Bader,et al. The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function , 2010, Nucleic Acids Res..
[27] Jennifer Park,et al. Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems , 2015, Database J. Biol. Databases Curation.
[28] I. Laher,et al. Systems Biology of Free Radicals and Antioxidants , 2014 .
[29] A. Churg,et al. Mechanisms in the pathogenesis of asbestosis and silicosis. , 1998, American journal of respiratory and critical care medicine.
[30] Melvin E. Andersen,et al. Developing tools for defining and establishing pathways of toxicity , 2015, Archives of Toxicology.
[31] Andrew D. Rouillard,et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update , 2016, Nucleic Acids Res..
[32] Ryan Miller,et al. WikiPathways: capturing the full diversity of pathway knowledge , 2015, Nucleic Acids Res..
[33] Andrew Worth,et al. Applying Adverse Outcome Pathways (AOPs) to support Integrated Approaches to Testing and Assessment (IATA). , 2014, Regulatory toxicology and pharmacology : RTP.
[34] Albert Duschl,et al. The Significance and Insignificance of Carbon Nanotube-Induced Inflammation , 2014 .
[35] Ralf Herwig,et al. Analyzing and interpreting genome data at the network level with ConsensusPathDB , 2016, Nature Protocols.
[36] Minoru Kanehisa,et al. KEGG: new perspectives on genomes, pathways, diseases and drugs , 2016, Nucleic Acids Res..
[37] Melvin E. Andersen,et al. Incorporating New Technologies Into Toxicity Testing and Risk Assessment: Moving From 21st Century Vision to a Data-Driven Framework , 2013, Toxicological sciences : an official journal of the Society of Toxicology.
[38] C. Taylor,et al. Hypoxia-sensitive pathways in inflammation-driven fibrosis. , 2014, American journal of physiology. Regulatory, integrative and comparative physiology.
[39] Blanca Suarez-Merino,et al. High throughput toxicity screening and intracellular detection of nanomaterials , 2016, Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology.
[40] Thomas Hartung,et al. Making big sense from big data in toxicology by read-across. , 2016, ALTEX.
[41] Janine Ezendam,et al. Anchoring molecular mechanisms to the adverse outcome pathway for skin sensitization: Analysis of existing data , 2014, Critical reviews in toxicology.
[42] Mathieu Vinken,et al. The adverse outcome pathway concept: a pragmatic tool in toxicology. , 2013, Toxicology.
[43] Ralf Herwig,et al. The ConsensusPathDB interaction database: 2013 update , 2012, Nucleic Acids Res..
[44] Georgia Tsiliki,et al. Enriching Nanomaterials Omics Data: An Integration Technique to Generate Biological Descriptors , 2017 .
[45] Scott C. Wesselkamper,et al. Editor's Highlight: Application of Gene Set Enrichment Analysis for Identification of Chemically Induced, Biologically Relevant Transcriptomic Networks and Potential Utilization in Human Health Risk Assessment , 2017, Toxicological sciences : an official journal of the Society of Toxicology.
[46] Yong Qian,et al. Multi-walled carbon nanotube-induced gene expression in vitro: concordance with in vivo studies. , 2015, Toxicology.
[47] Yong Qian,et al. System-based identification of toxicity pathways associated with multi-walled carbon nanotube-induced pathological responses. , 2013, Toxicology and applied pharmacology.
[48] Don C Rockey,et al. Fibrosis--a common pathway to organ injury and failure. , 2015, The New England journal of medicine.
[49] Andrew Williams,et al. Nano-risk Science: application of toxicogenomics in an adverse outcome pathway framework for risk assessment of multi-walled carbon nanotubes , 2015, Particle and Fibre Toxicology.
[50] Thomas C. Wiegers,et al. Advancing Exposure Science through Chemical Data Curation and Integration in the Comparative Toxicogenomics Database , 2016, Environmental health perspectives.
[51] Nuno Nunes,et al. PathVisio 3: An Extendable Pathway Analysis Toolbox , 2015, PLoS Comput. Biol..
[52] Joyce K. Thompson,et al. Asbestos-Induced Oxidative Stress in Lung Pathogenesis , 2014 .
[53] Melvin E Andersen,et al. Adverse Outcome Pathways can drive non-animal approaches for safety assessment , 2015, Journal of applied toxicology : JAT.
[54] Yong Qian,et al. Multiwalled carbon nanotube-induced pulmonary inflammatory and fibrotic responses and genomic changes following aspiration exposure in mice: A 1-year postexposure study , 2016, Journal of toxicology and environmental health. Part A.
[55] T. Oury,et al. Oxidative stress in pulmonary fibrosis: a possible role for redox modulatory therapy. , 2005, American journal of respiratory and critical care medicine.